Fintech Dictionary: Terminology for the Digitalized Financial World (Contributions to Finance and Accounting) [1st ed. 2022] 9783658360559, 9783658360566, 3658360550

Table of contents :
Preface
Contents
Abbreviations
List of Figures
List of Tables
A-D
E-H
I-M
N-R
S-V
W-Z
Numerical Terms
Appendix
References
Index

Citation preview

Contributions to Finance and Accounting

Rainer Alt Stefan Huch

Fintech Dictionary

Terminology for the Digitalized Financial World

Contributions to Finance and Accounting

The book series ‘Contributions to Finance and Accounting’ features the latest research from research areas like financial management, investment, capital markets, financial institutions, FinTech and financial innovation, accounting methods and standards, reporting, and corporate governance, among others. Books published in this series are primarily monographs and edited volumes that present new research results, both theoretical and empirical, on a clearly defined topic. All books are published in print and digital formats and disseminated globally.

More information about this series at https://link.springer.com/bookseries/16616

Rainer Alt • Stefan Huch

Fintech Dictionary Terminology for the Digitalized Financial World

Rainer Alt Information Systems Institute Leipzig University Leipzig, Sachsen, Germany

Stefan Huch Department of Design Computer Science Media RheinMain University of Applied Sciences Wiesbaden, Hessen, Germany

ISSN 2730-6038 ISSN 2730-6046 (electronic) Contributions to Finance and Accounting ISBN 978-3-658-36055-9 ISBN 978-3-658-36056-6 (eBook) https://doi.org/10.1007/978-3-658-36056-6 © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2022 Translation from the German language edition: Fintech-Lexikon by Rainer Alt, and Stefan Huch, © Gabler Verlag 2021. Published by Gabler Verlag. All Rights Reserved. This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer Gabler imprint is published by the registered company Springer Fachmedien Wiesbaden GmbH part of Springer Nature. The registered company address is: Abraham-Lincoln-Str. 46, 65189 Wiesbaden, Germany

“As Co-Founder and Managing Director of CLARK, I am dealing with innovations and market developments in the financial industry day by day. I never stop learning. The Fintech Dictionary is helpful to quickly read up on new terminology around various business areas like tech, marketing, or sales.” —Dr. Marco Adelt, Co-Founder & Managing Director, Clark Germany and Host of the Performance Podcast “This Fintech dictionary is an invaluable contribution to explaining the complex and fast-evolving nomenclature of Fintech. The synthesis of ideas, concepts and definitions from financial services and digital technology is impressive in its coverage and depth. The book will be of interest and value to academic scholars and financial services managers alike.” —Dr. Christopher P. Holland, Professor of Information Management, Loughborough University, UK “In the global environment of an international consulting company, clients and partners expect me to be able to talk to them about their issues and to provide competent support in all aspects of financial service industry. This requires a broad knowledge and the ability to formulate complex issues in a simple and understandable way. The Fintech Dictionary is a providential reference work for me, in which the most important terms are presented and explained in a structured and understandable way—for me the perfect supporter to get an overview of the fintech scene.” —Joachim von Puttkamer, Global Head Financial Services, International Strategy & Management Consulting, Capgemini Invent “Working for a leading global company in Silicon Valley means customers look to us for guidance and solutions to their business challenges. I need to understand the business of my customers as well as their competitors in industries such as fintech. When I want to have an organized overview of the most relevant terms in the fintech and the startup world, I find the most relevant in the Fintech Dictionary, a perfect source to get into new terminologies.” —Anne Meier, Director Industries Marketing, Salesforces

Preface

The use of information technology (IT) in the financial sector is not new. As a result of the information intensity of financial services, IT is inherently linked with this industry and was among the first application areas when electronic followed analog information processing technologies since the mid-twentieth century. Large IT departments emerged in banks and insurance companies. Until today, the IT solutions developed by banks and insurance companies are still considered “monolithic” and thus not very flexible or innovative. Over the past 10 years, important changes have taken place under the term “financial technology” or “fintech” that have literally “awakened” the financial sector. Since then, an extensive transformation process has occurred in the financial sector that has been subject to little change for several decades. The fintech buzzword now sets a new tone in IT, particularly in the areas of digital transformation and startup companies. However, fintech presents itself as an emerging field of knowledge that is not clearly defined. This led to the question of which terms should be included in this dictionary and which should not be considered relevant. On the one hand, fintech is related to terms that are banking-specific as well as IT-related, for example new forms of investment such as exchange-traded funds or cryptocurrencies. On the other hand, the question was which of these developments should be considered. The growing area of cryptocurrencies illustrates this: in contrast to the 2000 cryptocurrencies at the end of 2019, almost 15,000 cryptocurrencies were included in this listing by December 2021. Although a large number of them only have little or even no market capitalization, the number exceeds an overview that is possible in this book by far. Therefore, a pragmatic approach was adopted, and we focused on the top 30 in terms of market capitalization on CoinMarketCap at the beginning of 2020 and 2021 (see Appendix). As shown in Fig. 1, the subject area fintech presents itself as an intersection of the three disciplines: business administration (especially finance), (economic) informatics, and social science (especially innovation management). Consequently, terms from these three fields have been considered for this dictionary. Ultimately, the selection remains subjective with all relevant terms not included being at our vii

viii

Preface

Fig. 1 Positioning of the fintech domain

Finance Fintech

Computer science

Innovation management

expense, as are any errors in the descriptions that might still be included. We would like to thank Christoph Jahntz and for his assistance in preparing the layout for this book and for Rocio Torregrosa from Springer for managing its publication. Leipzig, Germany Wiesbaden, Germany December 2021

Rainer Alt Stefan Huch

Contents

A–D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

E–H . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

79

I–M . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 N–R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 S–V . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 W–Z . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Numerical Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223

ix

Abbreviations

Abbreviation 2FA ACH AES AI AISP AML API AR ARPU ASIC ATM ATP BaaS BaFin BACS BCC BIAN BIC BIN BIP BLE blockDAG BMC BNPL BoT BPO BSV CAVE CBDC

Keyword in encyclopedia Two-factor authentication Automated clearing house Advanced encryption standard Artificial intelligence Account information service provider Anti-money laundering Application programming interface Augmented reality Average revenue per user Application-specific integrated circuit Automated teller machine Alternative trading platforms Blockchain-as-a-service Federal financial supervisory authority Bankers’ automated clearing system Bitcoin Cash Banking industry architecture network Bank identifier code Bank identification number Bitcoin improvement proposal Bluetooth low energy Block directed acyclic graph Business model canvas Buy now, pay later Banking of things Business process outsourcing Bitcoin SV Cave automatic virtual environment Central bank digital currency xi

xii

CDO CFD CFT CIR CJ CTF CPS DAG DAI DApp DAO DeFi DEX DID DLT DMA DNS DPA DPoS DRaaS DSA DVA E-banking E-bill E-business E-cash E-commerce E-health E-market E-payment E-venture E-wallet EBA EBICS EBPP EC ECB ECDSA EDI EEA EFI eID eIDV EMD

Abbreviations

Chief digital officer Contracts for difference Combating the financing of terrorism Cost-income ratio Customer journey Counter terrorist financing Cyber-physical system Directed acyclic graph Distributed artificial intelligence Distributed application Decentralized autonomous organization Decentralized finance Distributed exchange Decentralized identifier Distributed ledger technology Digital markets act, direct market access Domain name system Digital personal assistant Delegated proof-of-stake Disaster recovery-as-a-service Digital services act Digital voice assistant Electronic banking Electronic bill Electronic business Electronic cash Electronic commerce Electronic health Electronic market Electronic payment Electronic venture Electronic wallet European banking authority Electronic banking internet communication standard Electronic bill presentment and payment European Commission European central bank Elliptic curve digital signature algorithm Electronic data interchange Enterprise Ethereum alliance Embedded finance Electronic identity Electronic identity verification E-money directive

Abbreviations

ERP ETF ETL ETP F2F FIBO FIGI FinTS FIX FX GDPR HBCI HCE HFT HODL I4.0 IBAN ICO IDM IEO IF IIN IMPS IoT IOTA IPA IPO IS ISIN ISO IT ITIN IVA JSON KBA KID KPI KYC LBS LTV M2M MB MC MDL

xiii

Enterprise resource planning Exchange-traded funds Extract, transform, load Exchange-traded product Face-to-face Financial industry business ontology Financial instrument global identifier Financial transaction services Financial information exchange Foreign exchange General data protection regulation Home banking computer interface Host card emulation High frequency trading Hold on for dear life Industry 4.0 International Bank Account Number Initial coin offering Identity management Initial exchange offering Interchange fee Issuer identification number Immediate payment service Internet of things Internet of things Iota Intelligent personal assistant Initial public offering Information system International securities identification number International organization for standardization Information technology International token identification number Intelligent virtual assistant Javascript object notation Knowledge-based authentication Key information documents Key performance indicator Know your customer Location-based service Loan-to-value Machine-to-machine Megabyte Mass customization Mutual distributed ledger

xiv

MDP MIF MiFID ML MQTT MSC MSP MTF MVCC NEFT NFC NFT NLP NPV O2O OKA OLTP OS OTC OTP P2P PAN PAYD PAYU PBFT PCI PDI PFM PIMS PISP PoA PoB PoC PoET PoI PoO PoP PoR PoS PoSS PoW PSD2 PSP QC

Abbreviations

Multi-dealer platform Multilateral interchange fee Markets in financial instruments directive Machine learning Message queuing telemetry transport Merchant service batch Multi-sided platform Multilateral trading facility Multiversion concurrency control National electronic funds transfer Near-field communication Non-fungible token Natural language processing Net present value Online-to-offline Objectives and key results Online transaction processing Operating system Over-the-counter One-time password Peer-to-peer Primary account number Pay-as-you-drive Pay-as-you-use Practical byzantine fault tolerance Payment card industry Pure digital insurer Personal finance management Personal information management system Payment initiation service provider Proof-of-activity Proof-of-burn Proof-of-capacity, point-of-contact, proof-of-concept Proof of elapsed time Proof-of-importance, point-of-interaction Proof-of-object Point-of-purchase Proof-of-reserve Point-of-sale, proof-of-stake Point-of-sales selection Proof-of-work Payment services directive 2 Payment service provider Quantum computing

Abbreviations

QR Code RDA REPO REST RFID RO ROI RoPDE RPA RPC RTGS SaaS SaFE SCA SCP SDP SEO SEPA SIC SLA SME SDK SDN SOA SoV SPAC SPoC SPoT SSI SSO STP STO TAP TARGET TCO TDAG TEE TGE TIPS TPA TPI TPP TPPSP

xv

Quick response code Robotic desktop automation Research online, purchase offline Representational state transfer Radio frequency identification Retained organization Return on investment Return on product development expense Robotic process automation Remote procedure call Real-time gross settlement system Software-as-a-service Scaled agile framework Strong customer authentication Stellar consensus protocol Single-dealer platform Search engine optimization Single euro payments area Swiss interbank clearing Service-level agreement Small-to-medium enterprise Software development kit Software-defined networking Service-oriented architecture Store of value Special purpose acquisition company Single point of contact Single point of truth Self-sovereign identity Single sign-on Straight-through processing Security token offering Technical acceptance provider Trans-European automated real-time gross settlement express transfer Total cost of ownership Transaction-based directed acyclic graph Trusted execution environment Token generation event TARGET instant payment settlement service Token purchase agreement Third-party issuer Third party provider Third-party payment service providers

xvi

TPS TSP UID UNIFI UX VAS VC W3C WETH WIF WKN WoC XRP LCP XS2A, XSTA ZKP

Abbreviations

Transactions per second Token service provider Unique identifier Universal financial industry message scheme User experience Value-added service Venture capital World Wide Web Consortium Wrapped Ether Wallet import format Securities identification number Wisdom of crowds XRP ledger consensus protocol Access-to-account Zero-knowledge proof

List of Figures

Chapter 1 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 Fig. 10 Fig. 11 Fig. 12 Fig. 13 Fig. 14 Fig. 15 Fig. 16 Fig. 17 Fig. 18 Fig. 19 Fig. 20 Fig. 21 Fig. 22 Fig. 23 Fig. 24 Fig. 25

Access-to-account approach in PSD2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Target values for classic and agile approach . . .. . . . . . . . . .. . . . . . . . . .. . . Application areas of AI in the financial sector by complexity and intelligence . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . .. . . . .. . . . .. . . Algorithmization for business processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . API connection of financial services at a car manufacturer . . . . . . . . . Example of an API of the smartphone bank Revolut for an exchange rate query . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . Classification of an application system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Categories of artificial intelligence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structure of BLZ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reference bank model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Areas of Banking 2.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Example of a Bitcoin transaction in six steps . . .. . . . . . . . .. . . . . . . . . .. . . Chaining of data blocks in the blockchain . . . . . . . . . . . . . . . . . . . . . . . . . . . . Forms of business analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structure of BIC .. . . . . . .. . . . . . . .. . . . . . .. . . . . . . .. . . . . . .. . . . . . .. . . . . . . .. . . . Positioning and topics of business information systems . . . . . . . . . . . . . Business model canvas for neo bank N26 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Development stages of cognitive computing (examples of systems shown in italics) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Calculation of the combined ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structure of CUSIP (left) and transfer to ISIN (right) . .. . . .. . . .. . . .. . Functional areas of core banking systems . . .. . .. . .. . .. . .. . .. . .. . .. . . .. Calculation of the cost-income ratio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Path of a customer journey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Assessment of the competitive situation in the customer relevance model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Data-driven approach for a data-driven service .. . .. . .. . .. . .. . .. . .. . ..

2 4 5 7 10 12 12 14 18 19 21 27 29 32 33 34 35 40 43 43 47 48 56 57 60 xvii

xviii

Fig. 26 Fig. 27 Fig. 28 Fig. 29 Fig. 30 Fig. 31

List of Figures

Data innovation board . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Linear and acyclic data structure .. . .. . .. . . .. . .. . .. . . .. . .. . .. . . .. . .. . .. . Overview of DevOps principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Card-based digital payments in the four-corner model . . . . . . . . . . . . . . Dimensions of digitalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Centralized (left side) versus decentralized (right side) platform architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

61 62 66 70 73 76

Chapter 2 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 Fig. 10

Actors and effects in an ecosystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 E-commerce and financial management . .. . . . . . . . .. . . . . . . .. . . . . . . .. . . . 82 Topologies of electronic markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Alternative forms of electronic payments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Structure of FIGI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Application areas of FinTS . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Areas of fintech .. . .. . .. .. . .. . .. .. . .. . .. .. . .. .. . .. . .. .. . .. . .. .. . .. .. . .. . .. 96 Selected forks in Bitcoin and Ethereum 2008–2022 . . . . . . . . . . . . . . . . . 99 Actors and activities in the four-corner model . . . . . . .. . . . . . .. . . . . . .. . . 100 Structure of hash graph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106

Chapter 3 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 Fig. 10

Process steps of an ICO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structure of IBAN . . .. . .. .. . .. . .. . .. . .. .. . .. . .. . .. . .. . .. .. . .. . .. . .. . .. .. . Elements of an IoT architecture . .. . . . . . .. . . . . . .. . . . . . .. . . . . . .. . . . . . .. . . Message exchange scenario in payment transactions with ISO 20022 . . . .. . .. . .. . . .. . .. . .. . . .. . .. . .. . . .. . .. . .. . . .. . .. . .. . . .. . .. . .. . . .. . .. . KPIs in the balanced scorecard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Forms of learning in machine learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fees for a card payment using the example of Amazon Pay . . . . . . . . Bilateral integration and integration via middleware . . . . . . . . . . . . . . . . . Mobile payment as a connection to digital payments . . . . . . . . . . . . . . . . Bilateral vs. multi-bank relationships . . .. . . .. . . .. . . . .. . . .. . . .. . . .. . . .. .

113 116 119 121 123 127 129 131 133 134

Chapter 4 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8

Structure of NSIN using WKN as an example . . . . . . . . . . . . . . . . . . . . . . . Calculation of the net present value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Example of an open API banking architecture . . . . . . . . . . . . . . . . . . . . . . . Types of oracles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Example of the Bitfinex order book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Payment services in the value chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Platform concept versus ecosystem, electronic market and e-commerce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ROI calculation . . . .. . . . .. . . . .. . . . .. . . . . .. . . . .. . . . .. . . . .. . . . .. . . . .. . . . .. . .

138 139 145 148 148 150 155 166

Fig. 9 Fig. 10

RoPDE calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 Classification of RPA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169

Chapter 5 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9

Scrum process and ceremony . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Example of a smart contract . . .. . . .. . .. . .. . .. . . .. . .. . .. . .. . .. . . .. . .. . .. . Areas of Social CRM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structure of SEDOL (left) and transfer to ISIN (right) . . . . . . . . . . . . . . Actors and activities in the three-corner model . . . . . . . . . . . . . . . . . . . . . . . Integration of the token service provider in the four-corner model Example of a payment instruction as URI . . . . . . . . . . . . . . . . . . . . . . . . . . . . Example for an UTXO calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Distinction between traditional and virtual currencies . . . . . . . . . . . . . . .

173 181 183 188 193 194 200 201 205

List of Tables

Chapter 1 Table 1 Table 2 Table 3

Overview of consensus mechanisms . . . . . . . . . . . .. . . . . . . . . . . .. . . . . . . . . . Types of crowdfunding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Protocols for decentralized exchanges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45 50 63

Chapter 3 Table 1

Areas of innovation in the banking sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

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A–D

Aave As part of decentralized finance (!DeFi), this !cryptocurrency is used to coordinate transactions on a decentralized lending marketplace. Aave allows to make loans (!crowdlending) and to form lending pools with various other !cryptocurrencies (e.g., !ETH, !DAI), as well as to conduct asset (!digital asset) and collateral exchanges. Aave’s !liquidity !token is based on !Ethereum’s !ERC-20 token and has also been used to establish other decentralized exchanges (!DEX) such as !Uniswap. Accelerator Describes a initiative that comprises several stages that support or “accelerate” !startup companies over several months in their early business development. Similar to !regulatory sandboxes, selected !startup companies receive benefits from an organization known as accelerator or !incubator. Among the examples are the provision of premises (!co-working spaces), technical equipment, or access to networks and coaching seminars. In return, accelerators receive future profit sharing, pre-emption rights or minority shares from the !startup companies they have supported. Access-to-Account (XSTA, XS2A) Third-party (!TTP) access to payment services that has become a !business model of many !fintech companies. It is used, for example, to process financial transactions and to analyze customer-specific transaction data. In most cases this also refers to access to customer accounts, which banks need to grant third parties in connection with !PSD2. From a technological side, the European Banking Authority (!EBA) is responsible for the development of standards (so-called regulatory technical standards, RTS) regarding security, authentication and communication. In the !four-corner model, this gives rise to account information service providers (!AISP) and payment initiation service providers (!PISP), who have direct access to transacting parties (see Fig. 1). These service providers penetrate the previously closed system of banks and thus open the way to !multi-bank services. © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2022 R. Alt, S. Huch, Fintech Dictionary, Contributions to Finance and Accounting, https://doi.org/10.1007/978-3-658-36056-6_1

1

2

A–D

Closed traditional system

Open access-to-account system

Business transaction Payer

Business transaction Payee

Payer

Payee

PSP Validation

Routing

Payer bank/ issuing bank

Payee bank/ acquiring bank

Scheme

PISP/AISP Payer bank/ issuing bank

Regulation

Payee bank/ acquiring bank

Fig. 1 Access-to-account approach in PSD2

Account Information Service (AIS) Account information services, as defined in the EU’s second payment services directive (!PSD2), provide users with an overview of their financial situation. They consolidate information from one or more !payment service user accounts (!PSP). AIS providers (!AISP) are mainly !fintech companies, but also primary or house banks. With the consent of the account holder, it is possible to combine accounts of different banks on the !online banking platform or on personal finance management solutions (!PFM, !multi-bank). Account Information Service Provider (AISP) Providers of account information services (!AIS) yield access to payment accounts (!XSTA) and are involved in the execution of !electronic payments as defined by the EC’s Payment Services Directive (!PSD2). Acquiring Bank/Acquirer In the !four-corner model, the acquiring bank enables the merchant to accept card payments at the point of sale (!PoS). Acquirers act as financial service providers in the credit card environment, offering acquiring services to retail companies on behalf of the credit card companies. Based on cooperation agreements with card providers (!EMV), acquirers ensure the acceptance and processing of transactions on behalf of the merchant by forwarding commercial and technical data to the participating banks or financial institutions and the card providers. They establish a connection to their bank (!issuer) and authorize the payment. If the acquirer and !issuer are the same institution, these are so-called !on-us transactions. Besides supporting the accepting activities within card-related transactions, they often also provide the necessary hardware equipment and software at the merchant’s !POS. Acquirers may also act as !integrators and offer other payment methods (e.g., invoice, PayPal, !cryptocurrency). In the past, the scale-elastic market of acquirers has experienced a strong concentration in recent years, resulting in two dominant companies, the Danish Nets Group and the French Worldline.

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3

Advanced Encryption Standard (AES) With symmetric encryption methods (!cryptography) such as AES, the keys used for encryption and decryption are identical in contrast to !asymmetric encryption methods (!RSA). AES encrypts and decrypts data block by block using a key whose length can be 128 (AES-128), 192 (AES-192), or 256 (AES-256) bits. Compared to the previously used data encryption standard (DES), which is limited to 56 bits, AES offers higher security and is therefore often applied in the financial industry (e.g., !MAC). Agent In the banking context, this term is used for representatives or agents of financial service providers (e.g., a clearing agent for !CSMs, a paying agent for imprest accounts, or a bank agent for banks in general). In a technological sense, the term also refers to intelligent software agents, which denote software with some form of autonomous activity. For example, !chatbots with artificial intelligence (!AI) functionalities support customer advice, and agents are also used on !electronic markets to identify and compare offers and to negotiate with providers (e.g., regarding price, delivery terms, payment conditions). Aggregator Intermediary !business model (!intermediation) based on the bundling of services, which is present in many !fintech solutions. Similar to the !broker model, an aggregator mediates between providers of competing and/or complementary services on the one hand and clients on the other. In contrast to brokers, aggregators take possession of the transacted offerings and they are also responsible for setting prices. The aggregator model is found with !e-commerce platforms such as Amazon or banks that provide services of cooperating insurance companies (!bancassurance). If these digital services are also linked to digitized physical resources (!smart product), such as !electronic payment services for vehicle parking services, then the term !smart service or !mobility service is also used. Agile Organization An agile organization features a high degree of maturity regarding !digitalization as well as transformation management and is a core characteristic of !startup or !fintech companies. !Agility should increase the ability to react on changing conditions in the business environment, as they result from new customer demand, new competitors or new technologies. The aim is being able to quickly develop measures that contribute to !customer experiences, improved business processes or !business models on the one hand, and to establish agile change structures and processes on the other hand. The latter should sustain explorative approaches, fast learning processes as well as self-control and organization in the sense of an “agile mindset”. Agility Known from the literature on lean management, agility has spread to other domains, in particular software development. It denotes a procedure in development projects, which aims at attaining results iteratively in smaller chunks. Agile principles have

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Flexible

Stable

4

Goals/ quality

Costs Agile

Goals/ quality

Classic Costs

Time

Time

Fig. 2 Target values for classic and agile approach

established themselves especially in the development of !IT applications (e.g., !front-end- and !back-end applications) and is present in concepts such as !Scrum or Kanban. As shown in Fig. 2, the agile approach conceives costs and time as stable and adapts project goals and quality accordingly. In contrast, classical development approaches like the waterfall procedure consider goals to be stable and are often linked with exceeding cost and time budgets. This has often been the case with the introduction of complex !core banking systems. !Fintech businesses have typically adopted agile development methods, but had the advantage of a “greenfield approach”, i.e., non-existing legacy structures and systems (!legacy system). AI Application Areas As a general purpose technology, artificial intelligence (!AI) may be applied to many use cases. To structure potential application areas in the financial industry, a periodic table known from chemistry has been suggested (see Fig. 3). The x-axis shows the abilities that determine intelligent behavior (!AI) and the y-axis shows the complexity levels. It starts with applications that support the visual or acoustic perception of the world, e.g., for the recognition of images, speech or faces. In the case of visual perception, neuronal networks store characteristic features, such as eyes, nose and mouth, in order to recognize them as faces in other images. An example from the financial sector is the know-your-customer process (!KYC), which supports the identification of “high risk individuals”. Areas of application with the functional scope of processing focus on the conclusive processing of the perceptions. Natural language processing (!NLP) allows to recognize words with their meaning and, if the system is specified accordingly, also the mood of the text from the different word combinations, which might be valuable in oral or written conversations (!sentiment analysis) with customers. Action comprises applications that involve actions to achieve specific goals. The simplest field is “control”, which refers to the control of software or hardware depending on defined measured variables. These could be automated !AI systems for financial investments, which maximize the value of investment portfolios in predefined asset classes. If the !AI system decides to buy or sell a security based on the preferences defined by the investor and the current market situation, it executes this transaction on an

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Cm

Sr

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Complexity

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Ii

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Ir

Image recognition

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Ms

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Collaborative robotics

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Ml

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Navigation

Lr

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Decision making

Prediction

Sy

Egg

Cn

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Explaining

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Lc

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Fig. 3 Application areas of AI in the financial sector by complexity and intelligence (see Dietzmann & Alt, 2020)

!electronic exchange and adjusts the portfolio accordingly (!robo advisory). In contrast, the field of application collaborative robotics is more complex, since (physical) !robots are ultimately supposed to independently conduct actions that make sense in a given situation. An example is the (meanwhile discontinued) humanoid !robot Pepper, developed by the Japanese technology company SoftBank Robotics for customer advisory services in bank branches. This robot was programmed to pre-select the products relevant to the customer while the customer was waiting for a conversation with the (real) customer advisor. The learning cluster enhances the areas of perception, processing and action. Intelligent agents may generate new knowledge about their environment during perception and processing as well as during the execution of actions. Category learning, for example, aims to learn combinations of characteristic values and thus to categorize them. Pepper, for instance, could categorize faces according to their mood (e.g., does the new visitor in a bank branch appear safe or unsafe because of his behavior?) and learn new subcategories from the category of “unsafe visitors” (e.g., visitors who appear to be looking for something and visitors who Pepper would classify as potential bank robbers). The application area of relationship learning goes beyond learning categories, in that the !robot learns reactions to the respective category and assigns them to the categories (e.g., whether the customer is waiting for his appointment and might be happy about a first interaction with the expert robot). The !robot could identify the faces of customers and analyze their social media contacts to determine other friends of the customer who have also recently visited the store. Customers in a corresponding network could receive individual benefits for referring friends. These responses could be supplemented by other interaction possibilities (e.g., Pepper could learn that he only has to show some visitors the way to the water

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dispenser if they are categorized to look uncomfortable in the summer), whereby the usefulness of such scenarios or their cost-benefit-risk ratio requires critical validation in each case. Airdrop In analogy to helicopter money, Airdrop refers to give away !coins of existing or new !cryptocurrencies for free. This may occur to retain active customers, to acquire new customers and, in the course of marketing campaigns, upon the introduction of new !cryptocurrencies or after a !fork. Algorithm Describes a procedure or a regulation for solving complex problems or a class of problems, which are sufficiently formalized to be processed by an artificial system. Algorithms are mathematical calculation rules or logical rules anchored in program code that determine the calculation and/or evaluation of data (e.g., if-then conditions). Algorithms are often present in solutions based on artificial intelligence (!AI) and allow a high degree of automation in standardized or low-complexity financial processes, which are often typical for !fintech solutions. The application of algorithms in a specific setting is referred to as !algorithmization. Algorithmic Banking/Algo Banking Use of artificial intelligence methods (!AI) to support or execute banking processes. This includes, for example, !robo advisory or the credit assessment of an applicant with the help of !algorithms and social media activities (!social data). In some cases, no historical data of the applicant is necessary for the decision-making process. Algorithmic Trading/Algo Trading A method of !AI-based !agents that have been used in the banking sector since the !digitalization of stock exchanges (!electronic exchange) from the 1980s onwards. Automated trading systems manage larger portfolios and place orders depending on rules and price developments on the exchange. Algorithmic trading systems lead to high frequency trading (!HFT) when they place buy and sell orders in quick succession to realize (small) arbitrage. Algorithmization Describes the use of !algorithms in business processes. As shown in Fig. 4, existing processes are supported by information technology (!IT) and deliver data that is subject to analytics (!business analytics). The information gained on this basis yields the ability to adapt or learn independently and improve decisions. If, for example, an “intelligent” vehicle is involved in an accident, it can transfer the previously acquired data (n in Fig. 4) to the manufacturer’s network and suggest to other vehicles that they should brake earlier in this situation in future. This would lead to new insights and data, i.e., n + 1 in Fig. 4, which in turn are labeled to make them amenable for machine processing. Similarly, !algorithms are used in credit allocation or complaint management processes.

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Analytics

Data set (n) Digitalization

Existing processes

Digitalized processes Label data

Information

Algorithmization

Machine learning (ML) / Artificial intelligence (AI)

New insights (n = n+1)

Fig. 4 Algorithmization for business processes

Alipay Chinese provider of a !mobile payment system, who has experienced numerous expansions from a pure online !payment system to become a dominant !mobile payment system. Founded in 2004, Alipay meanwhile comprises a large user base of over one billion active users and over 80 million merchants, making it the largest !mobile payment system worldwide. Since 2014, the service is part of the Chinese Ant Group, a subsidiary of the Alibaba Group, which still holds a 30% stake in the company. Alipay features a !mobile wallet and is used on !e-commerce platforms (especially those of Alibaba such as Taobao and TMall) as well as for car sharing, food or !mobility services. Payments are supported by credit card, direct debit or !P2P. If this is done between Alipay users, no classical financial service provider is required. In addition, Alipay acts as an intermediary (!intermediation) to providers of insurances as well as investment and credit products (!microfinance), which consumers may use to finance the goods purchased via numerous platforms (!ecommerce). In addition to the large user base, the procedure for assessing creditworthiness based on artificial intelligence (!AI) and !big data is considered a competitive advantage. A main competitor of Alipay is !WeChat Pay of the Chinese Tencent Group. Altcoin Alternative !coins are !alternative currencies in the !cryptocurrency environment, which often originate from splits (!blockchain split) of existing !cryptocurrencies like !Bitcoin. Although these new !cryptocurrencies differ from “original currencies” like !Bitcoin, they typically feature many similarities regarding the !mining algorithm or the !wallet functionality. Well-known altcoins are !Bitcoin Cash, !Eos, !Iota, !Monero or !Xrp. One of the main motivations for the emergence of altcoins are higher levels of privacy and anonymity in !electronic payments based on !cryptocurrencies, for which the term !privacy coins has emerged. For example, Altcoins derive from !Bitcoins may be generated (“mined”), stored in virtual !wallets and traded via corresponding exchanges (!crypto exchange), much like !Bitcoin.

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Alternative Credit Scoring Refers to the use of publicly available consumer information to create reliable risk profiles of credit applicants. While traditional credit scoring is based on data from payment history, current debt, the length of credit history or the credit utilization ratio, alternative approaches also include additional data sources. Among the examples is Fico, which draws personal data from social networks (!social data) or online profiles, transaction-related data from past purchases, outstanding payments, cell phone payments, income or bank information. It enables customers without bank accounts to qualify for loans. Alternative Currency Currencies that are neither issued nor regulated by national banks of individual countries and are not recognized as official means of payment. The latter might change with !cryptocurrencies that are officially accepted (e.g., !Bitcoin in El Salvador) or launched by official institutions, in particular, by central banks (!CBDC). Among the examples for alternative or complementary currencies are !Ethereum Coins, !Ripple Coins and !Bitcoins, but also currencies that are present in regional communities. At least many of the electronic alternative currencies (e.g., !Bitcoin, !Diem, !Ether) are expected to face increasing regulation. Alternative Financing While traditional financing opportunities include banks, stock exchanges or overthe-counter (!OTC) capital markets, alternative financing instruments have emerged for specific purposes. For example, these focus on projects or transactions with a lower capital volume for financing innovative or creative projects, which often comprise a large number of small investors. Well-known forms of this segment of !fintech services are !crowdfunding and !crowdinvesting. Alternative Lending With !digitalization, !digital platforms have emerged as alternatives to traditional forms of financing that bring together lenders and donors. This is particularly relevant for small and medium-sized enterprises (!SME), people with low incomes (e.g., student loans) or lenders in emerging markets without access to the banking system. Alternative lending may be divided into the segments !crowdlending (for companies) and !P2P lending (for private persons). Alternative Trading Platform (ATP) Similar to electronic stock exchanges (!electronic exchange), alternative trading platforms bring together buyers and sellers of securities or assets to settle transactions. As privately operated markets, they define the trading and price-setting rules and are often less democratic in yielding transparency on the market action for all parties alike. Although they are less regulated than official exchanges, they are still subject to national regulatory authorities, such as the SEC (U.S. Securities and Exchange Commission) in the case of alternative securities platforms in the US. While in the US the term alternative trading system (ATS) is often used synonymously for ATP, it is multilateral trading facility (!MTF) in Europe. Among the established ATPs are the systems of large banks (e.g., Credit Suisse, Deutsche Bank, J.P. Morgan, Goldman

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Sachs or UBS) but also those of service providers such as Dealerweb or Instinet. Similarly, the more recent !cryptocurrency trading platforms (!crypto exchange) are considered ATPs, which still await regulation. Ambient Intelligence Similar to !pervasive computing, environmental intelligence assumes a widespread or ubiquitous presence of information technology (!IT). This includes mobile technologies and !wearables as well as small computing devices in physical objects (!IoT), which are present in various assistance scenarios (e.g., assisted living, personal trainer, smart home) or sales scenarios (e.g., personalized advertising in bank branches). Such scenarios often include digital services (!smart service), which are charged on a per-usage basis (!PAYU). Anti-Money Laundering (AML) The prevention of money laundering is a key activity in financial systems and comprises checks on deposits or transfers of sums of money above a certain amount. The goal is to determine the origin of the assets as well as the identification of the owners of the assets (!KYC). Regulations are enacted by the European Union (EU) as well as by individual countries. In Germany, for example, the money laundering act (GwG) implements the EU'’s money laundering directive. According to this directive, cash payments are limited to an amount of 2000 € since 2020 without being subject to a money laundering audit and cross-border cash amounts in excess of 10,000 € require a declaration within the EU. With the amendment of the fourth EU money laundering directive (Directive EU 2018/843), the regulations also apply to !crypto custody transactions, which makes !digital currencies such as !Bitcoin also subject to money laundering checks. Financial service providers have traditionally implemented such !compliance checks in their internal !application systems, but external service providers with service offerings in this !regtech segment (e.g., the Estonian provider Salv) have recently emerged. API Banking Describes the use of application interfaces (!API) for coupling digital services among service providers in and with the financial sector. It aims at connecting modular !application systems is based on the concepts of !open banking and !platform banking to enable efficient networking and !sourcing strategies among businesses in the financial industry. In a broader sense, API banking allows the connection of actors in the primary value creation process (i.e., an automotive manufacturer like in Fig. 5) with providers in the secondary value creation process (i.e., financial service providers like the !PSP in Fig. 5) in the sense of embedded finance (!EFI). Figure 5 shows the example of an automobile manufacturer, which links various !payment services to a platform via !API to process master and transaction data. It can also be interpreted as a form of !outsourcing of financial functions of the car manufacturer.

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Automotive manufacturer (OEM)

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Parking service

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Accounting API Further applications

API

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API

Collection agency

… API

OEM house bank

Fig. 5 API connection of financial services at a car manufacturer

App Economy Generic term to denote use of !applications (“apps”) within the economic environment. It includes the orientation and construction of these !ecosystems, the !business models within these !ecosystems as well as the value creation logic (e.g., !network effect). Since apps use !digital platforms such as !app stores for distribution, the term “platform economy” (!platform) is often used in a similar sense. App Store Short form for a digital distribution platform for application software or !applications (“apps”). Typically, an application or app store comprises a !digital platform with an electronic catalog, which includes a large number of apps from various providers that may be searched, ordered and downloaded by users on their devices. Since app stores bring together many providers and many users, they may be regarded as !digital marketplaces. In the financial industry, the app store principle is increasingly present in the concepts of !core banking systems that follow the idea of !open banking. Application (App) The abbreviation “app” for application has established itself as a term for application software (!application system) in the domain of desktop computers and mobile devices. The latter, i.e., smartphones or tablets, also use the term mobile apps, which are often limited in their range of functions and are related to or individualized for the respective user. If the functional logic of the application is mainly located on the server (instead as on the client device), it is referred to as a web application. Application-Specific Integrated Circuit (ASIC) Application-specific circuits is computing hardware that comprises a set of instructions that is specific for certain application purposes (e.g., graphics, file handling, computing operations). Compared to central processing units (CPUs) that may serve a broad range of application purposes, ASICs are less universally applicable, but

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they are more powerful in their field and tend to be more cost-effective by omitting functions that are not required for them. The ASIC approach dates back to the concept of reduced instruction set computers (RISC) from the 1960s and has recently gained importance with the spread of !artificial intelligence (e.g., for !deep learning) and cryptographic calculations (e.g., for !consensus mechanisms such as !PoW). In particular, !miners and !mining pools rely on ASIC hardware, while alternative !consensus mechanisms such as !proof-of-stake have emerged that claim to be ASIC-resistant. Application Programming Interface (API) Denotes an interface of an application software (!application system), which comprises the specification of an input and an output. It allows application programs to exchange data directly or without media discontinuities (!media break) and are the basis for !real-time processing in distributed environments. In contrast to a data interface, which yields access to a database, APIs are function interfaces where the input consist of commands with corresponding parameters that is needed to trigger functions in the target application. The concept has long been known in the modularization and integration of !application systems, as it reduces the complexity of large (so-called monolithic) systems on the one hand and creates the possibility of flexibly integrating specialized systems inside and outside the company on the other. In the financial industry, APIs are key in the current developments towards !API banking, !banking-as-a-service, !platform banking or !open banking. The connectivity that is embedded in these initiatives is also driven by regulations such as !PSD2, which requires banks to offer standardized APIs for accessing accounts on a non-discriminatory basis. Thus, they enable financial service providers such as !fintech companies to access banking systems to read transaction data and to derive their own services (e.g., !multi-bank functionalities) on this basis. In principle, all market participants may offer APIs, but in the financial sector approval is often required regulating authorities (e.g., !BaFin in Germany). An example of an API implemented using the !REST technology is shown in Fig. 6 for querying an exchange rate of 100 USD in Euros at the !neo- or !smartphone bank Revolut. It contains the function call (request/input) and the individual transferred data fields with their descriptions. The feedback (response/output) is displayed in !JSON format. Application System Part of an information system (IS) consisting of a hardware and a software system (see Fig. 7). The latter comprises the basic software such as the !operating system and the utilities (e.g., compilers, device drivers) as well as the application software, which contains functionalities for various application purposes. These refer to general functions such as e-mail or web browsers as well as industry- or sector-specific application functions, such as !core banking systems. The aim of business application systems is to achieve high degrees of business process automation and integration between an organization’s functional areas. For example, this is the case when securities are purchased electronically at !electronic exchanges via digital brokerage systems or payments are effects without manual intervention (!electronic payment). Although

12 Request (Request)

Feedback (Response)

A–D GET https://b2b.revolut.com/api/1.0/rate?from=USD&&to=EUR&amount=100 Fields: from (source currency in ISO country code), to (target currency in ISO country code), amount (bill of exchange amount in decimal) Fields: { "from": { from object: Data on source currency with amount (decimal) and ISO country code "amount": 100, "currency": "USD" To object: Data on target currency with }, amount (decimal) and ISO country code "to": { "amount": 78.9, "currency": "EUR" rate: Exchange rate (decimal) }, fee object: Bill of exchange fee (decimal) "rate": 0.789, and with ISO country code "fee": { "amount": 0.85, "currency": "EUR" rate_date: Date for proposed exchange }, rate in ISO date/time format "rate_date": "2019-0116T13:01:47.229Z" }

Fig. 6 Example of an API of the smartphone bank Revolut for an exchange rate query (see Revolut, 2020)

Fig. 7 Classification of an application system (see Alpar et al., 2019, p. 26)

information systems may be seen as application systems with strong user interaction, the terms information system, !application and application are often used synonymously. From an infrastructural perspective, application systems may be operated either !on-premise or virtually (!virtualization) in the form of !cloud computing on a !platform or decentralized on a distributed infrastructure (!DLT). In the latter case, the notion of decentralized applications (!DApp) has spread for !applications may be executed on the more recent !blockchain frameworks (!Blockchain x.0). Architecture 4.0 Based on the !enterprise architecture concepts, the notion “4.0” emerged to denote the elements of digitalized businesses. Following !digital transformation, architecture 4.0 combines innovative technologies like !IoT and !AI with !application and information systems within an architectural setting, i.e., a framework that

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structures and aligns all constituting elements. Architecture 4.0 is also linked with the transformation whereas !Fintech businesses define themselves more as technology than financial businesses. This leads to increased importance of !information technology in these companies, which have turned the operation from a support function to a central and strategically relevant corporate function. Drivers are !innovation, new !information technologies such as !Big Data, !Blockchain, !IoT and !AI form the cornerstones of the !digital transformation. From the !enterprise architecture perspective, this means that internal structures and resources (e.g., !application systems like !ERP and !core banking systems) are stronger linked to external resources and that new !business models need to be considered. Examples include !data-driven products and services. Architecture 4.0 approaches build on existing !artefacts and tools of business informatics (!business information systems) and aim, among other things, at a coordinated design of technological (e.g., !application systems, infrastructures such as !DLT), organizational (e.g., cross-company business processes) and strategic (e.g., !ecosystems, !business models) aspects. Artifact An artifact (lat. “artificial structure”) describes a model produced with a specific tool. In the context of !digitalization, numerous (mostly immaterial) artefacts exist that represent the results of design-oriented work or research (e.g., business, process and architecture models or software code). For the creation and the development of models, a variety of modeling languages has emerged (e.g., BPMN for business processes, UML for information systems), which may be used with graphical modeling tools like ARIS, Signavio or Visio. Due to their formalization, the models may be used in workflow and !RPA technologies, which enable digitalized processes. Artificial Intelligence (AI) In the middle of the twentieth century, the field of artificial intelligence (AI) emerged to denote activities that strive for realizing human intelligence by machines. Following neuroscience, intelligence is based on abilities regarding perception, processing, action and learning. Already in the 1980s rule-based (expert) systems were developed, which allowed to analyze tasks following if-then rules and suggested possible decisions or recommendations. Today, the broad availability of data (!big data) and advances in computing power, have enabled AI to extract patterns from complex unstructured data sets (input) and to learn from them or to adapt their future behavior based on past events (output). As shown in Fig. 8, AI concepts (or methods) may be subdivided in various categories with machine learning (!ML) being an important area that applies artificial neural networks whose complexity (i.e., the number of input and output layers used) leads to !deep learning (i.e., two or more hidden layers). Neural networks process predefined (so-called supervised learning) or observed (so-called unsupervised learning) input data and store the results in a network of nodes (or neurons), which calculate transition probabilities for an output or recommended action and optimize them with each iteration. Although the depth of these networks tends to improve the

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Artificial intelligence Machine learning Neural networks Deep learning

Generic term for automation of „intelligent“ tasks Automatic generation of knowledge from experience Learning scheme based on networked artificial neurons I1

O1

I2

O2

I3

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Hidden layers

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Fig. 8 Categories of artificial intelligence

quality of decisions, the number of hidden layers makes the decisions of the artificial neural networks less transparent and comprehensible for humans. A general field of application is natural language processing (!NLP), where neuronal networks store correlations of words and then use them for voice recognition. Depending on the form of learning and the complexity of the application, a variety of application areas exist in the financial sector (!AI application areas). Asymmetric Encryption An encryption method (!cryptography) where the sender and receiver are using different keys. While both sides are using the same keys in symmetric encryption methods like the advanced encryption standard (!AES), asymmetric methods are based on a combination of public (!public key) and private (!private key) keys. The established method is !RSA, which is considered secure in the currently known computer architectures and has therefore reached broad adoption. More recently, other asymmetric methods have emerged in for !blockchain networks, in particular !ECDSA. In parallel, other recent developments such as !quantum computing are endangering existing cryptographic solutions, since these technologies are expected to solve complex prime number calculations within substantially shorter processing times. Atomic Swap In the !cryptocurrency environment, swaps refer to the direct transfer of !coins between users (“wallet-to-wallet”) according to the peer-to-peer model (!P2P), i.e., without the use of intermediaries (!intermediation) such as !crypto exchanges. The procedure requires a high degree of !interoperability of !DLT technologies and is considered to be disruptive (!disruption) for payment transactions. Augmented Reality (AR) Technologies in the field of AR expand the perception of reality by enriching or overlaying the real environment with user-specific information. Among the examples are visualizations in head-up displays (HUD) or by special interactive glasses (!wearable), which, for instance, show the product price or additional product information (such as financing information or the development of the account balance for an assumed purchase of the product). Many banks and especially !big tech companies have launched AR projects (!metaverse) since they expect

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large potential in the financial industry due to the high level of interaction and immateriality. Authentication In this method of !identity verification (!KYC) users provide personal data that allow providers to verify that a person is actually the person he or she claims to be. Common authentication methods are passwords or identification numbers (PIN), identity documents or devices (e.g., smartcards, !token, badges) or biometric features (e.g., fingerprints, iris scans). Typically, the data provided by the user are validated with the data in the provider’s systems. !Identity management services have emerged to support customers in the process of signing up (!onboarding) with service providers. Authorization Also known as !legitimation, this is the second level of !identity verification after !authentication. Here, the service provider checks whether the person is authorized to use the services (e.g., to order securities). A subsequent check in the financial sector is often the credit rating. If limits are exceeded, the authorization will typically be denied. Service providers such as the European Banking Authority (!EBA) with myBank have developed solutions for electronic authorization. Automated Clearing House (ACH) Electronic network for clearing payment orders (e.g., direct debits, credit transfers) between service providers in the domain of national and/or international payment transactions. Clearing comprises the electronic exchange (!EDI) and the net settlement of payments. The clearing of orders is typically not carried out in real time (!real-time processing), but at certain defined points in time (e.g., several times a day) and differs from the gross settlement procedure (!RTGS). Originally, the ACH term was associated with the electronic processing of checks in the US, which required 3–4 days for the clearing and settlement of a payment order. Today the term is also used globally and the systems have become more efficient (typically payment processing until the next day, t + 1). An example of ACH payment are !SEPA payments in Europe via the Step2 system, which uses the central bank accounts of the participating financial service providers in the TARGET settlement system. Providers of !payment services in the !fintech area access the services of an ACH via electronic interfaces (!API) from their national ACH systems. In Germanspeaking countries, the German Central Bank, Swiss Interbank Clearing (!SIC) and the Austrian National Bank, among others, operate as ACH. In Great Britain it is !BACS and in the US, among others, the Federal Reserve Bank. Compared to the ACH approach with networked national hubs, more recent decentralized approaches based on distributed ledger technology (!DLT such as !Ripple) promise more real-time and less costly transactions. However, they still fall short in terms of scalability and feature substantially lower transaction rates (!TPS). Automated Market Maker (AMM) Term used in decentralized financial systems (!DeFi) for the providers of !liquidity (!liquidity pool). Similar to securities traders or market makers in

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traditional stock exchange trading, AMMs offer !tokens, which are !smart contract bundles and automatically execute when there is a corresponding demand. AMMs may thus be conceived as an alternative to the !order books familiar to centralized stock exchange trading. Automated Teller Machine (ATM) In the 60 years of their existence, cash machines have become important contact points for customers. They evolved from pure cash dispensers to comprehensive !self-service stations. However, they are increasingly displaced in the course of the substitution of cash with !electronic money and with the rise of other self-service solutions, in particular !e-banking and !mobile banking. At the same time, !fintech companies have launched ATMs for !cryptocurrencies (for list of !Bitcoin ATMs see https://coinatmradar.com). Average Revenue Per User (ARPU) This metric (!KPI) is key in !business cases of !fintech business models (!business model) and in particular of !platform-based business models, which aim at attaining large user bases to generate !network effects. B3i Initiative by 21 companies from the insurance sector (e.g., Aegon, Allianz, Generali, Swiss Re, Zurich) for developing the use of !blockchain technologies. Since its launch in 2016, the initiative has grown to 40 participants in 2021, among them also software and consulting companies such as MSG and TCS. The first application B3i Re involves the mapping of catastrophe loss contracts (known as excess of loss reinsurance or catastrophe excess of losses, Cat XoL) between insurance and reinsurance companies. A second use case has been announced in the field of claims management. From a technological perspective, B3i’s Fluidity platform is based on !Corda. Back-End Describes the logic for the execution of technical functionalities and complements the !front-end, which focuses on user interaction. Among the examples are the transaction-oriented functionalities of !core banking systems as well as the distributed ledger functionalities of many !cryptocurrencies (!DLT). Back-ends are typically used via interfaces (!API). Back-Office Describes the business processes of financial service providers “behind” the !frontand the !middle-office. As back-office processes like opening accounts or processing transactions occur repeatedly along a defined and reliable workflow, the goal is to achieve high efficiencies through scale and standardization. To automate back-office operations, !core banking (or core insurance) systems have emerged since the 1960s and since the 2000s the area has also seen many attempts to outsource tasks to !third-party providers, which have the ability to achieve higher scale than individual banks (or insurances). Among the !sourcing models are in particular !transaction banks.

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BaFin The Federal Financial Supervisory Authority (Bundesanstalt für Finanzdienstleistungsaufsicht in German) supervises banks, financial service providers, insurers and securities trading in Germany. It is an independent institution under public law and subordinate to the Federal Ministry of Finance. Among others, BaFin grants the licenses to conduct commercial financial activities, in particular in the field of payments and loans, and receives fees and contributions from the supervised institutions and companies. Depending on their structure, the various !fintech business models may require a !bank license from BaFin, e.g., in payments, funding or portfolio management. Although BaFin has published several statements on !fintech business models and the application of emerging technologies (e.g., !blockchain, !robo advisory, !mining services), a final assessment often requires an individual case-by-case examination. Baking An alternative term used in !proof-of-stake based systems for the validation and addition of data blocks in a !blockchain. It corresponds to the !mining activity in !PoW-based !cryptocurrencies. For example, each participant in the !Tezos system may act as a baker, who owns more than 10,000 XTZ, but is more likely to be selected (and paid) for it, the more !coins he possesses. Bancassurance Refers to services that bundle banking and insurance services. The concept is based on a holistic view of the financial industry (so-called one-stop financial services) and assumes synergies between the two service areas. For example, customers could also opt for a property or household insurance policy or integrate life insurance into their investment portfolio when deciding on mortgage financing. Bancassurance solutions have emerged in the 1990s and have resulted in partnerships, joint ventures and mergers between banks and insurance companies. In 1997, for example, Credit Suisse took over Winterthur Insurance in Switzerland, but sold it to the French Axa insurance group in 2006 due to its unprofitable bancassurance strategy. The reasons for the failure of these early bancassurance concepts include the unwillingness of clients to entrust all financial services to one institution as well as the separate !back-end processes and systems. With the transition to more technologically affine !generations of customers and with more modular !application systems (!API banking), bancassurance approaches have experienced a second “wave” with the !fintech evolution. Today, there are partnerships in Switzerland between UBS and Swiss Re for life insurance for real estate owners, between the Raiffeisen Bank and Mobiliar Insurance for real estate ownership services, or between !fintech companies, such as the insurance !startup company Smile and the !smartphone bank Neon. In contrast, the German !neo bank N26 and the !robo advisory service Clark ended their cooperation in mid-2020 after 3 years. The different frequency of customer contact has been recognized as an important motive for bancassurance: while customers often check their bank account via !online banking, contacts with the insurance company usually only occur in the event of a loss or a claim. By cooperating with a bank, insurers may benefit from

18 Fig. 9 Structure of BLZ

A–D Banking group (1-digit) Clearing area (3-digits)

Bank individual (4-digits)

5 0 0 7 0 0 2 4

higher customer interaction frequencies, while they are depending stronger from the bank or the !digital platform used. This strategic downside has led insurance companies to launch their own multi-provider solutions (!PFM). Bank Code (BLZ) Identification number for banks and credit institutions in Germany that was initiated in 1970 by the German central bank. Referred to as BLZ (German for “Bankleitzahl”), it consists of eight numeric digits in Germany and a variant with five numeric digits in Austria. Since the introduction of !SEPA, the bank code has been part of the !IBAN. The first three digits of the BLZ shown in Fig. 9 identify the location number with a regional identifier in the eight clearing areas in Germany that are organized by federal states. The fourth digit specifies the affiliation with a particular banking group (e.g., central bank as well as savings, cooperative and private banks), and the remaining four digits denote the respective individual institutions. Figure 9 shows the code for Deutsche Bank headquartered in the county of Hessen (clearing area 500 for Frankfurt am Main) and the banking group (7 for Deutsche Bank and subsidiaries). Bank Identification Number (BIN) !Issuer identification number. Bank Identifier Code (BIC) !Business identifier code. Bank Informatics Domain-specific part within the scientific discipline of !business information systems, which features the analysis and the design of information and !application systems in the banking industry. Bank License Certification from federal institutions (i.e., regulatory agencies like !BaFin in Germany) that awards permissions to conduct commercial financial activities. While full banking licenses cover the execution of all banking transactions, partial bank licenses focus on certain activities such as securities trading or payment processing. Depending on the services offered, the regulatory agencies assess whether a !fintech company requires a license for their !business model. The license to operate a deposit-taking credit institution is granted by the European Central Bank (ECB), in coordination with national supervisory authorities. In Germany this is !BaFin on the basis of paragraphs 32 and 33 of the German

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Account management Product development Product master maintenance

Crosstransaction processes

Risk management Internal monitoring Customer reports Cross-functional processes

Support processes

Human resources (HR) Accounting Marketing Document management Management information Legal reporting Procurement Information technology (IT) Security logical/physical

Payment traffic monitoring Position and account reconciliation Corrections and investigations

Operating and investment loans

Corporate finance

Mortgages

Lombard loans

Building loans

Financial consulting

Commitment credits

Title transfer Securities monitoring Position and account reconciliation Administrative actions Corrections and investigations

Private financing and leasing

Money market

Foreign exchange

Supervision/monitoring Management transactions Handling exceptions

Precious metals

Transactionspecific processes

Derivatives, structured products

Initialization Registration Audit Release Processing

Funds (own and foreign)

Transaction processes

Information on customers (KYC) Preparation, planning and establishment of contacts Payment transaction consulting Investment consulting Offer preparation, adjustment and acceptance and rejection Signing of the contract Monitoring of implementation and identification of need for action

Participation papers

Information Contact Advice Offer Closing Care

Debt securities

Distribution processes

Cheque

Planning, control and control

Financing

Planning and management control Partner, service, architecture and transformation management Channel management and sales control Risk management and controlling Problem and exception management

Direct debit

Management processes

Customer processes Securities

Payments

Cards (credit and debit) Electroinc bill presentment and payment

Activities

Payment order (cash and giro) Standing order and master list Exchange of physical data medium

Bank processes

19

Credit monitoring Commission and interest charges Repayment Corrections and investigations

Opening, management, netting, research (e.g. dormant assets) Partner administration (e.g., custodians, financial data providers, correspondent banks, counterparties) Payment product development Credit product development Securities product development Payment transaction fee maintenance Credit fee maintenance Securities fee maintenance Management collateral Securities master maintenance Credit risks and non-performing loans Total exposure monitoring Liquidity management (e.g., liquidity planning, repo or repurchase transactions, refinancing, securities loans) Bank, legal and regulatory and directives/compliance Client output (e.g., securities account statements, account statements, performance statements,) Portfolio management Credit portfolio management Analysis and research (securities, industries, economies, financial markets) Financial planning and tax advice for natural persons Business valuation, succession planning, financial planning for legal entities Administration, payroll accounting, working time management and employee development Income statement, accounting, proprietary trading (nostro, market maker) and taxation/fees External appearance (e.g., brochures, samples, campaigns ) Templates,and archiving Key figures, evaluations, and internal reporting External reporting (e.g., national bank, stock exchanges, supervision, EU taxation of interest income) Office supplies, software and hardware Operation and development of IT infrastructure and application systems Authorizations and infrastructure monitoring

Fig. 10 Reference bank model (see Alt & Zerndt, 2020, p. 234)

Banking Act (KWG) in conjunction with article 4 (1) of the SSM Regulation (Single Supervisory Mechanism). !Fintech providers such as Revolut illustrate the international character, as the !smartphone bank has its headquarters in Great Britain and a bank license from Lithuania. In addition, some countries have developed dedicated licenses for !startup companies in the !fintech sector that provide for simplified requirements (e.g., the so-called !fintech license issued by the Swiss !Finma). Further regulations exist for !cryptocurrencies (e.g., the application of the money laundering directive to !digital currencies or !crypto custody transactions in Germany since 2020) or !electronic money (e.g., the EU’s !e-money directive). Bank Model The !reference model presents a concise overview on all processes and functional areas of a bank. With an emphasis on universal and private banks (investment banks differ in certain areas), it structures the main business areas of a bank (payments, investments and loans) in the horizontal dimension and the main business processes (management, distribution, execution, support) in the vertical dimension (see Fig. 10). The core operational processes are reflected in the areas of sales processes on the one hand and transaction processes on the other, whereby the latter can be further subdivided into the processing of individual transactions itself and activities that are

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related to a specific transaction and to multiple transactions (cross-transaction). Particularly in transaction processing and transaction-related processes, there are differences along the horizontal business areas, resulting in process variants, which may be detailed further in (reference) process specifications (e.g., process diagrams in BPMN notation). In the payments area, for example, the processes differ according to the variants of !electronic payments, i.e., whether it is a card payment or a credit transfer or direct debit. Similarly, the investment area contains process variants for the various investment instruments, such as funds, derivatives or foreign exchange. !Fintech companies may use the bank model for several purposes: (1) to define their own services in the market, (2) to align their (often standardized and limited) own offering with partners in the network (!ecosystem), (3) to compare or benchmark their own services with competing services in the market, (4) to develop process variants on the basis of more detailed reference processes and (5) as a functional basis to evaluate and assign !application systems or !apps within an overall architecture framework (!core banking system, !architecture 4.0). A similar banking model is the M4Bank model developed by !BIAN. Bank-as-a-Service A term often used synonymously with !platform banking to denote providers of !open banking solutions (e.g., the !startup companies Mambu and Banksapi). The concept is recognized as an important enabler for embedded finance strategies (!EFI). Bankers’ Automated Clearing System (BACS) Automated clearing house (!ACH) in the United Kingdom (UK). The system includes the processing, clearing and settlement of payments, including the automated UK Bacs Direct Credit, to initialize and receive payments by electronic transfer. Banking 2.0 Term that reflects the changing banking business with !digital transformation based on channel integration (!omni-channel), artificial intelligence (!AI) and data-driven solutions (!data-driven approach, !algorithmization). Banking 2.0 also captures the emergence of !fintech companies an !platform solutions (!open banking, !platform banking) in the banking sector. An example of Banking 2.0 that covers all customer groups and distinguishes the four main subject areas, online and offline channels, !smart processes and data is shown in Fig. 11. Banking Industry Architecture Network (BIAN) Founded in 2008, this non-profit association of banks, software providers and academic institutions aims at definitions for banking modules that foster the networking among service providers in the banking industry. In 2018, the organization comprised 60 members in 2018, who collaborated in the development of two !artefacts. The main model is the BIAN service landscape, which presents a framework and specifications for linking services of multiple providers. By means of agreed service interfaces (!API), application functionalities of different software manufacturers and service providers (!TPP) should be designed as interoperable

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21

New online and mobile channels

1

Mobile banking Online/mobile^brokerage Smartwatch banking Video consulting Chat and co-browsing Social media/platforms

Channel integration

3

Renewed offline channels • • •

Intelligent industry concepts Flagship and satellite stores Intelligent industry infrastructure (e.g. Genius Bar, WiFi, beacons, geolocation)

Data as "nerve center"

Digitalized processes

Intelligent data

• • • • • • •

• • •

Digital account opening Digital payments Digital investment consulting Personal finance manager Digital signatures, fingerprint authorization Video authentication Online loans

2

Peer group trading Trigger concept Self-directed banking

2

Information and insights

Channel integration

1

• • • • • •

Information and insights

Fig. 11 Areas of Banking 2.0

(!open banking) functional modules (!web service). The BIAN service landscape is currently available in its ninth version (per October 28, 2020) and comprises modules in the business areas of reference data, sales and service, operations and execution, risk and compliance, and business support. The second model is called M4Bank and summarizes the service domains of the service landscape along a value chain visualization (!bank model) with the main building blocks being business direction, finance and risk management (with operations, products, customers, channels), resource management and business development. Banking-as-a-Service With the emergence of !cloud computing, many providers of !core banking systems as well as !fintech businesses have started offering !SaaS solutions for banks as well as for !non-banks. The concept is closely related to !API banking and !open finance, but emphasizes the classical approach of standard software whereas the main functionalities of a bank may be sourced from one provider. Similar to the claim of !cloud computing providers, banking-as-service relies on configuration rather than comprehensive customization to enable a quick time to market. Banking Innovation Refers to !innovations in the banking sector and may be interpreted as a harbinger of !fintech. In contrast to the !fintech term, the focus is on the different facets of !innovation (i.e., technological, organizational, cultural innovation in the various banking functions, see !bank model) and less on the !startup nature of the companies that are driving the !innovation. Along the design levels that are established in the !business information systems discipline, banking innovations may be structured along the levels strategy, organization and technology. An overview with examples of banking innovations is shown in Table 4 under the keyword !innovation.

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Banking of Things (BoT) To denote the application of !IoT technologies in banking processes and in !fintech !business models, BoT has emerged as a domain-specific version of internet of things. For example, smart machines (e.g., !ATMs, !smart products) might directly order their spare or maintenance parts in predictive maintenance scenarios. The embedded functionalities for ordering and payment allow banks to also provide services for the management of the machines (e.g., calculation of the replacement point, depreciation). Similar services are also conceivable in the consumer sector with the spread of !wearables and could, for example, lead to the !collaboration between banks and healthcare providers (!e-health). Other strategic business areas are also possible, such as in the area of secure storage of personal data (!IDM) for banks. Banking Platform !Open banking, !platform banking. Basic Bank Account Number (BBAN) Data coding that defines the framework for an international account number. It is country-specific with up to 30 digits and it is used both at European level in the !IBAN as well as globally in the !SWIFT system. Typical components are an identifier for the bank with branches and an account number at these institutions. Batch Processing Denotes a mode of executing input (e.g., function calls for processing payment order) in and between !application systems. The collection of several orders in batches may be traced back to punch card-based systems, which queued calculation orders and processed the entire batch at a certain point in time (e.g., at the end of a business day or a business month). This implied that the data in the respective !application system was only updated with a time delay and that the execution of orders required longer periods of time (e.g., payments are executed on the following day, t + 1, or even later as in the case of cross-border payments). Although digital media have replaced punched cards, batch processing still occurs, particularly in the case of interfaces between !application systems. In the area of !electronic payments, a change from batch processing to !real-time processing only occurred with the rise of real-time credit transfer systems (!RTP, !RTGS). Batch processing features are also present in !cryptocurrencies such as !Bitcoin, where !miners bundle transactions and only write the transactions after generating a new block (!Bitcoin transaction). BATX Abbreviation for Baidu, Alibaba, Tencent and Xiaomi, that designates the largest digital economy companies in China. Their !digital platforms include Alibaba with !Alipay, Baidu with Baidu Wallet and Tencent with !WeChat Pay and TenPay, which all comprise advanced financial service offerings. For example, !WeChat features a strong integration of the payment functionalities with the !e-commerce services offered on the !platform and !Alipay offers credits, insurances as well as wealth management services (!wealthtech) besides its (mobile) payment function.

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Beacon These small computing devices may be attributed to the field of !IoT technologies and use Bluetooth low-energy technology (!BLE) for wireless communication. They open numerous use cases for location-based services (!LBS). For example, they may be placed in a bank branch office and send offers to the customers’ end device when they enter the location. PayPal also uses the technology for contactless automated payments in shops. Best-of-Breed Describes the use of several independent applications in !application architectures (!architecture 4.0), which often originate from different providers. In contrast to an integrated !core banking system from one manufacturer, the best-of-breed approach aims at linking individual products, which are often more specialized and feature a more comprehensive functionality compared to the broader !core banking products. For example, a bank may use a !front-end application from a different provider than the !back-end application(s). The latter may differ depending on their functional scope (e.g., payment transactions, investment and lending business). Initiatives like !BIAN and !open banking may be conceived as enablers of best-of-breed architectures since they foster standardized modules and interfaces. Big Data The term refers to !application systems that feature a large amount of structured, semi-structured and unstructured data. With the ubiquitous presence of computing devices, data has become available at an almost exponential pace. The logic of big data is to collect as many data as possible and to have it available for potential use at a later stage. Although data may initially lack a specific use case, big data systems and strategies aim to unlock the availability with potential future use cases. For example, data may serve to evaluate customer behavior and satisfaction or to detect developments in the market. The main challenge of big data is to extract and prepare the data necessary for the respective purpose from the large number (“volume”) of heterogeneous data (“variety”), which accumulate in rapid succession (“velocity”). For this reason, big data systems consist of high-performance data storage (so-called data-lakes), procedures for evaluation (!business analytics) as well as organizational regulations (e.g., dedicated big data teams, guidelines to manage big data). In the financial sector, big data has proved valuable in numerous fields of application, such as the detection of fraud, the evaluation of customer opinions or risk assessment in lending. In addition, big data strategies have to safeguard data privacy, which requires that the use of data is limited to a specific purpose and that users have agreed that their data may be used for analytical purposes (!opt-in). Big Tech Refers to the providers of !digital platforms that mainly originate from China (!BATX) and the US (!GAFA), which have developed comprehensive and widespread digital infrastructures as the basis for electronic !services in various industries. With the rise of !digitalization, these companies have moved to the most

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valuable companies worldwide (in terms of market capitalization), which mainly results from the cross-industry nature of their platform services. For example, the Amazon platform initially evolved from a virtual bookseller to include other products (e.g., electronics, healthcare, building supplies), whereby parts of this infrastructure have given rise to their Amazon Web Services !cloud computing services branch, which is cross-industry in nature. Likewise, Facebook has been using its social media platform as a !platform for !e-commerce (so-called Facebook Shops) for several years now. The financial industry is another application domain for the use of big tech infrastructures and most big tech companies have meanwhile embarked on offering financial services (e.g., in !mobile banking with Amazon Pay, Apple Pay, Facebook Pay and Google Pay as well as credit cards like the Apple Card). They successively penetrate into other financial services, such as investments, credits and insurances, or seek cooperation with existing providers (!incumbent). An important competitive advantage of big tech platform providers is their large user base (!network externalities), the !ecosystem of complementary devices and !services as well as their experience in offering customer-centric solutions. Bilateral Interchange Fee (BIF) These agreements exist in card payments between an issuing (!issuer) and an acquiring bank (!acquirer). An alternative are multilateral interchange fees (!MIF), which a card !scheme sets for charges from the !acquirer to the !issuer. Binance Coin !Cryptocurrency founded in 2017 that is based on the !Ethereum !blockchain to handle electronic payment transactions on the !crypto exchange Binance. With the abbreviation BNB, these !tokens are also used on other !platforms. Meanwhile the !ERC-20 !token has been replaced with a native !coin on the Binance chain (BEP2). Biometrics Biometric processes that capture and record unique physical characteristics, such as face, eyes or fingerprints, and/or behavioral characteristics, such as signature, speech pattern or typing, of a person for !identity verification from an electronic device. BiPRO Specifications defined by the Institute for Process Optimization (BiPRO) in Germany regarding procedures in the insurance sector. So far, the standards are available in two releases. The first refers to basic data and process models in the field of property, accident and liability insurance (PAL) and the second to pricing, offer and application of PAL, life, motor vehicle and health insurance. The BiPRO standards are used for the structuring of documents for !electronic data exchange and for the definition of processes with corresponding electronic modules or !web services. Bitbond Provider of a global loan brokerage service for self-employed and small businesses based on !blockchain technology. The transactions are settled in !Bitcoin.

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Bitcoin Bitcoin has become the most important application of !blockchain technology and the most valuable !cryptocurrency in terms of capitalization. The system was created in 2008 to enable electronic transactions securely and anonymously directly between trading partners without a central node. The main idea is that each participant within the network is able to view all transactions occurring in the network and holds a synchronized instance of the database on their devices. To add new transactions to this append-only database, !mining nodes with high computing power compete by solving complex mathematical equations. The successful !miners are then allowed to write the transactions in the database and receive !Bitcoins as remuneration in return. Due to the limitation to a maximum of 21 million Bitcoins, the !coins are a scarce commodity (18.77 million were already “skimmed” by July 2021) and have established themselves primarily as an object of speculation. Despite the termin “currency” suggests the availability of a means of payment, the classic functions of money (payment, value retention and value assessment) are only partially fulfilled by Bitcoins (!virtual currency). Although Bitcoins were accepted by 23,009 merchants worldwide as a means of payment (https://coinmap.org, as of August 09, 2021), Bitcoin is of little significance compared to established payment methods such as Visa, Mastercard or PayPal and can therefore only fulfill the payment function to a limited extent. However, since 2020, there has been a significant improvement in the use of Bitcoins as a payment method since major !cryptocurrencies such as Bitcoin and !Ether were included as means of payment in !payment services such as PayPal and Klarna. Due to the high volatility of the Bitcoin—the value increased from 9500 € on February 16, 2020 to almost 60,000 € on November 10, 2021 with intermediate ratings of 52,000 € in April 2021 and 25,000 € in July 2021—Bitcoin also lacks a stable retention of value. Regarding the value assessment function, values are not expressed in Bitcoin but rather on the basis of other (established) currencies, which has led to the concept of !stable coins. Further criticism of the Bitcoin system has been caused by the high energy consumption due to the !PoW !consensus mechanism, which is necessary to create and add transactions to the distributed database, and to the low performance in terms of the possible transaction volume per second (!TPS). Further developments have been addressed via !forks and have, for example, led to suggestions as defined in the Bitcoin improvement proposal (!BIP). According to the Cambridge Bitcoin Electricity Consumption Index (https://cbeci.org), the annual electricity consumption of the Bitcoin network is an estimated 112.83 TWh (as of November 29, 2021), which corresponds to around one fifth of the total electricity consumption in Germany from 2020 (approx. 545 TWh according to the German Federal Statistical Office). Other enhancements referred to the strong wearing of the !mining hardware due to high load as well as to more flexible forms of governance and higher levels in privacy. Bitcoin Cash (BCC/BCH) !Hard fork of the !cryptocurrency !Bitcoin as per August 01, 2017. In March 2020 Bitcoin Cash was the fifth largest !cryptocurrency after !Bitcoin and

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!Ethereum, !Xrp and !Tether, but has given way to younger !cryptocurrencies (e.g., !Polkadot, !USD Coin) by August 2021 where it ranged in twelfth place (see appendix). A main reason for the !fork to Bitcoin Cash was to increase the block size from 1 MB to 8 MB and later to 32 MB. Bitcoin Improvement Proposal (BIP) Describes the procedure for potential improvements of the !Bitcoin system. These may comprise suggestions for changes to the !protocol or the communication rules and the software (!forks) as well as changes to the BIP process itself. Like in other !open source software projects, suggestions from developers reach the communities, which then discuss, develop and decide on them. For example, the introduction of the !Mempool was included in BIP 35 and significant parts of the !Lightning network were included in BIP 112, while the Taproot extension, which aims to speed up the consensus process and improve data protection, represents a more recent BIP. Bitcoin SV (BSV) !Hard fork of the !cryptocurrency !Bitcoin that exists since November 15, 2018. In view of the !Bitcoin Cash !fork, the main goal of Bitcoin SV (“SV” for “Satoshi vision” following the anonymous founder of !Bitcoin, Satoshi Nakamoto) was to return to the original !Bitcoin protocol with the exception that the possible size of the blocks in the database (previously 1 MB) has increased to 128 MB. Bitcoin Transaction Since the first transaction on January 12, 2009, transactions of !Bitcoins have grown substantially. Following the decentralized idea of !Bitcoin, transactions occur directly between users (!P2P) without a central institution (typically a commercial or central bank) being involved. This represent an important difference to existing forms of electronic transactions and payments, which involve banks, networks (e.g., !SWIFT, !EMV) or credit card organizations (!scheme) as intermediaries (!intermediation). The decentralized architecture is enabled by !asymmetric encryption methods which assign each network participant an address that corresponds to a traditional account number or personal identification. In the !Bitcoin system this consists of a !public key, which needs to match a !private key. A transaction is then signed using the !private key and verified using the !public key. An example illustrates the process of a !Bitcoin transaction (see Fig. 12): 1. User 1 uses his !wallet to generate an address to which user 2 should transfer !Bitcoins in the amount of the purchase price. When a new address is created, a !public key and a !private key are created that are mathematically linked to each other (!asymmetric encryption). The private key is only known to user 1 (like a PIN), whereas the !public key is used both as an address and to verify a transaction. 2. User 2 receives the address in the form of a !QR code, scans the code with a mobile phone and agrees to transfer !Bitcoins to the !wallet of user 1. User 2 confirms the entry with her own !private key.

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Public key

Wallet

1

2

3

Private key 6

Nodes @

4

Miner Transaction 0#

Transaction 1#

Transaction 1+2#

2#

3# 3+4#

Transaction 1000# 5

Blockchain

Block n+1 Blocks n-1

Block n

Block Block Block n+1 Blocks n+1 n+1 n+1

Fig. 12 Example of a Bitcoin transaction in six steps (based on Capgemini, 2020)

3. Computer !nodes distribute the transactions via the network and use the !public key to verify that user 2 is entitled to carry out the transaction, i.e., whether sufficient funds are available to complete the transaction and to avoid !double spending. 4. !Miners, as specialized computer nodes, transform the transaction into a !hash function, which they connect along with other transactions into a block. One block contains about 1000 transactions (the limit is 1 MB) and takes about ten minutes to be built. As per August 09, 2021, the !Bitcoin blockchain comprised 694,957 blocks (see https://www.bitinfocharts.com/bitcoin). 5. The !miner, who is successful in the !PoW, adds a new block to the existing !blockchain and is awarded a compensation (!block reward of currently 25 new Bitcoins, which is halved every 210,000 blocks, !halving) as well as a transaction fee from the users. 6. The !nodes store the updated version of the !blockchain, thus completing the transaction. Despite not being full real-time (due to the transaction time of ten minutes), Bitcoin transactions are significantly faster than most established !payment systems. For example, a transaction in the Euro zone currently requires one day and even several days for transactions outside of the Euro zone.

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Bittorrent The Bittorrent protocol describes a data access or file sharing procedure on the basis of internet transmission !protocols (i.e., TCP/IP). Due to its efficiency in handling large amounts of data, it is used for up- and downloading large files. Bittorrent is based on the peer-to-peer principle (!P2P), i.e., the contents are not stored on servers, but rather on decentralized clients. Although there is a transparency of participants based on their internet addresses, these may be influenced by technologies such as virtual private networks (VPN). Besides being used for the distribution of large software files, Bittorrent is also known for numerous cases of illegal distribution of content. With the rise of !tokenization, Bittorrent software clients are expected to include functionality to buy and generate !tokens (e.g., the !cryptocurrency !Tron, which purchased Bittorrent in 2018). Block Directed Acyclic Graph (blockDAG) Manifestation of a !DAG that is based on the graph-based networking of blocks. Block Reward Refers to the remuneration paid to !miners for newly created !coins in !cryptocurrency systems with the proof-of-work !consensus mechanism (!PoW). For example, in the !Bitcoin system successful !miners receive a defined amount of !Bitcoins for successfully calculating a new block, which is halved every 210,000 blocks (!halving). Depending on the current valuation of the !Bitcoin, the remuneration, also referred as !bounty, may increase to several hundred thousand Euros. This provides the economic justification for the considerable investments in the computing infrastructure of the !mining farms. Blockchain Besides directed acyclic graphs (!DAG), blockchain technology has become the most important decentralized distributed database technology (!DLT). It is linked with the rise of the !cryptocurrency !Bitcoin since 2008 and is based on the idea that transactions among users are bundled in blocks, which are distributed among all !nodes in a network. The system uses a !consensus mechanism that ensures the consistency of data stored in all !nodes. A copy of the database is stored at each !node of the network, which the database management system keeps up-to-date or synchronized. The name “blockchain” points at the !data structure, where blocks are linked. As shown in Fig. 13, a block contains several transactions that are encrypted using cryptographic methods (!cryptography) and stored permanently and publicly visible in the database. Starting from the first block (!genesis block), each block refers to its predecessor and the latter to its predecessor. For each block a !hash value is calculated, which is composed of the !hash value of the previous block, a time stamp, the !hash value of the !merkle tree and the !nonce. Depending on the respective blockchain system (e.g., !Ethereum, !Hyperledger, !Tezos), different blockchain designs have emerged regarding openness (!public/ private blockchains), functionality (with !smart contracts, !side chains, !master node), !consensus mechanism (e.g., !PoW, !PoS) and block sizes (e.g., 1 MB in the original !Bitcoin system and 128 MB in the !Bitcoin SV system). In

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Block n-1 (hash) Previous hash Time stamp Nonce Merkle hash

Block n (hash) Previous hash Time stamp Nonce Merkle hash (H0123) H01

H23

Block n+1 (hash) Previous hash Time stamp Nonce Merkle hash

Hash values of the transactions

H0

H1

H2

H3

Transactions

T0

T1

T2

T3

Merkle tree

Fig. 13 Chaining of data blocks in the blockchain (based on Hellwig et al., 2020, p. 17)

the original !Bitcoin setup, the blockchain enables payment processes without additional actors (i.e., a bank or card provider, !intermediation) directly between the interacting parties. Since payers and payees are visible only with their !hash addresses, !blockchain payments are transparent and anonymous (see !cybercrime) in the public blockchain setup at the same time. As soon as a new payment transaction takes place between two persons, the database is updated at all other participants with these new transactions, even if these participants were not directly involved in the transaction. As a result, transactions are transparent at all times throughout the payment network of all involved parties. Meanwhile, a variety of !blockchain frameworks has emerged, which differ, among other things, with respect to the !consensus mechanism, the participants (!permissioned blockchain, !public blockchain), the data organization (!data structure) or the degree of decentralization (!master node). Blockchain-as-a-Service (BaaS) !Blockchain infrastructure provided for a fee according to the principles of !cloud computing and software-as-a-service (!SaaS). BaaS comprises the technical infrastructure for operating a !blockchain solution as well as the software of a !blockchain or !DLT framework (e.g., !Ethereum). It relieves users from implementation or licensing issues and can immediately implement !blockchain solutions “out-of-the-box”. Providers of BaaS solutions are Alibaba, Amazon, IBM, Microsoft, Oracle, SAP or !R3. Blockchain Framework Describes the architecture of a particular !blockchain technology, which consists of various aligned components (e.g., !consensus mechanism, data storage, !authentication, !development environment). Compared to the term !cryptocurrency, the framework term is broader than using a !blockchain or !DLT technology as a !virtual currency, as an infrastructure for !digital

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platforms or for !identity management. Following the model of standard software, advanced frameworks allows the development of customized solutions, especially in the context of !enterprise blockchains. !Cryptocurrencies that are considered blockchain frameworks besides !Bitcoin and !Ethereum are !Cardano, !Corda, !Eos, !Hyperledger, !Iota, !Nem or !Ripple. Blockchain Sharding !Sharding refers to separation of database contents in order to distribute the requirements of space or computing resources on multiple instances. In the environment of !blockchain technologies, !Ethereum, for example, pursues this technique with Ethereum Shards that distribute computing tasks among the !nodes to reduce the load for each !node and to increase the performance of the overall system. Blockchain Split Due to its !open source character, the original !blockchain technology for !Bitcoin’s !distributed ledger has experienced numerous extensions that are based on the requirements of the respective application purposes. This has resulted in so-called !altcoins and !forks, whereby the latter may be divided into !soft forks and !hard forks. Blockchain x.0 The version number of !blockchain frameworks denotes a growing range of functionalities and configuration features as well as use cases. Depending on the authors, the numbering and the respective functionalities may differ. The starting point for Blockchain 1.0 was the original !Bitcoin framework, which included a distributed database (!distributed ledger), a !cryptocurrency and a related !consensus mechanism (e.g., !PoW). With Blockchain 2.0, the enhanced functionality provided by !smart contracts and !DApps has been extended to non-financial applications. Best known examples are !!Ethereum and !Corda. Finally, Blockchain 3.0 is characterized by a variety of different distributed ledger technologies (!DLT) and enhanced abilities of virtualization, integration (e.g., !BaaS, !interoperability) and !tokenization. Examples include !Cardano, !Hyperledger, !Iota or !Tezos. Further developments of !Ethereum (e.g., !EEA, !ERC-20 !tokens) may also be attributed to the Blockchain 3.0 stage. In some cases, further version numbers (e.g., Blockchain 4.0) indicate the expansion into business applications (e.g., higher !TPS, more powerful !DApps) for !core banking applications and !ecosystems such as in the !open banking environment. Blocklet Pre-designed (out-of-the-box) modular program blocks stored in libraries for the efficient development of !DApps. While they accelerate the creation of !blockchainbased !applications, the !interoperability of blocklets is often restricted to a specific !blockchain framework. Due to this focus on specific !DLT platforms, the !interoperability of blocklets is limited.

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Bluetooth Low Energy (BLE) Radio technology for data transmission over short distances (100 business transactions, e.g., international credit transfer) as well as data formats (e.g., data fields in business transactions). These facilitate electronic data interchange (!EDI) between corporate and business customers and banks (!SWIFT) and improve !multi-bank capabilities. Figure 6 shows the use of FinTS for private as well as corporate customers and distinguishes between a connection via portals (!PFM) or a direct connection of !application systems (!EDI). The latter is widespread among corporate customers and primarily includes the !EBICS procedure for retail payment transactions. Financial Wellness Refers to the financial well-being of individuals or, from a business perspective, of employees. By establishing a comprehensive overview of past and planned expenditures, income and reserves, corresponding !application systems help to avoid risks and critical situations. Examples include !apps for expenditure and budget planning, cash flow analysis or portfolio optimization. Often, such solutions summarize financial wellness in a numerical score (!KPI). Financing Round Meetings or discussions from !startup or !fintech companies with different investors in successive stages. These are the !seed round or the !series A to C. The aim of !startup or !fintech companies is to complete equity financing by assigning shares to investors, thus enabling further company growth.

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Fintech Combination of the initial syllables of the terms “finance” and “technology”, spelled fintech or FinTech. There are two basic meanings: an institutional view denotes a specific type of company. These are mostly !startup businesses that renew traditional financial services by using modern technology and try to offer their !services in a more innovative, efficient and/or customer-oriented way than existing service providers (!incumbents such as banks). A second view is function-oriented and characterizes fintech solutions, which increasingly rely on standardization (economies of scale) and less complex products or services in the financial sector, which are often already familiar to the client or may be explained by means of short descriptions (text, picture or video). Generally, fintech solutions are based on comprehensive !digitalization and are not limited to !startup companies. There is also an increasing number of partnerships between !incumbents and fintech companies. From a functional point of view, fintech solutions for the banking and the insurance sectors may be distinguished (see Fig. 7). According to the !banking model, the key banking processes comprise financing, payments (!paytech) and investment (or saving and investing, !wealthtech), while insurance processes include the areas of improvements and protection and, to some extent, investment (for example in life insurance). Mixed solutions of banking and !insurtech services are found under the term !bancassurance. Other sub-sectors are !regtech for regulatory applications and !contech and !proptech for the construction and real estate industry. Due to the innovative character of fintech solutions, a distinction is made between product, process and technology !innovations. According to this distinction, innovative information technology (!IT) provides the basis for designing efficient processes, which in turn can be exploited on the market in the form of new products. In contrast to process and especially product innovations, technological innovations are not directly related to the functional areas. For example, !blockchain or !IoT technologies are applicable for both payment and insurance solutions. In the case of process and product !innovations, fintech companies must observe the regulatory framework conditions, as banking and insurance transactions are subject to a license issued by the regulatory authorities (e.g., !BaFin in Germany, FMA in Austria and !Finma in Switzerland) (!banking license). Fintech services are not subject to these guidelines if they directly concern money-creating or risk-bearing activities (e.g., consulting, settlement), or relate to a previously unregulated area, as was initially the case with !cryptocurrencies. Fintech Incubator An !incubator that accelerates the growth and success of !fintech companies by providing resources and services free of charge or at low cost. Typical supporting services are the provision of physical space and shared services as well as capital, coaching and (relationship) network (e.g., to lawyers, developers, investors). First-Stage Financing Refers to the third to fourth phase of venture capital (!VC) financing. The firststage phase consists of the start of production, the market launch, the development and expansion of personnel, the increase in sales, and the adaptation and further

Cash equivalent (e.g., Moneytis)

Personal finance management (e.g., Mint)

Loan comparison (e.g., Smava)

Risk assessment (e.g., Kreditech)

Blockchain / DLT

Payment processing (e.g., Paymill)

Interim financing (e.g., Kreditup)

Social media

Crypto bank (e.g., Bitcoin Crypto Bank)

Payments

Crowdlending (e.g., Auxmoney)

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Savings

Wealthtech

Artificial intelligence

Savings comparison (e.g., Verivox)

Call money (e.g., Zinspilot)

Time deposit (e.g., Savedo)

Interest rate platform (e.g., Weltsparen)

Fig. 7 Areas of fintech (based on Alt and Ehrenberg 2016, p. 13)

Technology innovation

Process innovation

Product innovation

Paytech

Big data

Sentiment data (e.g., Stockpulse)

Portfolio optimization (e.g. PersonalCapital)

Social banking (e.g., Fidor)

Robo advisory (e.g., Vaamo)

Securities

Fintech (Banking and insurance sector) Fintech (Banking sector)

5G

Agency support (e.g., CoPromote)

Information portals (e.g., Check24)

Contract optimizer (e.g., FinanceFox)

Health tracking (e.g., WeSavvy)

Improvements

Protection

Internet of things

Insurance administration (e.g., Simplr)

Digital brokers (e.g., Getsafe)

Community insurance (e.g., Friendsurance)

Default of payment (e.g., Klarna)

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development of the range of !services as well as strenghtening business relationships. The risk for investors may be better assessed from this phase onwards, as initial market experience is available and the market response and thus the potential returns may be better estimated. The importance of outside capital for companies also increases in this phase (leverage effect). Flow of Fees Similar to the clearing and transaction flows another relationship within !electronic payments applies to the settlement of individual charges between the parties involved in these transactions. For charge and credit cards, the flow of fees is similar to that of debit cards but neglects the internal cost allocation of the parties involved. Consequently, the flow of fees for !electronic payments is divided into three categories: (1) national point of sale (!POS) processing of card payments (!MSC), (2) card payments at the !ATM, and (3) clearing and settlement fees (!CSM, !interchange fee). Flow of Information !Transaction flow. Follower In social media like Facebook, Instagram or Twitter followers, fans or friends form the basis of social networking. A person, organization or !robot may follow another profile and receive messages published by that profile or send messages to their followers themselves. Similar to other businesses, financial service providers have recognized the potential of social media to attract a large number of followers on the respective social media !platforms, as this allows them to establish a direct and interactive form of communication, which may be used in particular in customeroriented processes (!Social CRM). Foreign Exchange (FX) Foreign exchange trading and cross-border payment transactions are considered fields that are strongly affected by !digitalization. They are driven by the emergence of electronic !payment systems (!electronic payments), which are based on payments between banks via the !SWIFT network and, due to time and cost advantages, increasingly via the more recent !blockchain systems (e.g., !Ripple). Forging Process of generating blocks in !blockchain systems, following the !proof-ofstake !consensus mechanism. The forging process allocates the transaction fees of the last completed transaction to the person who was allocated to creating the last block using the !proof-of-stake principle. Fork A fork refers to a branch of development after the splitting of a project into two or more subsequent projects. In software development, this refers to a modified !open source code, whereby the forked code has been subject to important or fundamental changes compared to the original code. Common use case for forks are testing purposes or when new !cryptocurrencies with similar but not identical properties

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are to be developed. A fork also means the gradual enhancement of !open source software, since its free accessibility allows developer to make their own copy and modify (or fork) it for their own purposes. In the context of !blockchain or !DLT networks, forks have led to numerous variants of !cryptocurrencies. These forks are often the result of disagreements about further developments, e.g., regarding block sizes, the !tokens used, openness (!permissioned blockchain) or the !consensus mechanism used. After a proposed change, either a !soft fork or a !hard fork may occur, which differ primarily in their compatibility with the previous version. An overview of important forks in !Bitcoin and !Ethereum is shown in Fig. 8. Four-Corner Model The architecture of existing !payment systems typically comprises four players, with the two transaction partners initially acting as debtor/buyer and creditor/seller. For payment processing, both connect to a bank that authorizes and then executes the payment. The other party (!TPPSP) is a network provider such as the credit card companies. Figure 9 shows the four-corner model using the example of a card payment, with the !acquirer acting as the creditor bank, the !issuer as the debtor bank, and the !card schemes as the network providers. !Fintech companies, in particular, are positioning themselves along the four-corner model in various forms, for example as payment service providers (!PSP) that take over traditional banking services. More recent approaches, especially in the field of decentralized networks (!DLT), attempt to replace this third party as well as the banks and thus tend to increase the efficiency of the !payment system. One example is !Ripple. Fractional Trading This trading strategy is increasingly being offered by online brokerage services and allows smaller investors to invest in highly valued stocks (e.g., from the !big tech companies). While the smallest order quantity at exchanges has traditionally been one share, fractional trading allows to invest in only fraction of this share and fosters diversification strategies via the combination of fractions of various shares. Framework An artefact that organizes elements of specific object of investigation. It is frequently used term for !cryptocurrencies that comprise several elements. These are the !operating system of the !blockchain or !DLT system, the database with a defined !data structure, the !tokens as exchange objects between the participants and a !development environment. Examples of well-known !blockchain frameworks are !Corda, !Ethereum or !Hyperledger. Front-End Describes the !applications that provide functionalities for user interaction. The terms user interface or graphical user interface (GUI) are typically used as synonyms. Front-ends, such as !wallets, supplement !back-end functionalities, which comprise a !blockchain or !DLT, for example. Front-ends are an important component of !blockchain frameworks.

2009

Hard fork

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2012

Announced

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Failed

2010

Ethereum

2014

Soft fork

2013

Metropolis

2018

Beacon chain

2019

SegWit2X (B2X)

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The DAO

2016 Ice Age

2015

Fig. 8 Selected forks in Bitcoin and Ethereum 2008–2022 (based on Viens, 2019a, b)

Legend:

2008

Bitcoin

Bitcon Knots (Bitcoin Core application)

Libbitcoin (Bitcoin Core application)

Bitcoin ABC

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Design

Information flow

Card scheme (e.g., EMV)

Feedback authorization request

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5

Design

Acquirer (vendor bank)

Financial flow

Fig. 9 Actors and activities in the four-corner model (based on Huch, 2013, p. 39)

Front-Office Refers to all customer-oriented processes (e.g., distribution and transaction entry processes, !bank model), organizational units (e.g., counter) and systems (e.g., !online banking) of a bank. Full Node A full node is a program in distributed ledger technologies (!DLT) that validates transactions and blocks. Full nodes accept and validate transactions and blocks from other full nodes and forward them. As key components of decentralized systems they include not only include the program logic for validating and synchronizing data, but they also store a copy of the distributed database. Similarly used terms are those of !master and !supernodes. Fundraising Describes the action of raising money for a specific purpose (fund acquisition). Fundraising is often associated with organizations that aim to acquire the resources (money, goods and services) needed to fulfil their statutory purposes by consistently focusing on the needs of the providers of resources (private individuals, companies, foundations and public institutions). GAFA Abbreviation for the “Big Four” of the digital economy (!big tech), the largest and most dominant companies in the information technology (!IT) industry of the US namely Google, Amazon, Facebook and Apple. All four are now also providing financial services (e.g., Google Pay, Amazon Pay, Facebook Pay and !Diem, Apple Pay) and link their !payment services with other services, especially in the !e-commerce sector. While the GAFA term is limited to US companies, the acronym !BATX also includes Chinese companies Gamification Concept that denotes the use of playful elements in non-play situations. Elements of game design include leaderboards, which represent a ranking of participants, the

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achievement of primarily non-monetary points, rewards, badges or certain levels, which in turn are linked to certain achievements, or the placement of content objectives (e.g., strategy development, training) in game situations. Gamification is present in numerous !fintech solutions, e.g., in !PFM, to create awareness of spending or saving behavior, or in !Social CRM, when customers receive points or other incentives for advising other customers. Gatekeeper Term used in the European Commission’s digital markets act (!DMA) for !digital platforms that dominate with their !services (e.g., search engine, operating system, social media/messaging, intermediary) in at least three EU countries through a high number of users (>45 million active end users/month and >10,000 active business users/year in the EU). The !DMA quantifies these companies with annual revenues in the EU region of at least 6.5 billion € in the past 3 years or a market capitalization of at least 65 billion € in the past year. If !digital platforms qualify as gatekeepers, they must not exploit their dominant position opportunistically, but must comply with certain rules regarding openness and transparency. Gateway In an (electro)technical context, a gateway denotes an interface between two components (e.g., between an !application system and mobile devices such as !RFID tags). Following this meaning, the term has also established itself in the German payment transaction community. As a so-called !headend, a gateway acts as a technical interface between the three banking pillars in Germany (private banks, mutual banks, savings banks) as well as an interface between a merchant and the bank or the credit card provider (!issuer) for processing financial transactions. Actors offering gateway services are often also referred to as payment (service) provider or payment processor (!PSP). General Data Protection Regulation (GDPR) Regulation of the European Commission, which is mandatory for all EU member states and regulates the processing of personal data by private and public data carriers. The goal is to ensure, on the one hand, the protection of sensitive data within the EU member states and, on the other hand, the free movement of data within the European single market. The GDPR is transferred in national legislation, for example the DSGVO (“Datenschutzgrundverordnung”) in Germany and also applies to !fintech companies operating in Germany. Their digital !business models require them to comply with data protection laws when processing personal or personally identifiable data (in particular gender, title, password, bank/account/ payment data, date of birth, age, other IP address, phone number, residential/ delivery/billing address, first name and surname). Generation In terms of the age of users of digital services and devices, there are several categories of users known as Generation X, Y or Z. This assumes that young users are more familiar with digital technologies as they have already grown up in an increasingly digitized world. While the birth of Generation X (born 1965–1980) took

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place in an early phase of !digitalization, which was thus limited to certain sectors of companies and society, the two successive generations of !Generation Y (born 1981–1996) and !Generation Z (born 1997–2012) are considered the prototypes of !digital natives. Those born younger (from the early 2010s onwards) are also called Alpha Generation. The !now-generation, which includes those born between 1985 and 2000, refers to the overlap of Generation X and !Generation Y. Typically, each generation is associated with its distinct style of digital media use (e.g., while !Generation Z makes greater use of the social media service Tiktok, !Generation Y prefers Instagram and !Generation X is most adept with Facebook and Twitter). Generation X Members of this population group were born between 1965 and 1980. As a generation between the previous “baby boomers” and the subsequent !Generation Y, they grew up in an affluent society characterized by television and video and computer games. They have thus already experienced the early phase of !digitalization in companies and society. In contrast to the !digital natives of !Generation Y and !Generation Z, however, the use of digital media was restricted to a certain group of people (e.g., representatives of the IT department and IT specialists or “nerds”) as well as sub-sectors of companies and of society. The representatives, also known as “twentysomethings” or “slackers”, are also considered to be rather pessimistic and weak in decision-making, besides being not very determined and interested in professional or material fulfilment. For financial service providers, addressing this customer group is challenging, since the individuals are little interested in financial matters on the one hand, but are increasingly gaining in prosperity through inheritance on the other. !Fintech companies are trying to lure them to financial matters by digital offerings, !gamification strategies and the like. Generation Y Describes the population group of the so-called Millennials that were born between 1981 and 1996. They grew up with the presence of digital technologies and rapid change, and are therefore considered flexible, less brand loyal and often immune to traditional marketing and sales methods. On the other hand, recommendations, relationships and opinions from social networks (!social banking, !P2P) and sustainable behavior (!ESG, !sharing economy) are often more important. Generation Z Refers to a group of !digital natives born between 1997 and 2012, who grew up not only with computers but also with the internet and mobile technologies. Members of this population group are not only active users of digital services (e.g., social media, !e-commerce), but are also increasingly involved in the establishment of !startup companies in the !fintech sector. Genesis Block A genesis block is the first block of a !blockchain, often marked “0”. It has no upstream block to which it can refer and therefore cannot be calculated by the network. Rather, the genesis block is assigned in the context of an official release and is firmly anchored in the source code. Each !cryptocurrency based on

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!blockchain technology has its own genesis block from which the !master chain and possible !side chains are formed. Gentleman Agreement In general, the gentleman agreement stands for an agreement between two or more parties that relies on good manners and is therefore not specified in writing. !Fintech companies often neglect formal declarations and rely on the word of their partner(s). Geo-IP This method determines the geographic location of a computer by identifying the IP address of that computer. Although Geo-IP can assign the location of a terminal to a city, the method is less accurate than other methods of geolocation. The use of GeoIP is well known to tailor content to specific locations, to target advertising, or to impose location-based access restrictions. Besides GPS coordinates, Geo-IP is one element for location-based services (!LBS). Geolocation Method for identifying the geographical location of a person or institution by means of digital technologies (e.g., GPS or !Geo-IP devices in smartphones and/or !wearables), which enable the offering of location-specific services (e.g., !LBS, !PAYD). Gesture Control Interpretation of human gestures through mathematical !algorithms to control computing devices. This may occur either via cameras or sensors, which are installed in mobile devices or via !wearables that record and process the movements of the user. Financial service providers have experimented with these technologies to support user interaction, e.g., to control displays or input devices in branch offices and to enable payments for pay-as-you-use services (!PAYU). The aim is to positively contribute to !customer experience. Global Gateway A global interconnection of different networks to enable the communication of a participant of one network with participants of another network. Gateways are also used as an online electronic identity verification (!eID) service for the international market to support companies in complying with anti-money laundering (!AML) and customer information (!KYC) regulations. Goal-Based Investment Investment concept, which uses !algorithms to determine the appropriate investment instruments to achieve specific goals within a given period. Relevant factors are the customer’s initial capital and risk preference, possible deposits and withdrawals, and the desired time frame. The approach is present in !robo advisory and !wealthtech solutions.

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Gossip A method used in decentralized networks (!P2P) to ensure the synchronization of the network !nodes and thus the consistency of the distributed data sets. It is found, for example, in !cryptocurrencies in various forms with the !consensus mechanisms determining how data fields are appended to the database (e.g. blocks in !blockchain systems, transactions in !hashgraph systems). If, for example, more than half of the !nodes acknowledge a new data record, the system adopts it into the distributed data pool. Due to the time requirements and the computing and energy intensity associated with communication, the gossip process has faced limitations in the business environment, in particular when high transaction volumes are present as in the area of payment transactions. In these environments alternative !consensus mechanisms are advocated that involve less communication (e.g., !Ripple). GovCoin !Cryptocurrency provided by a federal (government) institution. An important domain of government-backed currencies is traditional central bank money, which recently has seen attempts to be provided digitally as central bank digital currency (!CBDC). Governance Determines how control occurs in systems of multiple actors, which may be socioeconomic, political as well as technological systems. Following systems theory where (super)systems may comprise (sub)systems, governance is apparent on various levels, e.g., on an organizational and a supra-organizational (i.e., !business network, industry or even global level). In the organizational context, standards for “good” governance have emerged (e.g., ISO 37000) with more recent initiatives also focusing on the governance principle for digital technologies (e.g., !AI by OECD or the European Commission). In the context of !digitalization, this includes the governance of electronic networks and !platforms as well as the entire field of !cryptocurrencies (see also the activities of !ISO/TC 307). In the latter case, the design of governance determines the rules in the system (e.g., for !mining, the !consensus mechanism or the tasks of the !nodes) and who decides on the further development of the network. While in !public blockchains that create consensus with proof-of-work (!PoW) principles this is achieved by means of almost basic democratic principles (!DAO), !proof-of-stake systems are based on quasidemocratic principles (!validators) and closed !enterprise blockchains are based on more centralistic or hierarchical principles. Graphical User Interface !Front-end. Hackathon The portmanteau consisting of “hack” and “marathon” describes an event format that takes place in a physical and/or virtual environment during a defined period of time, e.g., 1–3 days. The objective is often to create a competitive and creative atmosphere for the development of business solutions that are often based on information technology (!IT). It combines creativity and the understanding of market

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requirements with the knowledge of operational processes and software development. Thus, hackathons favor mixed teams with complementary skill profiles and apply existing methodologies like !design thinking, !Devops and !Scrum. At the end of the hackathon, the teams present their solutions in a competitive setting (so-called pitches), receive feedback from a jury and often the best solutions are awarded. Hackathons typically comprise different stages (e.g., preparation, execution and follow-up stage) and may occur in various forms (e.g., !Digithon). Halving Method in the !Bitcoin system, which reduces the remuneration by half for the !miners after 210,000 blocks were produced or mined by the !miners. For example, from the third halving that took place in May 2020 onwards, miners receive only 6.25 !Bitcoins instead of 12.5 !Bitcoins starting from block 630,001. Halvings take place under the assumption that the reduced money creation will curb the inflationary tendencies of the !Bitcoin and thus have positive effects on its price development. The first two halvings have shown this: in the 12 months after the halving in 2012 the price rose by 8.000% and in the 12 months after that in 2016 by 290%. The next halving is expected for 2024. Hard Fork In the case of a hard bifurcation, the !protocol or code of the !blockchain undergoes a change that invalidates the old !protocol or code. Therefore, this type of !fork is not downward compatible and existing !nodes must update their software to be able to consider new blocks. The incompatibility of the versions leads to a split and often the old version exists alongside the new one (e.g., with !Bitcoin and !Bitcoin SV). Hash Tree A data structure in !cryptography named after the scientist Ralph Merkle. A hash tree or !merkle tree is a structure of !hash values of data blocks that resembles the branching of a tree consisting of edges and nodes. Hash trees are thus an extension of hash lists and are intended in particular to ensure the completeness and integrity of data. Hash Value This method, known in IT security as the scatter value function, is based on the mathematical conversion of a numerical input of any length into a compressed numerical output of fixed length. The resulting hash values are usually significantly smaller than the original values and have a uniform length. This makes them easier and faster to process than the original values. The important feature is that hash values are one-way functions based on cryptographic procedures (!cryptography), which makes them almost impossible to resolve and, thus, to modify. They are therefore used as digital fingerprints for signing messages or for ensuring data integrity since each change of the input data would lead to a different hash value. For example, the identification of participants and the storage of transactions in !blockchain systems is done via hash functions.

106 Fig. 10 Structure of hash graph (based on Hays, 2018)

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Hashed Timelock Contract (HTLC) Procedure that allows !interchain transactions or !atomic swaps. It is based on so-called hashlocks, which block the !coins on the respective systems until the other side has unblocked them. Examples exist for transactions between !Bitcoin and !Litecoin. Hashgraph Like !DAG and !holochain, it is a !data structure that has emerged as an alternative to !blockchain in order to avoid its disadvantages regarding the energy-intensive !consensus mechanism (especially !PoW) and its limited !scalability (e.g., by replacing !PoW with !proof-of-stake). While in !blockchain systems no blocks can be created in parallel and the number of blocks generated per time unit is limited, hashgraph uses the !gossip protocol (“chatter protocol“) to process information continuously and asynchronously by means of an election mechanism (rather than a !consensus mechanism like !PoW or !PoS). A node then passes the signed information (events) to two randomly selected neighboring !nodes (see Fig. 10), which in turn combine it with information from other nodes to form a new event and pass it on to other randomly selected neighboring nodes. This process continues until all nodes are aware of the information created or received at the beginning. Ideally, all nodes have the same view of all transactions. In addition, each !node may determine whether a transaction is valid through virtual reconciliation, by having more than two-thirds of the nodes in the network as “witnesses”. One of the advantages of this method vis à vis the !blockchain is the higher speed of >250,000 !TPS compared to seven TPS (and one block per 10 min) with the !Bitcoin blockchain. However, Swirlds’ Hashgraph (not !open source) has only achieved a low penetration rate compared to !blockchain-based currencies such as !Bitcoin or !Ethereum so far. Hash Rate Denotes the unit of measurement for the performance of !cryptocurrencies, which use !PoW as a !consensus mechanism. For !Bitcoin, the hash rate refers to the power consumption for generating blocks in 10-minute intervals. In March 2020, it

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was between approx. 95 and 120 tera hashes per second. It is critical for the stable and trustworthy functioning of the !PoW mechanism that no !node has a majority (>51%) of the hash rate and can therefore influence the block formation in its favor (!double spending). Headend Denotes a centralized !gateway in !electronic payment transactions that identifies the various processes along the value chain in payment transactions, in particular for card payments. These headend systems exist both on the !issuer and on the !acquirer/merchant side. In the card business, the !acquirer’s headend sends the !authorization request from the merchant to the !issuer’s headend, which performs a final confirmation/debit of the account and sends a response to the !acquirer’s headend for the final approval or rejection of the card transaction. For example, four headend transfer points (one per banking association) have been established for processing transactions across institutions/associations within the framework of the agreement on the “national ATM-Association” (NOV) of the German banking industry. Healthtech Refers to !startup companies in the healthcare sector that offer innovative digital solutions in the field of !electronic health. HedgeTrade HedgeTrade is an !Ethereum-based !cryptocurrency that aims at !social trading. Participants use their market knowledge and assessment to create a price forecast in which other participants may invest. If the forecast comes true, the creator receives the !coins, if it does not, the creator has to refund them. High Frequency Trading (HFT) With the !digitalization of processes on !electronic exchanges, high frequency trading occurs when systems execute high trading volumes automatically with short holding periods (!algorithmic trading). The !algorithms execute the orders partly in the microsecond range and can thus achieve arbitrage gains due to the high amounts involved. Hold on for Dear Life (HODL) Saying that has spread in the !Bitcoin community to resist the strong bull movements of the !cryptocurrency and keep their investments in the currency. Holochain Another alternative to !blockchain based !DLT systems besides !DAG and !hashgraph. Similar to !hashgraph, it uses a !gossip method instead of a !consensus mechanism and is based on the concept of distributed hash tables. These are independent local datasets (!ledgers) that can search each other according to a defined search procedure. For example, the distributed datasets are queried until the desired content is retrieved. It is particularly suitable for implementing distributed !applications (!DApps) but is not widely used yet.

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Home Banking Computer Interface (HBCI) Agreements on the home banking interface that have been in place since the mid-1990s as a result of an industry-wide standardization initiative in Germany. With the participation of players from the three sectors of the German banking industry (cooperative/mutual banks, public sector institutions and private banks) and the German central credit association “Die Deutsche Kreditwirtschaft”, the various versions of HBCI have created an open standard (!open source) that defines security procedures (e.g., PIN/TAN) and numerous functionalities (so-called business transactions such as individual and collective transfers or the display of account balances). Due to its broad support in the German banking industry, HBCI is an important basis for !multi-bank relationships and was renamed !FinTS in 2002. Host Card Emulation (HCE) An emulator is an information system that replicates another system in certain aspects. In the case of HCE, a software takes on the function of a physical hardware, which can be found particularly in the card area (ID cards, health insurance cards, bank cards, and so on). Thus, HCE emulates the security chip in !mobile payments and eliminates the need for a separate SIM card from the mobile network operator for payment processing. It forms the basis of many well-known smartphone-based !NFC payment methods (e.g., Apple Pay, Google Pay), in which the payment network providers (!EMV) transmit a security !token to the mobile payment provider and use this token to carry out secure !NFC communication with the payment terminal. Thus, the payment network provider acts as a token service provider (!TPS) while the !payment service provider (!PSP) acts as a token requestor. Hot Storage Refers to the storage of !cryptocurrency online, i.e., in internet-based !wallets or !wallets that are connected to the internet. In contrast to !cold storage, they are regarded to present a higher ease of use, but also involve greater security risks. Howey Test A check that is used to determine whether a !token is a !utility token or a security token. The test dates back to an examination by the US Supreme Court in 1946 when it was necessary to decide in a lawsuit whether a transaction was an investment contract or not. If it is an investment in a company with the prospect of making a profit, the Howey test is positive and a !token is !classified as a security token. Huobi Token !Cryptocurrency based on !Ethereum, issued by the operator of the crypto platform (!crypto exchange) Huobi. It is primarily used to settle the fees on the own trading platform. Hyperledger !Blockchain or !DLT framework published in 2015 by the Linux Foundation, which has been developed by a consortium of well-known companies from the finance, logistics and !IT sectors (including ABN Amro, Accenture, Cisco, Deutsche

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Börse, IBM, Intel, J.P. Morgan, !R3, State Street, Wells Fargo). Like numerous !blockchain frameworks, Hyperledger is designed as !open source, but is intended to have a higher performance than !cryptocurrencies such as !Bitcoin and to offer comprehensive functionality (e.g., regarding the !consensus mechanisms used, access control or !smart contracts). The Hyperledger framework lacks an own !cryptocurrency and aims especially at the realization of !enterprise blockchains. Hyperledger Fabric has experienced the greatest adoption in the domain of !permissioned blockchains. Hyperscaling Term for providers of !cloud computing services that are able to realize high economies of scale and thus cost advantages due to their size. Examples include Amazon (Amazon Web Services), Google (Cloud Platform), Microsoft (Azure) as well as IBM (SoftLayer), Oracle (Cloud) and Salesforce. Compared to companies in other industries, financial service providers (major banks as well as !startup companies from the !fintech sector) tend to make more frequent use of hyperscaling services.

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Identity Management Approach for the administration of identities and permissions in companies, which is usually based on a separate !application system or module that is linked to other !application systems of the company. The aim of the master data, which are usually managed on a central identity data management (IDM) server, is to achieve a high degree of consistency and integrity of the data to enable !front-, !middle- and !back-office areas to access data for !authentication and !authorization purposes. Identity management is usually a prerequisite for channel strategies (!multichannel, !omni-channel) and !SSO. With the move towards !multi-bank relationships (e.g., due to !PSD2) and the use of !digital identities in other areas of life (e.g., health, public administration), services for identity management have become established. Among the solutions that are also known as !KYC, are centralized solutions (e.g., PostIdent, Verimi, Veriff or WebID) as well as decentralized solutions based on !blockchain technology such as Hyperledger Indy, Sovrin or Vetri (!SSI). Identity Verification Corresponds to and !authentication procedure where a user provides his credentials, which are then checked by a provider (!KYC). It is the prerequisite for !authorization or !legitimation for the service offerings of financial service providers. Immediate Payment Service (IMPS) Term for a electronic payment network in India that supports real-time payment processing (!RTP). InCar Refers to applications in which the vehicle is the main channel of distribution and communication. Passengers may use in-car electronic (financial) services via corresponding devices (e.g., displays, !AR, !wearables).

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2022 R. Alt, S. Huch, Fintech Dictionary, Contributions to Finance and Accounting, https://doi.org/10.1007/978-3-658-36056-6_3

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Incremental Describes the progression in small steps to achieve something. After each step, selfreflection and reassessment of the performance is carried out. When combined with an iterative procedure these steps are repeated within the framework of continuous repetition until the solution or the desired improved state is satisfactorily achieved. Incremental procedures are found in numerous methods that are common in !startup companies (e.g., !design thinking, !DevOps, !Scrum). Incubator Originating from the medical field, where incubators serve to raise for premature creatures, e.g., in the breeding of chicks, to ensure the optimal environment for rearing or development at an early stage of life. In the !startup sector, it refers to the state in which a company can develop under the best possible conditions in a noncompetitive-market environment. The incubator promotes this state with the aim of generating growth in order to increase the market value of the !startup company. Incubators are often institutions, bodies or private investors who accompany and support a !startup company on its way to independence in various ways, e.g., with venture capital (!VC) or know-how. For !startup companies in the !fintech sector, the term !fintech incubator is also used. Incumbent Term for companies that are established in an industry and receive a challenge from new players (!startup) in the course of technological !disruptions, such as the !digital transformation. Incumbents in the financial sector are typically the banks challenged by !fintech companies or the insurance companies challenged by !insurtech companies. If incumbents are not successful in mastering the change, they might run into the !Kodak trap. Industry 4.0 (I4.0) A concept that refers to the extensive !digitalization of processes in production companies by integrating all resources (e.g., machines, conveyor systems, workpieces, materials, warehouses) and processes within and between companies by means of !IT. The term cyber-physical systems (!CPS) is also used to describe the networking of intelligent machines (!M2M), storage systems and operating resources. Together with !IoT technologies and decentralized control logic, these systems are increasingly replacing a centralized control of processes with more flexible decentralized procedures (e.g., Kanban, negotiated solutions) in real-time (!real-time processing). I4.0 concepts are present not only in the area of physical manufacturing processes, but also for information-based services and processes such as those found in the financial sector (e.g., !back-office processes). Influencer Due to the large number of !followers in their social network, influencers have a high reach with their own social media contributions and are therefore considered to influence opinion formation. Influencers have become an important part of online marketing, especially for purely digital companies such as !fintech companies. An overview of influencers in the !fintech sector may be found at Influencer.World.

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Information Technology (IT) (1) From a functional point of view, the term refers to information processing technologies. Although these can also be realized non-electronically, with the advent of the computer age from the middle of the twentieth century onwards, IT has become synonymous with electronic data or information processing as well as information and communication systems (ICT). IT systems consist of a hardware and a software system, which can be divided into computer hardware with peripherals and system and application software (!application). !Cloud computing has led to virtualization, which makes IT resources more flexible. (2) From an institutional perspective, IT often refers to the organizational unit of a company responsible for the deployment and operation of IT systems. Due to the relevance of software development and the operation of IT systems in !fintech companies, the responsibility for IT should be located at top management level (and not in sub-departments). (3) From an economic perspective, IT refers to all areas or sectors of an economy that comprise hardware and software providers, telecommunications companies and service providers, and increasingly also media providers and service providers. Infrastructure-as-a-Service (IaaS) !Cloud computing. Initial Coin Offering (ICO) Also known as a !crowdsale or token generating event (!TGE), an ICO is based on a company’s going public (!IPO). In the ICO case, the investor first receives a virtual equivalent in the form of a !token for real money, which is a !virtual currency or a !cryptocurrencies. Depending on the type of !token, the countervalue may also be a !service or the right to obtain a product that is still under development. Figure 1 shows the process of an ICO after a credit auction (!crowdlending). Two investors have agreed to make a total of 30,000 € available to a borrower via the !platform (step 1). The !smart contract documents the debt relationship and contains the credit conditions such as interest (in this case 5.5%), term, loan amount and balance. The investors receive 10,000 or 20,000 !tokens in 2

Investor 1

10’000 Token

3

10'000 EUR 1 6

EUR 441

Crowdlending platform

EUR 882 EUR 20'000 1

Investor 2 2

2

20’000 Token

5

EUR 30'000 Borrower 1'323 EUR*

1'185 Payback

Smart contract*

Fig. 1 Process steps of an ICO (see Swisspeers, 2019)

4 * of which EUR 138 interest payment

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their !wallets and the borrower receives the payout of 30,000 € (steps 2 and 3). Steps four to six contain the monthly repayments (paybacks), which result in an update of the balance in the !smart contract and a payout to the investors. Initial Exchange Offering (IEO) Financing strategy in which (!startup) companies obtain their financing entirely via !crypto exchanges. The exchange provider conducts appropriate checks (e.g., due diligence) and takes over the entire !ICO process. Initial Public Offering (IPO) The terms “primary offering” or “going public” refer to the going public of a company. For !startup companies, this is usually the result of several successful rounds of financing and the hope of raising substantial capital. Innovation Based on the translation of the Greek word “Innovatio” for renewal and “something newly created”, innovation describes a new idea and its implementation. The essential characteristics of an innovation are the reference to an innovation object (a !business model, product, process or technology innovation, see Table 1), the degree of novelty (either !disruptive or gradual innovations) and the application or marketability of the invention. In the financial sector, the !fintech term is inherently linked to innovations, which in the age of !digitalization are often technologyinduced innovations (e.g., through the application of !big data, !blockchain, !IoT or !AI technologies). Innovations may also stem from market- or demanddriven impulses such as an improved !customer experience. Regarding the area of application in banking, the !term fintech is used in addition to the term !banking innovations to also comprise innovations from the insurance sector (!insurtech). Insourcing Denotes a !sourcing strategy that aims at the (re)integration of tasks into the own organization. For example, a bank might decide to take over back-office functions from competitors to foster their !business model as a !transaction bank. Similarly, a !fintech company might insource their accounting function, Table 1 Areas of innovation in the banking sector (see Alt & Sachse, 2020, p. 225f) Innovation area Strategic innovations Business model Product/service Organizational innovations Process Organization Technological innovations !Application system Infrastructure

Examples from banking innovations !Crowdfunding, !PAYU Advisory among customers (!P2P) !Mortgage comparison, online mortgage !Outsourcing, single point of contact (!SPoC) Personal finance management (!PFM) Hardware for secure information transfer (!token)

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which was previously performed by an external tax advisor. In competitive markets, insourced tasks should closely comply with the organization’s core competencies. Insurance IT Applied scientific discipline which may be regarded as a within the !business information systems discipline and deals with the application of technologies for the automated processing of insurance company data as well as for supporting insurance business processes. Insurtech The combination of “insurance” and “technology” describes a subset of !fintech solutions in the insurance sector. Insurtech companies are !startup companies that provide digital solutions for improvements and protection (!fintech). Examples for insurtech solutions are meanwhile present in all lines of insurance (e.g., life, property and health insurance). Similar to the !fintech companies in the banking sector, partnerships with existing insurance companies (!incumbent), but also with products and service providers (e.g., !e-commerce, !smart service, !mobile service) can be increasingly observed. These collaborative settings (!collaboration) are particularly suitable, since underwriting and carrying risks are subject to regulation, which is not the case with advisory and brokerage services. One model, for example, is the development of an innovative insurance product by an insurtech !startup company coupled with a cooperation with a primary insurer as risk carrier and with a distribution partner (e.g., a bank) for the distribution of the insurance product. Instant Payment !Real-time credit transfer payments (RTP). Integrator !Business model of an intermediary (!intermediation) based on the bundling of !services combines services of different providers. In contrast to the !aggregator model, the focus is less on !intermediation, but rather on linking !services along a value chain (provider view) or a problem-solving process (customer view). The essential value contribution of integrators may be seen in the coordination of !services to form a comprehensive !service for customers (!customer experience). In the banking sector, for example, central institutions such as Germany’s mutual bank DZ-Bank provide integrator services for other banks in their !ecosystem. Integrator models are also present in payment transactions when providers such as Klarna or PayPal support a variety of electronic payment procedures (!electronic payments). Intelligent Personal Assistant (IPA) !Intelligent virtual assistant (IVA). Intelligent Virtual Assistant (IVA) An intelligent virtual assistant or intelligent personal assistant (!IPA) is a software !agent that can perform tasks or !services as a virtual employee for a person based on commands, rules or questions. The term is often used synonymously with !chatbot and virtual assistants (!virtual assistant). Some of them apply artificial

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intelligence (!AI) to interpret human speech (!NLP) and to respond via synthetic voices. Users may interact with their assistants and ask questions or manage business tasks such as emails, to-do lists, and meetings via verbal commands. Other forms of AI-based IVA in the financial sector may be found in the field of !chatbots in advisory (!robo advisory) and customer service processes. Interchain Refers to transactions in !DLT or !blockchain systems that take place between different !cryptocurrencies. In contrast to trading !coins via trading platforms (!crypto exchange), interchain transactions occur directly or between the respective !cryptocurrencies. Similar terms aiming at the !interoperability of different !DLT frameworks are !cross-chain, cross-ledger interoperability (!CLI) and !multi-chain. Interchange Fee (IF) For credit card payments in the !four-corner model, IF are payments made from the !acquirer to the !issuer. These form a part of the merchant service charge (!MSC) that is billed by the !acquirer to the merchant. In the case of !EMV, the IF for debit and charge or credit cards in Germany are often in the range of 0.20% to 0.30% of the transaction value. Intermediation Describes a !business model that links two tiers in a value chain, for example, buyers and sellers. Depending on their functions, there are various forms of intermediaries (e.g., !aggregators, !brokers, !digital marketplace, !integrators) that add value to market participants (e.g., improved market overview, simplified transaction processing, independent trust authority). In return, intermediaries charge fees, thereby increasing costs in value chains. Intermediation underlies many !fintech initiatives and is the countermovement to !disintermediation. International Bank Account Number (IBAN) Standardized syntax for an international account number consisting of the !bank code, a check digit and the country code. The IBAN code was created in 1997 on the basis of numerous national numbering systems through the initiative of !ECBS and is now internationally certified as !ISO 13616. It features a length of up to 34 digits, which varies among countries. In Germany, the IBAN has 22 digits and consists of the eight-digit bank code (!BLZ) and an institution-specific account number, as shown Fig. 2.

Fig. 2 Structure of IBAN

Check digit (2 digits) Country code (2 digits)

Bank code Account number (8 digits) (10 digits)

DE58500700240123456789

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International Organization for Standardization (ISO) Founded in 1947, the standardization organization ISO comprises representatives from currently over 160 countries and, as an independent non-governmental organization, aims to develop standards to simplify trade. Since its inception, ISO has developed standards in many sectors (e.g., telecommunications, agriculture, healthcare) and for many applications, including the financial sector (!ISO 20022). Development is carried out in over 250 technical committees (TC) according to a defined standardization process. For example, since 2017, !ISO/TC 307 has been working on the development of standards for !blockchain and !DLT applications, which were published from 2020 onwards. In addition to ISO, there are other standardization organizations, some of which are in competition with each other. These include technology-oriented organizations in the internet (e.g., World Wide Web Consortium, W3C) or in the blockchain context (e.g., !EEA) as well as industry-related organizations such as !BIAN, !SWIFT or the Blockchain in Transport Alliance (BiTA). International Payment Instruction (IPI) This standard by !ECBS specifies an international payment instruction. The so-called EBS206 document contains both the !BIC and the !IBAN. With the introduction of !SEPA payments, IPI has become less important in the Euro area and is only occasionally used outside this area (e.g., in payment transactions with Switzerland). International Securities Identification Number (ISIN) Internationally valid standard for the semantic denomination of securities, which dates back to the US company ISIN Network and has been available since 1990 as !ISO norm 6166. ISIN consists of 12 digits with the first two letters specifying the issuing country according to ISO 3166-1 alpha-2 (e.g., DE for Germany), the following nine numerical digits specifying the national security number (!NSIN such as the security identification number !WKN in Germany), and a concluding check digit. ISIN is used by numerous national and international clearing systems (!ACH) and is likely to replace national identification systems such as the !WKN in the future. International Token Identification Number (ITIN) Initiative launched by the German association “International Token Standardization Association (ITSA) e.V.” for the standardized identification of !tokens in !cryptocurrencies. Similar to the concept of the security identification number (!ISIN, !WKN), the ITIN identifies the various !tokens and provides an eightdigit alphanumeric identification number and one check digit. Among other things, the uniform designation is intended to prevent different !crypto exchanges from trading the same !cryptocurrency with different symbols (e.g., !Bitcoin Cash as BCC or BCH) and also allows identification across !forks. Internet Bubble !Dot-com bubble.

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Internet of Things (IoT) Refers to the networking of real-world objects by means of !digitalization based on extensive automated machine-to-machine (!M2M) communication. The aim is the comprehensive integration of sensors, processors and actuators in operational and/or social applications. Mundane objects equipped with IoT technology are able to record environmental information and to act on events based on pre-defined rules. It is expected that such rules will increasingly be replaced by more adaptive !AI !algorithms, which may render IoT objects to act more autonomously. IoT is considered an important driver for !digital transformation along the value chain and for integrated concepts such as industry 4.0 (!I4.0). The elements of IoT architectures may be divided into three levels (see Fig. 3): The infrastructure level manages hardware and network technology, the platform level includes services, storage resources and !middleware, and the application level provides the !frontend to the various user groups. Internet of Things Iota (IOTA) The acronym from internet of things (!IoT) and the smallest letter in the Greek alphabet Iota denotes a !cryptocurrency launched in 2015. The !open source quantum-proof !protocol, also known as !Tangle, is based on a direct acyclic graph !data structure (!DAG), which offers improvements regarding !scalability and secure data transfer compared to !blockchain technologies. The suitability for the !IoT environment stems from fee-free transactions, so that frequent transactions (e. g., status data, payments) between devices are also viable from an economic perspective. Interoperability Refers to the ability of organizations and !applications to work together. As an important success factor in networked business models (e.g., !collaborative business, !open banking, !sharing economy, !sourcing, !smart service), the organizational and technological interoperability influences the !transaction costs between organizations. The existence of industry-wide or cross-industry standards is considered an !enabler for achieving interoperability. These include standards for business processes (e.g., !BiPro), application interfaces (!API) or data semantics (!BIC, !IBAN) and syntax (!EDI, !ISO 20022) as well as the use of dedicated !applications for integration (!middleware). Interoperability is also relevant, when data needs to be transferred between different !cryptocurrencies, since neither the !data structures nor the !coins are currently standardized across distributed ledger (!DLT) !frameworks. Appropriate approaches for !interchain transactions and !digital identities are emerging for this purpose (e.g., Chainlink, !Corda or !Cosmos). Intrachain Describes the !interoperability of !coins of a !cryptocurrency or !blockchain framework.

Sensors Thermometer, accelerometer, hygrometer, GPS, acoustics, optics

Actuators

Mechanics, electronics, hydraulics

Server

System on chip, receivers, sensors

Gateway hardware

GPRS, 3G, 4G, 5G, LTE-M

WiFi, Bluetooth, NFC, RFID

Hardware components

Mobile networks

Data analytics

Storage

Short-distance networks

Network technology

Developer tools

Services

Application management

Device management

Cloud

e.g. non-profit

Other

Memory/processor chips, energy

Other hardware

Low power wide area networks (LPWAN)

Smart city, public authorities, industry, SMEs

In office, at home, on the road

Middleware

Company/administration (B2B, B2G, G2G)

Consumers/consumers (B2C, C2C)

Fig. 3 Elements of an IoT architecture (Capgemini, 2020)

Infrastructural level

Platform level

Application level

Security for wireless connections

Data security

Encryption

Access control

Security

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Investtech The combination of “investment” and “technology” refers to !business models that offer digital investment services and often apply !AI to determine the appropriate strategy and actions for financial investments. Examples are established in the field of portfolio management, in particular with !robo advisory systems. ISO 20022 ISO 20022 is an !ISO message standard, also known as !UNIFI. It specifies data and message formats for processing financial transactions, especially in payment transactions. Well-known examples in Europe are !SEPA credit transfer (!SCT) and SEPA direct debit (!SDD). ISO 20022 comprises eight parts, including an overarching (data) meta-model, data models in UML notation and XML schemas for implementing the total of more than 400 already specified messages. An example scenario in the !four-corner model is shown in Fig. 4. The importance of ISO 20022 is expected to increase in the future through its use in the !TARGET and !SWIFT systems. ISO/TC 307 Technical committee of !ISO for the development of a standard for !DLT and !blockchain technologies. In addition to terminology and architecture, the areas of work include !interoperability, security, !smart contracts, !governance and use cases. First documents were released in 2020. Issuer In the payment area, there are two interpretations for issuers. (1) In a narrower sense this is a financial institution that provides cardholders with the payment instrument and maintains a contractual legal relationship with them. The issuer uses an issuing license of the respective !payment system, which yields access to the payment and acceptance network. In addition, the issuer takes accountability for the marketing and sales of the payment card, as well as the acceptance and processing of card transactions at the !ATM. (2) In a broader sense, an issuer denotes an organization (company, authority or investment company) that issues securities (e.g., shares, bonds, !cryptocurrencies) or payment instruments (e.g., debit, credit or prepaid cards) to customers and is subject to supervision. !Fintech companies such as Revolut cooperate with issuers like American Express, Discover or banks (e.g., Wells Fargo, Deutsche Bank UBS). Issuer Identification Number (IIN) Coding to identify the !issuer of a financial instrument with a length of six or eight digits after the revision in 2017. Since the issuing organizations are often banks, the IIN is also referred to as bank identification number (!BIN) but differs from the bank identifier code (!BIC). Iterative An iterative approach aims to reach a defined goal in small steps (!incremental) and foresees continuous repetition cycles (iterative). A well-known methodological !framework in technological and !innovation projects is !Scrum.

Debtor

Debtor bank

Account switching

Cash management

Creditor payment activation request

Change / verify account identification

Exceptions and investigations

Credit transfers / direct debits / mandates

Fig. 4 Message exchange scenario in payment transactions with ISO 20022 (ISO, 2020)

Authorities

Financial investigations

Credit transfer initiation Advice and statement Exceptions and investigations Change / verify account identification Bank account management

Creditor payment activation request Account reporting request Bank services billing Stand-alone remittance advice

Direct debit initiation Advice and statement Exceptions and investigations

Creditor

Creditor bank

Mandates

Creditor payment activation request Notification to receive Bank services billing Stand-alone remittance advice

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JavaScript Object Notation (JSON) Structured, text-oriented and thus human- and machine-readable data format that is used for communication between !application systems. It has seed wide adoption especially in combination with !API and !REST-based interfaces. An example of a message in JSON format is shown in Fig. 6 for an exchange rate query at the British !smartphone bank Revolut in chapter “A–D”. Kanban Originating from the Japanese word for card, note, board or receipt, it dates back to the invention of the Toyota production system in 1947. Kanban implements a decentralized control method with self-controlling loops between a requesting and a supplying point. The cycles are demand-driven based on so-called Kanban cards, which are placed by the requestor on a Kanban board and then trigger the production of new items. The procedure is widespread in logistics processes and has also found its way into agile software development and agile project management (!agility) for the coordination of tasks between teams. Key Information Documents (KID) Structured overview of the product and/or service information of investment funds. These information sheets describe the nature of the financial instrument, how it works and the associated risks, profit prospects and costs. Key Performance Indicator (KPI) Refers to a performance metric or key figure that reflects aspects of the company’s performance, i.e., operational successes or failures. KPIs measure the degree of achievement with regard to operational objectives or !critical success factors within (e.g., revenue, profit) or outside an organization (e.g., growth, market share) and are closely related to controlling. They support decision-makers and investors in evaluating and managing processes, which is the basis for taking appropriate action in the event of deviations from defined targets. Different areas of a company require different KPIs, e.g., key figures such as market share or brand coverage image are relevant for the marketing department, while for accounting it is more likely to be variables such as profitability or cost recovery. For investors in the !startup environment, KPIs such as return on investment (!ROI), net present value (!NPV) or profitability of product development (!RoPDE) are the most important. A well-known structuring approach for KPIs is the balanced scorecard, which distinguishes KPIs in the areas of finance (e.g., sales, profit), customers (e.g., customer satisfaction and profitability), internal processes (e.g., process costs and throughput times) as well as potential (e.g., time-to-market, employee turnover) and suggests that these areas should be equally addressed (i.e. balanced). The example of a balanced scorecard is shown in Fig. 5. Know Your Customer (KYC) “Get to know your customer”or “Know your customer”are not only phrases from marketing, but regulatory requirements that mostly financial institutions must comply with. They need to ensure that new customers or suspicious existing customers are checked for legitimacy in order to prevent money laundering (!AML), terrorist

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Financial perspective

Customer perspective

• • • •

• • • •

Market share (absolute/relative) Turnover EBIT/EBITDA, profit, ROS, ROI, RoPDE Market capitalization (share value)

New customer acquisition Customer experience and value Customer lifetime value (CLV) Repeat purchase rate

Process perspective

Employee/potential perspective

• • •

• • •

Degree of digitalization of processes Share of digitalized products/services Scope of electronic integration of external partners

Employee satisfaction and identification Staff qualification in the field of digitalization Participation of employees in innovation processes

Fig. 5 KPIs in the balanced scorecard (based on Kreutzer et al., 2018, p. 187)

financing (!CFT), etc. KYC is a process within a company for checking the identity of its customers (!authentication), but is also found in the environment of banking regulations, i.e., by purely digitally operating financial companies (e.g., !direct banks, !PDI) during acquisition. The goal is to know customers as if they were personally present. With the opening of bilateral bank-customer relations by means of the !PSD2 regulation, KYC procedures that are applicable across banks (!multi-bank) have gained in importance. Financial companies have therefore developed their own !identity management solutions or used external !services (e.g., nPA, Verimi, Veriff, Yes) and standards (e.g., Blockcerts, OAuth, OpenID, Liberty Alliance). In contrast to the established solutions, which follow a centralized architecture model, decentralized approaches have emerged that are more in line with the principle of consumer sovereignty (!SSI). Knowledge-Based Authentication (KBA) An !authentication procedure that identifies end users via pre-defined security questions in order to obtain !authorization for using digital services. Kodak Trap This notion was coined when the dominant manufacturer of analog cameras failed to master the transformation to digital photography and refers to a key problem of !innovation. When companies like Kodak are successful in an existing technology, this success tends to harm the ability and openness for disruptive change (!disruption). Kodak recognized the rise of digital technology too late and fell behind competitors. Analogies to the Kodak trap may be found in the financial sector, for example with the transition from physical to !virtual currencies or with the (future) substitution of !incumbents by decentralized technologies (!DLT) and decentralized finance (!DeFi) concepts. Late Stage Financing Refers to the sixth phase of !VC financing and includes financing of acquisitions, succession arrangements, consolidations or restructurings, buy-outs, turnarounds as well as !bridge finance.

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Launch Describes the initial phase of a project that may be the start of a business or the introduction of a new product, !service or software. For !startup businesses, founders aim try to specify and validate the !business model during the launch phase. This is typically done !iteratively and fundamentally (!pivot), as the idea and plans often need to be adjusted during the search period due to dynamic technological change on the one hand and the market environment on the other. Lean Startup Describes the “industrialization” or professionalization of the initial phases of starting a new business (!startup). Lean startup divides the !startup process in several phases in order to maximize capital efficiency. Besides favoring a sequential approach (instead of a one-time “big bang”), lean startup advocates an experimental approach (e.g., by means of early !MVPs) instead of an (too) elaborate planning of all steps (e.g., of !business plans that are differentiated in detail) and prefers the close !collaboration with customers over a purely intuitive approach. Ledger In economic and social life many forms of ledgers are present, such as general ledgers, (e.g., cash, stock or subsidiary) books, journals, accounts or registers. From the !IT perspective, a ledger is a collection of data (or transactions) organized according to a specific !data structure. Each economic entity usually has one or more ledgers that ideally work neatlessly together in economic structures where division of labor is present (!digital value creation). Systematic reconciliation and synchronization of distributed databases is at the heart of distributed ledgers (!DLT), which are currently attributed a high potential for efficiency and change (!disruption) in the financial sector. Legacy System Notion for a software system (!application system) that has been in operation for some time and is in discussion with the introduction of new systems. Often, the legacy system has the advantage of being functional and reliable but fails to support novel requirements regarding new functionalities and system infrastructures, security standards and interfaces or modularity and architectural requirements. Among the well-known examples in the financial organizations are !core banking systems that have been developed internally by many (especially larger) banks and have become the backbone of many operations. In view of the !digital transformation, many banks and insurance companies decided to integrate or even replace these systems with newly developed (or purchased) systems. Compared to !incumbents, it is considered an advantage of young !fintech businesses that they lack the “burden” of legacy systems and may start developing their solutions on a “green field”. Legitimation ! Authorization.

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Lending Club This US-based !crowdlending marketplace was founded in 2006 and aims to broker funds from private individuals to private individuals within the a loan transaction. Following the peer-to-peer model (!P2P), the allocation of funds focuses as far as possible on individuals and less on groups as financiers. Lending Pool As an area of decentralized finance (!DeFi), lending pools enable decentralized lending and borrowing among individuals (!P2P). These !crowdlending services are based on !cryptocurrencies like !Maker, Compound or !Aave and aim at automatically providing collateral-based loans in !real-time. Typical collaterals are !digital assets, which trigger !smart contracts for providing the loans and for paying interest on these loans (!liquidity pool). Libra !Diem. Lightning Network Extension of the !Bitcoin blockchain to increase the performance of payment transactions. For example, this includes increasing the block size from one megabyte to 32 megabytes for !Bitcoin Cash. As Bitcoin improvement proposal (!BIP) number 112 it aims at enabling !off-chain payments, in particular the processing of !micropayments. In addition, the lighting network is intended to improve the execution of !cross-chain transactions (!interchain). Liquidity Refers to the ability to execute transactions in (electronic) markets at all times. In liquid markets, suppliers and buyers have the opportunity to find a market partner, which requires that a certain minimum number of offers to buy or sell need to be present in the market (!critical mass). In order to ensure liquidity in certain product or market segments, (electronic) stock exchanges have specialized market makers who place offers (see !AMM for crypto markets). Liquidity Pool This concept within decentralized market and trading systems (!DeFi) aims at creating !liquidity automatically via !smart contracts instead of centralized !order books. The latter support the exchange (“swap”) between two different !tokens (e.g. !ERC-20 tokens in !Uniswap). Several participants may provide !tokens in a pool and receive a fee for their role as liquidity provider for each executed transaction (e.g., 0.3% divided equally among all liquidity providers in !Uniswap). Similarly to market-makers who quote prices in centralized exchanges, users ensure the !liquidity of the market. Since the !smart contract represents the “counterparty”, the terms “automated market maker” (!AMM) and “peer-to-contract” are also used. Litecoin Litecoin is a !cryptocurrency, which offers a decentralized !open source payment network. It works similar to !Bitcoin, but uses reduced mining times (one new

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block every 2.5 min instead of 10 min for !Bitcoin) with a total volume of 84 million !coins (instead of 21 million for !Bitcoin) and a more complex encryption !algorithm. Loan-to-Value (LTV) This indicator (!KPI) is frequently used in practice to measure loan collateral and, puts the loan amount in relation to the amount of the investment (e.g., the market value of a property). It serves to check the creditworthiness of the investment to be financed and to set a lending limit. !Fintech companies (e.g., in the area of !crowdlending) use it to support creditors in their credit assessment. Location-Based Service (LBS) Location-based services use the !geolocation technology of mobile devices to determine geographic data in real-time (!real-time processing) to provide users with personal or location-specific information. Once users have given their consent (!opt-in), LBS may identify the location (e.g., an address) automatically without the need for manual data entry. Advantages for the user include being able to checkin to restaurants, shops, concerts and other locations or events online and to receive corresponding context-specific offers or news. Financial service providers may, for example, offer (micro) credits or insurances (e.g., when buying skiing equipment or ordering an insurance before a steep descent). Machine-to-Machine (M2M) Manufacturing machinery equipped with sensors and/or other computing devices (e.g., !IoT) is able to automatically communicate directly or via a centralized management and control system (e.g., a production planning and execution system). Use cases are integrated concepts like !industry 4.0 in the industrial sector and contactless payments (!M2M payment) or pay-as-you-use (!PAYU) models in the service sector. Machine-to-Machine Payment (M2M Payment) Describes a communication between two machines (!M2M), whereby a payment transaction between two electronic devices takes place without human interaction (e.g., PIN entry). It is now widely used for contactless card payments at the !point of sale using !NFC technologies (e.g., credit card, smartphone). Machine Learning (ML) This field of !AI comprises !algorithms that enhance machines or !application systems with learning abilities or adaptive behavior. For this purpose, ML distinguishes between different learning styles or forms of learning, which pick up (“learn”) a behavior based on training data in a supervised or unsupervised procedure. While supervised learning presupposes the definition of an initial learning model and training data, unsupervised or reinforcement learning learns the behavior through experience or through the feedback received. Among the !algorithms for the respective procedures (see Fig. 6) are regression models, decision trees, clustering procedures or artificial neural networks with !deep learning for supervised

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Machine learning

Supervised learning

Unsupervised learning

Classif ication (e.g. K-Nearest Neighbor)

Cluster analysis (e.g. K-Means algorithm)

Regression (e.g. linear, logistic)

Anomaly detection

Neuronal networks (e.g. deep learning)

Association analysis

Decision trees

Dimension reduction

Reinf orced learning

Strategy f or action

Fig. 6 Forms of learning in machine learning (based on Lanquillon, 2019, p. 103)

learning. Among the use cases in the financial sector are fraud detection, market analyses, language or text recognition in the processing of paper documents. Magic The phrase “with a little magic” describes the enrichment of an activity or product with a differentiating value proposition. This is often the result of a (creative) development process that leads to product, process or business model innovations (!innovation) and is a common way to create !fintech !business models. Maker !Cryptocurrency based on !Ethereum, which is designed as a !stable coin against the US dollar and aims to be used as a currency in various decentralized financial applications (!DApps, !DeFi). Mainchain In !blockchain !data structures this is the longest block sequence that may be traced back to the !genesis block. Additional sequences resulting from the mainchain are !sidechains. The conceptual pairs main-/master-chain and sidechains are sometimes used synonymously with parent/child chain. Marketplace Lending Refers to lending via electronic platforms (!digital marketplace) which often pursue the peer-to-peer (!P2P business) model (!crowdlending, can also happen) and foresee lending without existing intermediaries (!intermediation). Since both natural persons and legal entities can act as lenders, the default risk is borne directly by the capital providers and not by a legal entity such as a bank. Markets in Financial Instruments Directive (MiFID) EU directive on the harmonization of financial markets, which dates back to 2007 and is now in its second version (MiFID 2), valid since 2018. The aim of the regulation is to improve investor protection and the transparency of the financial

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markets. This includes the obligation to declare investment recommendations and to disclose commissions, to ensure best execution by financial service providers and to document transactions on the financial exchanges (!electronic exchange). Mass Customization (MC) Approach to flexibly adapt the range of services to customer requirements, which aims to combine a high degree of !personalization with a high degree of efficiency. MC allows customers to individually configure goods and services, such as clothing, vehicles, travel or financial services. The basis for this is the standardization of service or system components or modules (e.g., equipment variants in vehicles) along general solution models (e.g., a vehicle consists of certain components), which span a solution space of possible configurations. The matching of customer requirements (the problem space) with the components from the solution space is usually done by means of configurators (e.g., !robo-advisory), which are used either by consultants or by the customers themselves (!self-advisory). Master Node Describes a !node in !blockchain networks that has a complete copy of the distributed database (!distributed ledger) stored within itself. Depending on the !cryptocurrency (e.g., !Dash), this participant may qualify for remuneration in the form of !coins. In !cryptocurrencies that have implemented the !proof-of-stake !consensus mechanism, this represents a revenue opportunity for !validators similar to the !miners in the !PoW model. Media Break Describes the need to re-enter data between different media, which may be physical (e.g., paper, DVD, USB sticks) or virtual (e.g., !application systems) in nature. Breaks occur when data has to be transferred from one medium to another. In the physical case, this occurs when data is transferred between paper forms or between paper and an !application system. In the virtual case, data is transferred or manually (re)typed from one !application system to another. The discipline of !business information systems attempts to avoid the inefficiencies associated with media breaks in the form of error potentials, delays as well as costs in time and workforce with the design of digitalized business processes supported by integrated !application systems (e.g., !core banking system, !ERP). In addition to designing digitalized business processes in intraorganizational systems and to using electronic documents for interorganizational integration (!EDI), the use of !robots to automate manual data transmission activities (!RPA) is a nother possibility to address media breaks. Mempool Denotes an extension of the Bitcoin !blockchain (!BIP) that creates a buffer for unconfirmed !Bitcoin transactions at each !full node. This is necessary to manage peak loads and bridges the time between the verification of the transaction by the !node and the processing by the !miner. The size of the mempool varies with the number of cached blocks and amounts to 3 MB for three blocks.

I–M Transaction amount 20 EUR

129 Interchange fee (0.2 %) 0.04 EUR

MSC (1.7 %) 0.34 EUR

Authorization fee Total fee (0,35 EUR) 0.35 EUR 0.73 EUR

Fig. 7 Fees for a card payment using the example of Amazon Pay (Amazon, 2020)

Merchant Service Charge (MSC) Service fee charged by the !acquirer to the merchant for e.g., credit card transactions, which the merchant can include in the sales price. Frequently, the fee is calculated as a percentage of the transaction value plus a transaction-fixed fee (e.g., for !authorization). The MSC reflects the !acquirer’s transaction processing costs and, together with the interchange fee (!IF), gives the total cost of a card transaction charged to the customer. The calculation of an Amazon Pay payment in Fig. 7 shows this principle. Merkle Tree !Hash tree. Message Authentication Code (MAC) This !symmetric encryption mechanism is used in !electronic payments to ensure the integrity of messages and that the sender is authorized to access accounts or to initiate transactions. Contrary to !asymmetric encryption it is based on a !private key that is shared among the parties and lacks a separate !public key. Message Queuing Telemetry Transport (MQTT) !Protocol for machine-to-machine (!M2M) communication that allows the realtime transfer of telemetry data between devices. For example, it is used between payment terminals at the point of sale (!PoS) such as vending machines, !mobile payment terminals or other !IoT devices. Recent solutions are based on !APIs that follow the !REST principles. Messaging Commerce Describes the possibility of customers to interact with companies within a messaging or chat application (e.g., Facebook Messenger, !WeChat). Customer support is provided, for example, via (voice or text) chat on the homepage using !chatbots. Such approaches can be found in !Social CRM. Metaverse Notion from a science fiction novel by Neal Stephenson from 1992 that has recently spread to denote a comprehensive virtual world created by virtual (!VR) and augmented reality (!AR) technologies. Similar to the Second Life environment that was launched by Linden Labs in 2003, metaverse represents a separate world besides the real world where users are present as avatars and are able to purchase goods or properties and to conduct transactions via digital technologies (e.g., !cryptocurrencies). Among the early examples are Decentraland where events (e.g., concerts, exhibitions) take place, the gaming platform Roblox where users are able to purchase items as well as the Horizon platform announced by Facebook,

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which even renamed itself into Meta at the end of October 2021 to reflect the importance of the metaverse. Microfinance/Microfinancing Granting of small (micro) loans to people who are not served by traditional banks, due to poverty or to companies whose borrowing requirements are too low to receive loans from traditional banks. The microfinance industry that developed has its origins in the emerging markets and has spread to Europe and Germany with the rise of !startup or !fintech businesses. At present, microfinancing has become a specific financial instrument for !startup businesses that operate with low debt capital requirements and is reflected in !crowdlending platforms such as Kiva. Micropayment Payments with low payment amounts are in the range of up to 5 € and tend to exhibit process costs that exceed the payment amounts. For example, !e-payments such as credit card payments often require minimum amounts and special procedures have been established for small amounts (e.g., cash card, !mobile payment). Microservice In contrast to the often monolithic (or “one-piece”) architecture of !application systems (e.g., in !core banking systems), the architectural principle of microservices aims at a modular design of !applications. Since it is more lightweight than the complex monolithic architectures, it has become also common in the !fintech sector. !Crowdlending solutions could, for example, include microservices for credit registration, credit scoring, debt collection or customer analysis. Companies such as Modularbank have built their platform on microservices, and microservices are also found in !open banking concepts. They may be implemented using !web service technologies, often using !REST. Middle-Office Organizational and process area of financial service providers that is concerned with the ex-ante verification and ex-post control of transactions. This also includes crossfunctional organizational units such as risk management or product development, which are “downstream” of the !front-office and “upstream” of the !back-office. Middleware Denotes a middle layer in software system architectures and forms an approach for the integration of !application systems. While a bilateral coupling of system components or modules leads to a high complexity of connections, the concept of middleware aims at reducing this complexity by adding a layer that manages the interfaces. As shown in Fig. 8, one component accesses many other systems (or modules or !services) via this middleware layer. Depending on its functional scope, the middleware takes over this coordination between the !services, e.g., the administration of the interfaces (!API) in directories, the flow control or the assignment (mapping) of data formats.

I–M Fig. 8 Bilateral integration and integration via middleware (based on Alt, 2018a, p. 124)

131 Bilateral integration (1:1) Coupling e.g. via API/RPC

Integration via middleware (n:1:n) Coupling via middleware

Miner Derived from the activities of workers in physical mines, miners are participants in a !cryptocurrency network who perform the task of !mining. They compete for the calculation of new blocks, whereby successful miners generate the blocks and store the transactions in the distributed database (!ledger). In return for this mining of blocks and the provision of the necessary computing power, miners receive a remuneration in form of !block rewards. Minimum Viable Product (MVP) Based on the philosophy of prototyping, users should receive an impression of a new solution (product and/or service) with sufficient or minimal basic functions at an early stage in the development process. Pilot users should be given an opportunity to test the new solution, which enables developers to collect relevant data and include this in subsequent development steps. The complete functional scope is typically only available after the interaction with the early adopters of the product, so that the development of an MVP also serves to reduce risk. Mining Mining is a key task in !cryptocurrency systems that use the !PoW procedure as a !consensus mechanism. In this procedure, the !miners generate the individual blocks that include the transactions of the !blockchain network. Mining Pool This virtual combination of several !miners intends to conduct successful !mining in !blockchain systems that are based on the !consensus mechanism !PoW and require significant computing power. The remuneration (!block reward) is divided according to the shares brought into the pool (so-called pay-per-share). Among established mining pools are AntPool, Poolin and Slush. Mixed Reality Combination of augmented reality (!AR) and virtual reality (!VR) that allows users to see both real and virtual objects in a display (e.g., a head-up display). The concept originated from the field of computer games and has found use cases in service industries. In the financial sector, users may, for example, see their (physical) credit card together with the (virtual) transfers made with it. Mixing Service Refers to service providers who exchange !coins of !cryptocurrencies (in particular !Bitcoins) and thereby change the allocation of the !coins and prevent traceability.

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On the one hand this increases privacy, while it may contribute to money laundering on the other. Mobile Banking Describes the financial activities that are carried out via mobile devices such as smartphones, tablets or !wearables using an !app. Logging into !online banking via a browser on the mobile device is not considered as mobile banking. Mobile Brokerage Securities trading via mobile devices allows investors to access trading platforms and actively manage portfolios via an !app or a mobile website. Besides traditional banks, !fintech companies such as Acorns, Robinhood or Stash offer mobile brokerage solutions. Mobile Claims Processing Describes solutions in the insurance sector that support customers in claims processing via mobile devices. The functionalities include the recording, documentation and calculation of claims, thus enabling a more efficient claims processing. In the future, claims can be reported not only via smartphones or tablets, but also directly via intelligent objects (e.g., vehicles, houses) and !M2M communications. Several !insurtech companies (e.g., Lemonade, MotionsCloud) already offer solutions for mobile claims handling and often combine these with an overview of insurance policies, etc. Mobile Payment (m-Payment) This form of !electronic payments comprises the recording and processing of payments via mobile devices such as smartphones, tablets or !wearables. Wellknown providers are !Alipay, Apple Pay, Google Pay, PayPal, Paydirekt or !WeChat. They complement the !four-corner model by supporting payments at the point-of-interaction (!PoI) via host card emulation (!HCE), thus providing an alternative to payment cards at the !point of sale. A distinction is made between forms with or without reference to card-based procedures (!EMV). While !peerto-peer payments or !cryptocurrencies often have no reference to card-based !payment systems, this is not the case with many existing mobile payment methods (e.g., Apple Pay, Google Pay). While customers have the impression to use mobile !payment services, established payment processors known from the four-corner model or technical solutions such as !ACH or !EMV continue to operate in the “background” (see Fig. 9). However, as the example of PayPal with its own payment network illustrates, alternatives to the !four-corner model with !three-corner models as well as fully decentralized (two-corner) models with distributed ledger technologies (!DLT). Mobile Wallet This !wallet is an !application on mobile devices such as smartphones or tablets for making cashless payments.

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Buyer/debtor (mobile payment customer)

Point of interaction

Point of sale

Mobile payment solution (e.g., Apple Pay, Google Pay etc.)

Seller/vendor (mobile payment acceptance point)

Digital payments (card schemes)

Fig. 9 Mobile payment as a connection to digital payments

Mobility Services Although mobility services have been established with public transportation as well as private transportation companies (e.g., railways, airlines) for long, !digitalization has given rise to digital mobility services that feature stronger !personalization and are based on the principles of the !sharing economy. Examples are ride hailing services such as Uber and Lyft, car sharing services such as Teilauto, e-scooter services such as Bird, Lime, Tier or Voi and carpooling services such as BlablaCar. A key aspect of these services is the integration of several digital services (!smart service), including navigation and payment functions. Mock-Up In the sense of a demonstrator or a demonstration model, a mock-up is an early, not necessarily functional prototype of a product or service. For !startup companies, mock-ups are important because they concretize the idea of the future solution for potential customers and investors. Mock-ups can therefore be found as a component of many innovation methods, e.g., !design thinking. Typically, mock-ups precede the development of minimum viable solutions (!MVP). Mondex Initiated in the early 1990s, Mondex offered the first stored cash card and was purchased by Mastercard in 2001. It allowed decentralized payments without central authorities long before !Bitcoin and other !crytocurrencies emerged. Monero !Cryptocurrency, which aims at achieving high degrees of confidentiality. The transactions stored in the !blockchain (e.g., payments, account balances) cannot be viewed transparently, which is why Monero is a popular medium for payments in the !darknet. Moneta !Digital platform that connects people without bank accounts to the global economy and provides access to the full range of financial services. Money Laundering !Anti-money laundering (AML).

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Mortgage Financing This financing option for !fintech businesses is similar to the purchase of tangible assets such as real estate, which are partly financed by the company itself and partly by external financing. Debt financing is usually provided with a mortgage. The creditor of the mortgage (usually a credit institution or a building society) provides the !fintech company with the necessary debt capital and receives a lien on licenses, patents, etc. in return. In the event of the !fintech company’s insolvency, the creditor can realize the licenses in his own interest. Multi-bank Based on the observation that customers maintain several bank accounts instead of a single account with a main bank !application systems that aimed achieving an overall consolidated view and functionality on these individual accounts were already developed in the 1990s. They enable customers to manage several bilateral bank relationships via a uniform user interface that allows consolidated views on accounts and assets (sometimes even banking and insurance services) and a centralized initialization of transactions. The introduction of standardized bank-customer interfaces since the mid-1990s (!HBCI, !FinTS) formed the basis for these multibank solutions, whereby customers can access the other systems via a bank’s !online banking or a separate !PFM system (dashed lines in Fig. 10). The multi-bank capability is considered an important element of the !customer experience and, in particular with the regulatory basis being created by !PSD2 (!accessto-account), has been subject of !business models of numerous !fintech companies (e.g., N26, Neon, Revolut, Robinhood or Yapeal). As shown in Fig. 10, in the multi-bank scenario only the consolidating actor has direct customer contact (bank 1 or PFM system provider), while banks 2 to 4 loose this contact. Multi-chain Term for !blockchain or !DLT frameworks that focus on the !interoperability of different !cryptocurrencies. On the one hand, !coins of one !cryptocurrency (e.g., !USD Coin) can also be used in other !cryptocurrencies and, on the other hand, !cryptocurrencies can build intermediary !data structures (e.g., !Polkadot) that sustain cross-ledger integration (!CLI).

Bilateral bank relations

Multi-bank relationships

OB Bank 4 OB Bank 3 OB Bank 2 Customer

Online banking (OB) Bank 1

Online banking (OB) Bank 1

Online banking Bank 3

Customer

PFM System

Fig. 10 Bilateral vs. multi-bank relationships

Online banking Bank 4

Online banking Bank 2

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Multi-channel This concept refers to the interaction of a company with its customers via at least two different channels (e.g., online, e-mail, app, in-car) in order to support customerfacing processes (i.e., marketing, sales, service). Multi-channel approaches shall support a consistent !customer experience across all channels, which is regarded as a !critical success factor especially in service industries. The similar concept of !omni-channel management goes beyond offering various channels (as so-called silos) and foresees the possibility of seamlessly switching between the different channels. Multi-dealer Platform (MDP) With the transition from physical floor trading to virtual electronic trading on !OTC markets at the beginning of the 1990s, intermediaries emerged to allow their clients to trade across multiple banks and platforms (e.g., !ATP, !electronic exchange, !MTF). The dominant providers are Refinitiv, Bloomberg, State Street, CME or Deutsche Börse. Multi-home Indicates a situation in a market or industry where customers and/or suppliers can choose between several offers without monopolies being present. In the financial sector, the term is commonly used to denote the choice between different forms of payment. In addition to cash payments, there are numerous forms of !electronic payments. Multi-sided Platform (MSP) This form of an !electronic market assumes that more than one player is present on both sides of the market. While single-sided platforms are based on the principle of the supermarket and include products from different suppliers!, multi-sided platforms act as !brokers and make their platform available with the corresponding functionalities (e.g., product/service catalogue, shopping basket/contracting functions, billing/payment functions). One example is Amazon, which has developed from a single-sided to a multi-sided platform with the Amazon Marketplace. As a result, suppliers competing with Amazon (e.g., book suppliers) may also offer their products via the Amazon platform. While they benefit from the reach and functionality of this !platform, Amazon in its role as platform provider receives fees for each of these transactions and obtains access to the corresponding data for usage statistics. In the financial sector, the MSP logic is reflected in !platform banking strategies and also in various forms of !peer-to-peer platforms (!crowddonating, !crowdfunding, !crowdlending, !crowdsourcing). Multi-signature Multi-signature or multisig is a technology used in !cryptocurrency transactions to provide additional security. Multi-signature addresses require at least one other user to confirm or sign a transaction before the final entry in the !distributed ledger is made. The required number of signatures may vary and may be defined by the users upon setup of the solution.

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Multi-version Concurrency Control (MVCC) Multi-version Concurrency Control (MVCC) is a method for controlling the consistency of data accessed by multiple users simultaneously. This database technology procedure is designed to execute concurrent accesses to one or more (distributed) databases as efficiently as possible without blocking the system or jeopardizing the consistency of the database. Each transaction receives a consistent image (“snapshot”) of the data at startup and when a transaction updates an entry, the system checks that no other transaction is updating the entry at the same time. Only then it will create a new version of the entry. The new version is not visible to other transactions until it has been successfully completed. At the time of the update, the entry is blocked and signals an error, known as an update conflict. Multilateral Interchange Fee (MIF) In addition to the bilateral interchange fee (!BIF), which is charged between the !issuer and the !acquirer for card payments, MIFs represent the interchange fee (!IF) that credit card companies such as Visa and MasterCard may charge as a margin on card transactions between the !issuer and the !acquirer. Currently, the MIF is 0.2% for debit cards and 0.3% for charge and credit cards. Multilateral Trading Facility (MTF) Multilateral trading systems are (mostly electronic) market !platforms that allow securities to be traded as an alternative to existing financial exchanges (!electronic exchange). Examples are Aquis, Bats Chi-X, Cboe, Tradegate and Turquoise. Mutual Distributed Ledger (MDL) A term used synonymously with distributed ledger technology (!DLT) that emphasizes mutual validation of transactions, but has not been widely used, at least so far.

N–R

National Electronic Funds Transfer (NEFT) System of the Reserve Bank of India that processes payments as an automated clearing house (!ACH). National Securities Identifying Number (NSIN) Denotes country-specific identification standards to characterize securities. NSINs consist of nine alphanumeric digits and include national standards such as the !CUSIP in the US, the !SEDOL in the UK, the !WKN in Germany and the security number (“Valorennummer”) in Switzerland. The respective !NSINs, in turn, are part of the international securities number !ISIN. Figure 1 shows the structure of the NSIN using the Deutsche Bank share as an example. Natural Language Processing (NLP) Method within the field of artificial intelligence (!AI) for human speech (text or audio) by computers based on rules and !algorithms. The goal of NLP is a direct communication between humans and computer systems based on natural (written or spoken) language. NLP is used in the financial sector, for example, for !sentiment analysis or in the context of !chatbots or !virtual assistants. Near Field Communication (NFC) A technology of wireless data transmission based on induction, similar to !RFID technology. NFC devices must be located in immediate vicinity (11,000 banks in >200 countries and processes >30 million messages daily. For this purpose, SWIFT operates four computer centers (in Hong Kong, The Netherlands, Switzerland and the US) and organizes a data network for secure communication between the connected institutions (so-called SWIFTNet). SWIFT has also standardized important data and messages for electronic message interchange (!EDI) in payment transactions (e.g., !BIC code) and securities trading (e.g., ISO 15022) or contributed to their development. Future fields of development include the use of !blockchain technology and !ISO 20022 standards. Soft Fork A term frequently used in the field of open software (!open source), which refers to changes in software systems (!fork) where the new and older versions remain compatible. Compared to !hard forks, soft forks in networks such as the !blockchain are characterized by downward compatibility, so that the network nodes (!nodes) can operate with both the older and the new software. Software-as-a-Service (SaaS) Web-based method of software delivery where a software vendor hosts and maintains the hardware and software infrastructure (!cloud computing). In contrast to traditional !on-premise software, users may remotely access the application and are not required to invest in hardware or the hosting and maintenance of the software. Since the software functionality is offered as a !service, users will not purchase an unlimited license, but pay an annual or monthly license fee (subscription model). This fee usually includes the license and the support of the software together with the operation of the “underlying” hardware. It relieves users to make upfront investments in licenses or hardware and allows them to terminate the contract after a defined cancellation period. Most contemporary !application systems, in particular from !fintech businesses follow the SaaS paradigm (e.g., !banking-as-a-service, !blockchain-as-a-service). Software-Defined Business (SDB) With the !digitalization of business processes (!smart process), products (!smart product) and !business models, the role of software has increased in comparison to hardware. In addition to the technological-driven concept of !software-defined networking, SDB is application-oriented and characterizes the increased importance of software development to master the !digital transformation. It means that competencies and structures (e.g., !DevOps) regarding software development as well as in the cooperation with corresponding service providers are required. Businesses in the financial sector are particularly affected by this “softwarization” since design elements within this industry are information-based. In consequence, many !fintech companies consider themselves as !IT-companies rather than financial services companies, which brings !big tech companies in a position to also offer financial services.

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Software-Defined Networking (SDN) Describes the decoupling of hardware and software in a network environment. The concept is based on the !virtualization of resources and allows the integration of different end devices on one network (mostly, the internet) !protocol, the provision of location-independent virtual workplaces and data storage in the cloud (!cloud computing). In the financial sector, SDN is regarded as an approach for established banks (!incumbent) and !startup companies alike to integrate multiple end devices cost-efficiently and securely (!multichannel, omni-channel) or to provide !services such as !business analytics across multiple systems. In adddition, the centralized management of virtual resources is valuable from a !compliance perspective. Software Development Kit (SDK) Describes a software development environment consisting of a programming language, a runtime environment and a compiler as well as program libraries. SDKs in the !blockchain frameworks exist for !Corda (e.g., Tokens SDK), !Ethereum (e.g., OpenZeppelin SDK) or !Hyperledger (e.g., Fabric SDK). Solidity Object-oriented programming language built on JavaScript for developing !smart contracts in !blockchain frameworks such as !Ethereum. In addition to Solidity, Clarity is a programming language that uses the !blockchain system stacks 2.0 to complement !Bitcoin with the functionality of !smart contracts and !DApps (!Blockchain x.0). Solo Mining In contrast to !pool mining, solo mining denotes a single actor who participates in the !PoW !consensus mechanism procedure. When successful, this actor may claim the entire !block rewards and is not required to share them with other collaborating miners. However, solo !miners will require a high-performance computing infrastructure to achieve a competitive !hash rate. Sourcing While sourcing originates from the logistics sector and is concerned with the procurement of goods, a wider interpretation extends this meaning on the procurement of resources, such as computing services or business processes. In this wider sense, sourcing strategies may differ along four dimensions: (1) the type of the resources (e.g., the sourcing of technological infrastructure, !applications (!cloud computing) or processes (!BPO)), (2) the direction of sourcing (e.g., !insourcing, !outsourcing), (3) the location of the sourced service (e.g., onshoring, nearshoring, offshoring), and (4) the scope of sourcing (e.g., minimum, partial and maximum outsourcing), the latter being measured in steps of 80% by the degree of in-house production. In particular, young !fintech companies with limited resources depend on external partners and sourcing relationships for !collaboration. !Service level agreements are typically used to define and control these relationships.

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Special Purpose Acquisition Company (SPAC) A company established for investment purposes whose only business activity is the acquisition of companies. For this purpose, they raise funds on the stock market and enable investments over a maximum period of 2 years in companies that they subsequently intend to merge with. In contrast to traditional !IPOs, the process is less complex and more time-efficient. The concept has also become known in the area of decentralized finance (!DeFi), as the processes (such as repayments to investors if no suitable investment objects are found) may be automated (or digitalized) using !smart contracts. Stable Coin The combination of the words “coin” and “stability” designates !cryptocurrencies that are not subject to exchange rate fluctuations or feature only minor fluctuations. Stable coins thus intend to avoid a disadvantage of !Bitcoin as a !virtual currency. In particular, it aims to increase confidence in the respective currency, as it will become more similar to legal tender, especially regarding the currency function of value retention. Since the !cryptocurrency is linked to a reference currency, the base value of this reference object of the (e.g., a !token, an existing country or a !fiat currency, physical commodities such as gold, or another !cryptocurrency) determines volatility. Stable coins already exist in countries such as Brazil, China, Sweden, Singapore, and Venezuela. Staking In !cryptocurrencies that use proof-of-stake (!PoS) as !consensus mechanism, staking refers to the process of locking !coins or !tokens in a !wallet and to receiving rewards for contributing this way to the operation of the distributed network. Thus, staking is for !PoS-based systems what !mining is for proof-ofwork (!PoW) based systems. Staking Coin !Coin generated by a !cryptocurrency using the !proof-of-stake mechanism. An overview of widespread staking coins may be found in the tables on top30 cryptocurrencies in the Appendix. Startup According to the definition used in financial management, a company with an innovative idea evolves in case of success along several phase, in particular, the the !seed (development of prototypes or business concepts), the foundation (clarification of financing, !startup phase), the first phase (start of production and market launch) and several financing stages (!Series A-F). Since formal characteristics such as the age of the company or the number of employees are often not appropriate due to the uncertain evolution of startups, metrics such as the degree of !innovation, the !scalability of the !business model, the participation of !venture capitalists or !business angels or the life cycle phase, are commonly used.

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Startup Financing Refers to financing in the !startup phase and thus the second phase of !VC financing after !seed financing. If successful, this is followed by the !first-stage financing phase. Startup Phase The startup phase marks the phase of building up the company. Depending on the status of the !digital transformation and the technological field of application, extensive R&D activities occur in this phase, such as preparing production, sales and distribution as well as the market launch. Stellar !Cryptocurrency that provides an !open source solution for payment transactions or the exchange of !tokens. It uses the Stellar consensus protocol (!SCP) as !consensus mechanism. The network consists of about 60 nodes and is able to handle a large number of transactions efficiently since no !mining is required. Stellar Consensus Protocol (SCP) The !protocol for !Stellar’s !consensus mechanism is based on so-called quors (a series of !nodes), which achieve a secure !consensus by exchanging signatures. The intended features of SCP are decentralized control, low latency, flexible trust and high security. Stock Exchange Daily Official List (SEDOL) An identification standard for securities issued by the London Stock Exchange, which is incorporated into the !ISIN as the national identification number (!NSIN) for England and Ireland. A SEDOL has seven digits, six of which are alphanumeric and one numeric check digit. The conversion into the !ISIN is possible by adding the !ISO country code and two zeros as well as a final check digit. Figure 4 shows an example of an HSBC fund. Store of Value (SoV) Denotes a function of a currency (!virtual currency) that aims a maintaining the value associated with the currency. It is also used in the field of !digital currencies for !cryptocurrencies that are backed by !fiat currencies or other reliable assets. These !stable coins are expected to feature less volatilatility and, thus, serve as a “safe haven” for investors. Fig. 4 Structure of SEDOL (left) and transfer to ISIN (right)

Security (6- digits)

SEDOL (7- digits)

Zeros Check digit (2-s digits) (1-digit) Country (2- digits)

B5L01S8

Check digit (1-digit)

IE00B5L01S80

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Straight Through Processing (STP) Refers to the direct transmission of electronically recorded data or messages between two or more !application systems without !media breaks. The concept of electronic data interchange (!EDI) dates back to the 1970s and leads to an increase in processing speed as well as a reduction in manual (human) errors. According to the goals of !electronic business, STP is an essential prerequisite for integrated and cross-company processes. Sometimes (e.g., in the insurance industry) the term dark processing is also used for STP, since with a complete STP the execution is completely automated or not visible. Strong Customer Authentication (SCA) As part of the !PSD2 regulation, SCA is a requirement associated with the !twofactor authorization procedure (!2FA) to ensure the security of !electronic payments. Sub-chain This concept aims to establish !blockchains for individual application settings, where linkages among !cryptocurrencies are important. It follows the idea that the sub-chains increase the performance of a !blockchain (i.e., the !mainchain or !rootchain) and allows higher efficiency among less participants (!private blockchain). To avoid that a small number of participants corrupts the system, links (so-called anchors regularly integrate hashes in the !mainchain) exist to a larger !mainchain, which will typically be a !public blockchain. Super Peer Refers to enhancements of the !P2P model in computer networks that aim to use selected peer members (e.g., with powerful computing resources) as !nodes that support in organizing the network. In super peer networks like voice-over-IP services (VoIP) such as Skype, calls are not conducted via a central server, but via nodes (supernodes) between the individual users. Similarly, the super peer idea has been adopted with !master nodes in !blockchain networks. Supply Chain Finance In particular in multinational supply chains, a variety of suppliers as well as logistics service providers are involved. Including financial strategies in the management of these supply chains affects the procedure and timing of payments among this parties. Several fintech !business models have emerged in the field of supply chain finance that aim at improving working capital in the supply chain, to reduce administrative costs due to digitalized processes and to achieve favorable financing terms, for example, suppliers might be paid upfront (e.g., within 2 days). Sweet Equity This incentive-based remuneration system for employees of a company aims to avoid that employees leave the company. Following the sweet equity model, discounted equity shares are offered to employees as a binding bonus arrangement by the investors (e.g., the founders of a !startup). In the case of a management buy-out, managers may acquire capital shares, for example, at preferential conditions

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from the co-financing investment company, provided that certain basic conditions, such as ensuring business continuity or initiating measures to avoid customer churn, are met. Swiss Interbank Clearing (SIC) Switzerland’s national clearing system is operated by SIX Group, a joint effort by Swiss banks, and operates both as a !ACH and a !RTGS. SIC was established in the 1980s and is today the main actor for processing !electronic payments in Switzerland. In 2021, SIX has announced together with the Swiss national bank, to establish a dedicated networking infrastructure referred to as Secure Swiss Finance Network (SSFN), which creates a secure communication environment for over 300 banks and financial service providers that are connected to SIC. Switch/Switching In the field of computing networks, switches connect resources within a network and routers connect networks and switches. In the context of !electronic payments, switching is part of !routing transaction information to the corresponding recipient as part of the payment value chain (!payment service). Switching is necessary when the !acquiring bank needs to determine the appropriate !issuing bank and the appropriate clearing and settlement mechanism (!CSM). Switching also includes the conversion of data formats and operates as a !gateway that converts external formats into an in-house format for !authorization and settlement. Symmetric Encryption An encryption method (!cryptography) where the sender and receiver are using the same !private keys for encryption. Among established procedures are the advanced encryption standard (!AES) and the message authentication code (!MAC). Synthetix !Cryptocurrency from the decentralized finance (!DeFi) environment, which is built on !Ethereum and supports the trading of synthetic financial products (e.g., derivatives based on tangible or intangible assets). Tablet Advisory Tablet advisory describes the use of mobile devices such as tablets or smartphones to support financial service providers in advising customers. It aims to increase !customer experience with the interactivity and !personalization of the !applications on these devices (e.g., !robo advisors), but also to increase the efficiency of the advisory process. Especially the use of table advisory in the physical advisory situation often enables a more intuitive access to understanding the developed financial solution, as advisors develop the offer interactively with the customer, which makes it easier to follow and to understand what is being offered. Tangle !Data structure based on the concept of directed acyclic graphs (!DAG), which is used in the !cryptocurrency !Iota.

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TARGET Instant Payment Settlement Service (TIPS) !Service offered by the !ECB since 2017 for processing real-time payments (!real-time processing) between banks in the Euro area according to the SEPA instant credit transfer scheme. Participants include central and commercial banks. Technical Acceptance Provider (TAP) Companies that are concerned with providing infrastructural services for !e-commerce and !mobile commerce. These include, for example, !authentication services (e.g., 3DS authentication, risk assessment or scoring) or specific !identity verification procedures (e.g., !video ID procedures). TAP complement the roles of !issuers and !acquirers in the !four-corner model. Tendermint Using a !consensus mechanism without !mining, this software provides functionalities for a secure and consistent replication of an application on many systems. For security reasons, Tendermint should work even if up to one third of the systems fail. Consistency means that every non-failing machine has access to the same transaction log (!protocol) and calculates the same facts. Secure and consistent replication is important in !DLT systems and for fault tolerance in many use cases (e.g., currencies, elections). Tether Similar to !Bitcoin or !Ripplecoin, Tether is a non-unregulated !cryptocurrency that supports a 1:1 to the US Dollar, the Japanese Yen or the Euro traded !stable coin. Tether was founded in 2014 under the name Realcoin, but changed to Tether shortly thereafter and its !USDT token was tradable (e.g., via the !crypto exchange, !Binance) as of 2015. Tezos Tezos is both a !cryptocurrency and an !open source platform. It is supported by the Swiss non-profit Tezos Foundation with a global community of !validators, researchers and developers. The !Token XTZ is classified as a !utility token and serves as the basis for !tokenization initiatives as well as for the remuneration of !validators (!baking). Tezos aims at providing planning security for investors since only !validators decide on enhancements and avoid that !hard forks take place. Theta !Cryptocurrency based on !Ethereum, whose !ERC-20 !token Theta is used in the fields of video streaming and computer gaming. It allows users to share videos via the !DApp Theta.tv, which is integrated into numerous Android smartphones and also includes payment functionalities. Thin File In the area of credit scoring, a thin file refers to a limited creditworthiness, i.e., a individual person or legal entity with a short credit history. Thin files face difficulty in obtaining approval for loans or other forms of financing due to this missing history in dealing with loan repayments. As young entrepreneurs or !startup companies

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typically face a thin file situation, credit agencies often use alternative data for their credit assessments, e.g., payment transaction history, pension payments, rent payments or information from social media. Third-Party Issuer (TPI) These third-party providers (!TPP) also issue payment cards to customers without managing the bank account. The card-issuing institution (!TPP) does not have to be the same institute as the provider managing the account (!issuer). Third-Party Payment Service Providers (TPPSP) Third-party payment service providers are third-pary providers (!TPP) that specialize on payment services in compliance with the !PSD2 regulation. The term TPPSP includes payment initiation services (!PISP) and account information services (!AISP). Using the account holder’s personal access data, both types of service providers gain access to the account holder’s payment account. Payment initiation services initiate transfers to third parties, while account information services query the account balance and/or transactions. Third-Party Provider (TPP) Third-party providers who offer specialized services, for example in !outsourcing relationships and networks (!business network, !ecosystem). Numerous roles are present, for example, in the area of payment transactions (!acquirer, !issuer, !NSP, !PSP, !TPPSP) offer as defined in the !payment services supervision act (!PSD2). TPPs for !payment services comprise providers of account information and payment initiation services (!AISP, !PISP) as well as providers in the area of security services, which offer services such as !identity management, !authentication or key custody (!private key, !TTP). Third Stage Financing This refers to the final phase of venture capital (!VC) financing. In the case of !startup businesses, this stage includes to the provision of capital after the company has left the loss area or is about to or already in the profit zone and requires further financing to penetrate the market (!Series A to F). Three-Corner Model Compared to the !four-corner model, this architecture variant reduces the number of actors, since !issuer and !acquirer are bundled in one company and do not act as independent institutions (see Fig. 5). A well-known example of such a more closed network is American Express. Token Denotes a sequence of characters assembled according to certain rules. Tokens may be found in the field of knowledge processing, which breaks down texts into tokens for further processing (e.g., text mining), in the field of encryption, where tokens represent non-sensitive equivalents of sensitive data, and in the field of !digital assets, a digital representation of economic values. In the financial sector, text mining methods are used in !Social CRM and encryption methods are used in payments. For example, tokens contain encrypted credit card data used for online

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Transaction and payment order

Seller/vendor (acceptance point, dealer)

(cardholder)

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Authorization request

4

Feedback authorization request

Card scheme (e.g., Amex)

Issuer (debtor bank)

Legend:

Information flow

3

Authorization request and feedback

5

Design

Acquirer (vendor bank)

Financial flow

Fig. 5 Actors and activities in the three-corner model (based on Huch, 2013, p. 39)

payments and mobile or contactless payments (e.g., for data exchange between mobile device and merchant terminal and between !acquirer and payment network). They are managed on token servers of !token service providers (e.g., the credit card companies). Another type of token used in the financial sector are !virtual currencies, with physical coins already representing one type of token. However, the term has spread with !distributed ledger or !blockchain technology, where tokens represent the !digital assets that are exchanged. They may be interpreted as tokens or chips and are often used synonymously for !coins. Existing forms are !payment tokens (means of payment such as !Bitcoin, !Ether, which are often subject to !anti-money laundering regulations (!AML)), !utility tokens (prepaid royalty, not a means of payment or securities), and security or asset tokens (like a security, they represent assets or derivatives and are not a means of payment). The !utility and security tokens are often based on !payment tokens, which provide important basic functionalities as so-called protocol coins. For example, the !Tron and !Binance Coin tokens apply the !ERC-20 token and can therefore use blockchain 3.0 functionalities (!blockchain x.0). Tokens are sold in initial coin offerings (!ICO) as a form of financing where customers participate in the future product. For example, they obtain the assurance to receive shares/units after the !ICO occurred). Token Economy Following from the third area of !tokenization (i.e., tokens as digital assets), the broad notion of the token economy captures the impact of decentralized infrastructures on the economy, which includes new industry segments, markets and actors. It is based on the ability to digitalize aspects of virtual and physical objects (e.g., property rights, proof of origin, authenticity) and to make them amenable to being traded. The token economy is enabled by distributed ledger technologies (!DLT) and is attributed large potential due to improved process efficiencies and streamlined value chains with less actors (!disintermediation). An example is the field of

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decentralized finance (!DeFi) with various forms of !crowdfunding (e.g., !NFT). Token Generating Event (TGE) !Initial coin offering (ICO). Token Launch Describes the phase of an !ICO in which the search for investors who participate in !tokens initiated by a community takes place. These investors receive a defined number of !tokens for their investment. Token Purchase Agreement (TPA) Contract that specifies the conditions for the purchase of !tokens, e.g., !ERC-20based !tokens from !Ethereum. The contract includes the name of the !token, the purchase price, the terms of delivery, conditions to the buyer (e.g., a certain nationality), naming of risks, confidentiality rules or the regulation of exceptional cases (e.g., loss of keys, invalid !wallet address). Similar to service level agreements (!SLA), a TPA thus provides a legal basis for executing of !smart contracts. Token Service Provider (TSP) These service providers are responsible for managing !tokens on a !tokenization server in the area of !electronic payments. They apply to the second area of !tokenization, i.e., the security tokens in !mobile banking. Well-known providers include !issuers or operators of payment networks such as !EMV. Figure 6 shows the integration of these TSP in the !four-corner model for !mobile payments. User store their credit card data on their !NFC-capable mobile devices in the !app of

7

Buyer/debtor (card owner with mobile device) 6

13e

Tokenized PAN is stored

Payment request with payment details, tokenized PAN

Response payment authorization

Vendor/creditor (acceptance point, merchant)

Payment request with payment details, tokenized PAN Authentication, card details

15 Payment confirmation

Card verification request with card details 3

Issuer (debtor bank)

4

Token request with card details

5

11

Tokenized PAN

Tokenized PAN is detokenized

Payment request with payment details, PAN

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Payment execution

Information flow

Financial flow

Card scheme (e. g., EMV)

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Server e-payment provider (e. g., Apple Pay)

Payment request with payment details, tokenized PAN

Response card verification, PAN

12

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2

Tokenization server (e. g., card scheme, TSP)

8

10

Payment request with payment details, tokenized PAN

13b

Response payment authorization

14b

Payment execution

Tokenization PAN: Primary account number

Fig. 6 Integration of the token service provider in the four-corner model

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Acquirer (creditor bank)

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e-payment providers such as Apple Pay. The !app then transmits this data to the server of the e-payment provider (step 1 in Fig. 6), who forwards them to the TSP’s !tokenization server (step 2). From there, a request for verification of the card data is sent to the debtor bank (step 3) and after verification of the card data, the debtor bank sends the primary account number (!PAN) from the credit card back to the tokenization server (step 4), which tokenizes it and returns it to the server of the e-payment provider (step 5). The server in turn forwards the tokenized !PAN to the user’s !app (step 6), where it is permanently stored unless the user deletes it. If the mobile device recognizes an !NFC field at a point of interaction (!PoI), the user first needs to authenticate himself in the !app, e.g., via password, face recognition or fingerprint (!authentication), and may then use the stored card for payment. The !app sends the tokenized !PAN together with a transaction-specific security code and the payment data to the merchant terminal (step 7). This is followed by the traditional card-based processing in the !four-corner model (steps 8 to 15). Tokenization Corresponding to the three interpretations of a !token, there are also several conceptual understandings in the financial sector regarding tokenization. The first applies to the decomposition of texts in text mining. For example, this procedure is present in the area of !Social CRM to analyze unstructured data (such as annual reports and analysts’ reports or customer postings with !sentiment analysis). A second meaning refers to data security procedures based on !tokens, where a non-sensitive equivalent (i.e., the !token) replaces a sensitive data element. For example, !tokens (non-sensitive reference value) replace credit card number (sensitive data element) for credit card use. In payment transactions, the !token may then be passed on and used without restrictions and the need for additional security measures or certificates (e.g., !PCI compliance). The !token enables the merchants to store customer-specific data, such as the last four digits of the credit card number, in their systems and use it as an identity feature or preferred payment instrument in !one-click checkout procedures. The third concept conceives !tokens as !digital assets issued on a distributed ledger (!DLT). Tokenization describes the process of creating an unforgeable digital image of an asset and may be applied to numerous goods (e.g., shares, real estate or works of art). Corresponding tokenization services are offered by !crypto banks, but since !tokens may represent all types of property rights - from tangible or intangible objects to services or rights - a market segment is emerging that goes beyond today’s investment market and allows new forms of investment such as !crowdfunding. Total Cost of Ownership (TCO) Includes all direct (e.g., hardware and software procurement, development and maintenance costs) and indirect (e.g., downtime costs, !transaction costs) costs associated with owning a resource (e.g., hardware and software systems). The ownership lifecycle ranges from procurement through operation to maintenance and further development (e.g., due to regulatory requirements) and directly affects the cost burden of a company (!CIR). Besides establishing an overall view on these

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costs, the goal is to reduce TCO (e.g., via the use of !open source solutions) and to make fixed costs variable (e.g., via !outsourcing and !services). Trader Commission !Merchant service charge (MSC). Trading Platform A trading platform is a !digital platform with market functionalities (!electronic marketplace) for electronic economic transactions (!e-commerce). In the financial sector, there are established players (!incumbent) such as the financial exchanges (!electronic exchange), and younger players such as multi-trading facilities (!MTF) and over-the-counter markets (!OTC) as well as the !crypto exchanges. Trading platforms allow investors and traders to buy and sell securities, foreign exchange, options, futures, !cryptocurrencies and the like, online, either directly or via !financial intermediaries. Due to the large number of trading platforms, permanent and ubiquitous trading becomes possible and tends to contribute to a reduction of !transaction costs in the financial sector. Trans-European Automated Real-Time Gross Settlement System (TARGET) Clearing system that settles all Euro payments in the Euro area between the European Central Bank (ECB) and the central banks of the European countries that have introduced the Euro. The system connects the banks via the !SWIFT network and operates both as an automated clearing house (!ACH) as well as a real-time gross settlement system (!RTGS). Target2 has been in use since 2007 and the banks are connected to the system via the !SWIFT network. The replacement of TARGET by the T2 platform, has been announced for the end of 2021 and will also bring the adoption of the !ISO 20022 standard. Transaction-Based Directed Acyclic Graph (TDAG) Characteristics of a !DAG based on the graph-based networking of transactions. Transaction Bank !Business model of financial service providers that focuses on the processing of financial transactions (e.g., payment transactions, securities, credit, insurance orders). The goal is to achieve a cost advantage in !back-office operations by realizing economies of scale, often by bundling the settlement activities of several banks. Since transaction banks focus on transaction execution, they not necessarily require a !banking license. This also allows !IT service providers to position themselves in this domain. Transaction Costs For transaction costs, two interpretations may be distinguished. (1) In a narrower and more colloquial sense, they describe the monetary costs of an economic transfer of goods between economic entities. In the financial sector, such transaction fees are, for example, the costs of a credit card transaction, which are incurred by the merchant as a percentage of the value of a transaction per transaction (!MSC) or the interchange fees (!IF) flowing from the !acquirer to the !issuer. (2) In a broader and industrial economic sense, they refer to all monetary and non-monetary

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expenses associated with an economic transaction on the part of the buyer and seller. This begins with the time required to review offers and vendors in the market and continues through the negotiation of price and contractual conditions to possible disputes on the enforcement of agreed clauses. In principle, it may be assumed that !digitalization with comparison platforms (!electronic market) and numerous !self-services will help to reduce transaction costs and thereby contribute to the networking of companies (!business network). Examples include cooperation between banks (!incumbent) and between banks and insurance companies (!bancassurance) as well as between banks and !fintech companies. The reductions in transaction costs are also reflected in the recent !ecosystems and !open banking strategies pursued by many actors in the financial industry. Transaction Flow After !authorization of a !digital payment, the merchant and the !issuer store information about the transaction in their systems, which indicates that a payment amount has been transferred from the cardholder’s account. This process involves the !issuer, the merchant, the network service provider (!NSP) and the merchant bank. To initiate the processing, the merchant has various options for communicating the information about the authorized transaction to his merchant bank. For example, the merchant may send the information directly to the !NSP via the !POS terminal, which prepares the data and transmits it to the merchant bank. Likewise, the merchant may directly transfer the payment information to the merchant bank on a specific date that was agreed upon in advance. Regardless of how the merchant handles the transaction, the !issuer authorizing the payment needs to simultaneously enter a note in the account management system until the account is debited. Once this information about the transaction has been received by the merchant bank, the clearing and settlement (!CSM) process starts. In the context of !ATM transactions, the cardholder’s account is debited immediately, i.e., in real-time. Transactions Per Second (TPS) This key metric (!KPI) reflects the performance of transaction-oriented !application systems and networks. It is relevant for transaction processing in !core banking systems (e.g., in payment transactions or stock exchange orders) as well as in networks of !SWIFT, credit card providers or !cryptocurrencies. For example, Visa states a maximum TPS of 65,000 (Visa, 2020) for its credit card system, while internet sources (Sedgwick, 2018) assume a maximum TPS of 1700 TPS for Visa. In contrast, the TPS of the !Bitcoin blockchain is currently around 4–7 and is therefore subject to various enhancements to increase performance (!BIP). Due to such enhancements !Dash reaches about 30–56 TPS, !Eos about 5000 TPS, and !Neo about 1000 TPS (De Kwaasteniet, 2018). A similar situation may be observed with !Ethereum, where the traditional TPS of 7–15 is expected to rise to 100,000 with the Eth 2.0 expansion (Simmons 2020).

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Tron !Cryptocurrency founded in 2017 on the basis of !Ethereum and later constructed as an independent peer-to-peer network (!P2P), using the !proof-of-stake !consensus mechanism. It is organized according to the !DAO principle and differentiates itself through its free use and the claim to achieve a high performance of about 2000 transactions/second (!TPS) compared to other existing !blockchain frameworks. Trusted Execution Environment (TEE) Computing platform (e.g., based on Intel-CPUs) that features certain aspects (e.g., the transparency and verification of transactions and time logs), which are used in !consensus mechanisms. For example, the !PoET uses a random wait time for the construction of blocks (the !validator with the shortest waiting time creates a block), which is delivered by TEE. Trusted Third Party (TTP) A trustworthy third party is an organization that is trusted by the actors involved in an economic transaction. TTPs have emerged in the area of electronic identities (!electronic identity) or trust services (!custodian). Recent developments in the field of !DLT aim to replace intermediaries such as TTP with trust in the technological solution. Tumbler !Mixing service. Two-Factor Authentication (2FA) An !authentication procedure that is intended to provide a high level of security when accessing resources (!SCA), especially in the area of accounts. The !PSD2 regulation posts that at least two of the three characteristics listed are present for the verification of a transaction: (1) Knowledge that only the user has (e.g., username, password, one-time password, PIN, TAN), (2) possession of objects that only the user has (e.g., hardware token, bank card, key) or (3) biometric characteristics of the user (e.g., fingerprint, iris recognition, human voice). In addition, the features must be independent of each other, i.e., if one feature is not fulfilled, the reliability of another feature is not compromised, so that the !authentication data remains protected. Two-Way Peg A process that denotes a binding of !coins between !mainchains and !sidechains and enables the transfer of !coins in both directions. The !coins of the !mainchains are temporarily stored, which enables to generate and use !coins on the !sidechain afterwards. If the !coins of the !sidechain are invalidated, the temporarily stored !coins may be reactivated. Ubiquitous Computing !Pervasive computing.

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Unbanked Refers to persons or organizations without a bank account who usually pay in cash. They typically also lack other financial products such as insurance, pensions, investments, loans and therefore have no coverage by the financial system. Alternative financial services (!alternative finance) are also limited, such as cheques or payday loans (express credit), which means that this customer group is oftsen outside of the focus of financial service providers. Unbundling Describes the unbundling of existing value chains, which comes with a decrease of vertical integration in the financial industry. It is driven by innovative information technologies (!IT, !digitalization) and the emergence of !startup companies in the financial sector (!fintech). It leads to a fundamental change (!disruption) in traditional services or product offerings, for example by replacing established payment networks (e.g., !SWIFT) with !blockchain-based solutions, replacing or at least supplementing client advisors with !robo advisory systems, or replacing traditional forms of lending with !crowdlending. Unbundling is often related to the distinction of economies of scale, scope and skill. Thus, !fintech companies may bundle services of different providers (!multi-bank) from a customer perspective (economies of scope) or concentrate on a specific service offering (economies of skill). Due to the inherent economies of scale, !business models requiring high transaction volumes, such as in the field of payment transactions (e.g., !transaction bank, !virtual currency), represent a challenge for !startup companies. However, compared to existing providers (!incumbent) with historically grown (legacy) structures, !startup businesses tend to have lower administrative and overhead costs, but are often dependent on partnerships with other providers (!sourcing, !business network). The development often referred to as !rebundling also includes the intensified collaboration of banks (!incumbent) with !fintech companies, e.g., within the framework of !open banking solutions. Underbanked Refers to persons or organizations that have no or insufficient access to banking or other financial services at market rates. Similar to the !unbanked group, there is relevance to forms of !alternative finance and newer forms of !fintech business models (e.g., !micro-financing, !mobile banking). Underwriting In the insurance sector, underwriting refers to the mathematical assessment of risk to determine the appropriate premium for a specific risk. Digital underwriting often uses artificial intelligence (!AI) to calculate premiums in !real-time on the basis of comprehensive historical data. Unified Resource Identifier (URI) Generic term for identifiers of electronic resources that follow a specific structure or schema. These include function calls of application components (!API, !RFC) and concepts such as !REST and !SOA, the unified resource locator (URL) widely used for web resources, or the unified resource name (URN) widely used

200 Generic URI Schema definition

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S–V payto-URI = "payto://" authority path-abempty [ "?" opts ] opts = opt *( "&" opt ) opt-name = generic-opt / authority-specific-opt opt-value = *pchar opt = opt-name "=" opt-value generic-opt = "amount" / "receiver-name" / "sender-name" / "message" / "instruction" authority-specific-opt = ALPHA *( ALPHA / DIGIT / "-" / "." ) authority = ALPHA *( ALPHA / DIGIT / "-" / "." ) payto://iban/DE75512108001245126199?amount=EUR:200.0& message=hello

Fig. 7 Example of a payment instruction as URI (see Dold and Grothoff 2020)

for electronic documents. In the !fintech environment, URIs are present in the concepts of !API and !open banking. The example of a payment instruction with the syntax and data field definitions is shown in Fig. 7. The function call “payto” reflects the structure of the command with path (!IBAN), amount (EUR 200) and a message (“hello”). At the same time, this shows that an additional standard (in this case !IBAN) is required for uniform semantics of the data fields (alphanumeric or numeric characters), which are syntactically defined in a URI. If this is not the case, coordination on the meaning of the data fields is necessary between the communication partners (or systems) prior to the exchange of data. Unicorn !Startup company whose values are not yet listed on the stock exchange, but which investors estimate to have a prior !IPO market capitalization of more than USD 1 billion. This growth is typically based on !venture capital money and often “unicorns“are not (yet) profitable, as they place gaining market share before generating returns. Successful examples from the !fintech sector are Coinbase, Klarna, Lemonade, N26, Revolut, !Ripple or Transferwise. Unique Identifier (UID) To ensure the uniqueness of a material or immaterial object, codes are being used that either determine the affiliation of an object to a certain class of objects or they identify a specific object on item level. In the business world and within the financial sector, a large variety of standardized identifier codes has emerged to render transaction processing among multiple involved actors more efficient and to avoid costly matching processes. Among the examples are !BIC, !IBAN, !ISIN, !ITIN or !SEDOL. UIDs are also added to physical resources via !crypto anchors to prevent fraud. Uniswap !Cryptocurrency based on !Ethereum’s !ERC-20 token in the field of decentralized finance (!DeFi). Uniswap uses !smart contracts for decentralized trading of !cryptocurrencies and positions itself as a decentralized marketplace (!DEX) vis-à-vis to centralized marketplaces such as !Binance. The swap character is

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201 Tx 3 Tx 1 Tx 0

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Fig. 8 Example for an UTXO calculation (Hellwig et al., 2020, p. 8)

reflected in the idea that users may offer !tokens and receive a fee in the form of UNI tokens after the transaction in return for providing !liquidity. Universal Financial Industry Message Scheme (UNIFI) Specification for electronic data interchange (!EDI) in the financial industry based on XML syntax certified by !ISO. Also known as !ISO 20022, UNIFI defines the syntax of electronic messages primarily between the actors in payment transactions (!four corner model). As the !application systems of manufacturing and trading companies (!ERP), banks (!core banking system) and market infrastructure operators (e.g., !SWIFT, !electronic exchange) support the standard, UNIFI is an approach to make conversions between different formats more efficient and contributes to reduced !transaction costs in the inter-organizational setting (!business network, !ecosystem). Unspent Transaction Output (UTXO) Describes a balancing procedure that is applied in the !cryptocurrency !Bitcoin, whereas !cryptocurrencies such as !Ethereum or !Eos use an account assignment model. UTXO denotes !coins that result from transactions and may be used in other !Bitcoin transactions (see Fig. 8). Accordingly, an input minus a transaction fee is either marked as already spent or as output that has not yet been spent (i.e., unspent). To avoid !double spending, only unspent !coins are allowed as input for new transactions and the value of the received values always needs to equal to or exceed the amount that should be spent. Unus Sed Leo An !ERC-20-based !token used at the Bitfinex !crypto exchange, that serves to pay fees (e.g., for trading, custody, withdrawal) at that exchange.

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USD Coin !Cryptocurrency based on the !ERC-20 specification and designed as a !stable coin. The aim is to use established !fiat currencies in !blockchain applications. The !token is applied in several other !cryptocurrencies (e.g., !Eos, !Ethereum, !Tron), which explains why USD Coin is also called !multi-chain. User Experience (UX) The design of the user interface of !application systems is part of the UX design, which aims at a positive user experience when interacting with the system. UX is based on the principles of software ergonomics for designing user interfaces that are intuitive and performant in accordance with the purpose of the !application. Approaches used in UX design are service blueprinting or the design of customer journeys (!CJ), personas and storyboards as well as methods such as eye tracking or A/B comparison group tests for assessments. Since the user interface is the main touch point with customers in many, often digital-only, !fintech models, it has strategic relevance for !customer experience. Businesses adopt approaches like !DevOps that involve customers closely with development and operations to combine continuous innovation with high levels of stability. Utility Token Designates rights to use a product or to purchase a !service (e.g., computing power on the Golem platform) based on !coins of a !cryptocurrency. Depending on the purpose, a utility token may also assume the function of a means of exchange and payment as well as a security (!virtual currency). Compared to !security or asset tokens, which include shares in companies, utility tokens are less regulated and applicable on a broader scale. Validator Similar to the !miners in !PoW systems, the validators are dedicated !nodes in a !DLT system that have implemented the proof-of-stake (!PoS) !consensus mechanism. As co-owners (shareholders) of the !cryptocurrency, validators are involved in generating new blocks and in decisions on the further development of the system. They thus assume an essential !governance role that is also present in the concept of decentralized autonomous organizations (!DAO). Value-Added Service (VAS) Providers of value-added services have emerged from the field of network services (e.g., mapping of data fields, !routing of messages, management of keys) and have over time also covered higher (i.e., more business-oriented) functionalities. In the financial sector, VAS exist for example in the area of payment networks (!TPPSP, !TSP) and various !business models are currently emerging with the diffusion of !cryptocurrencies (e.g., regarding !mining, !business analytics or !interoperability). VeChain !Cryptocurrency that focuses on applying !blockchain technologies in the field of supply chain management and includes the !tokens VET and VTHO. While the

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VET solution is designed to achieve resource transparency by integrating data from different !application systems and !IoT devices in the supply chain using the !PoW consensus mechanism, VTHO aims at confidential trading via the !proofof-authority mechanism in the energy sector. Venture Commercial enterprise or a speculative act that involves a risk. Investors or company founders enter into this in the hope of making a profit. Venture Capital (VC) Venture or risk capital is a form of equity financing associated with equity and external financing. It is used to finance young companies (!startup) and is characterized by a higher risk/return profile. Typically, VC investors are rather interested in supporting innovative ideas than in short-term profit making (!single bottom line). Venture Capital Financing !Venture capital or risk capital financing is a form of corporate financing for companies that are considered to be particularly risky. It includes equity or equitylike instruments, such as mezzanine capital or convertible bonds, known as private equity. The capital is provided in the various phases or financing rounds of a !startup company (!Series A–F). Venture Capitalist Venture capitalists provide young companies (!startup) with venture capital (!VC) for their growth. Compared to other investors such as !business angels, they operate with higher investment amounts and only invest at a later stage. In addition, they tend to pursue primarily monetary goals and try to reduce the market risk by exerting control on the company by means of ownership shares. Venture Client These customers support !startup companies by purchasing their products instead of providing venture capital (!VC). The buyers of the products already become customers of a !startup company when the company is still in an early stage of development (!venture) and the product is not yet ready for the market (e.g., via a !crowdfunding !platform). In many cases, the promoters hope that this will give them a future innovation advantage. Verifiable Credentials Data for identifying things, people, or organizations that may be found in particular in the environment of decentralized identities (!DID) and can be structured according to verifiable credentials data model specification of the World Wide Web Consortium (W3C). Video Authentication !Video ID procedure. Video ID Procedure A procedure approved by the supervisory authorities (e.g., !BaFin) for the !legitimation of customers via video chat. As part of the !onboarding process,

204

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new customers show their ID document to a call center employee via a webcam or smartphone, who then checks the data and initiates the !authentication. Since identification is possible regardless of location, the procedure is used in particular by !fintech companies without physical presences (!smartphone bank). Examples of providers of Video ID procedures are IDNow or WebID. Virtual Assistant The term has two interpretations. (1) First, it refers to a form of remote support where employees provide or receive supporting !services (e.g., in their home office). These support services are particularly relevant for smaller and online companies that require infrequent support and refrain from hiring permanent staff for this purpose. The tasks of these gig workers (!sharing economy) are often in the areas of marketing, PR, social media management or web design. (2) Second, virtual assistants are !application systems that provide automated support in the form of !chatbots or !robots. They are also found under the notion of !personal assistants and establish new interaction channels (e.g., in the area of consulting and customer service) in addition to a company’s website or are combined with an !app for mobile use. Virtual Currency With the rise of information technologies (!IT), a !digitalization of money has occurred that has led to electronic currencies, which are also referred to as !alternative currency, !digital currency or !electronic money. First approaches date back before current !cryptocurrencies like !Bitcoin when in 1982 the scientist David Chaum designed the eCash system and founded the company DigiCash in 1990, which no longer exists today. Compared to traditional currencies (!fiat money), virtual currencies lack a physical representation of money in the form of coins or banknotes, and in most cases (with the exception of the development of electronic central bank money, !CBDC) they are not under the control of a federal authority. Virtual currencies or prepaid credit balances as non-physical and electronically stored assets may be used flexibly for large and small amounts as well as for national or international transactions. Although many existing regulations were initially not applicable to virtual currencies, more recent approaches such as the European Union’s !e-money directive or Germany’s !crypto custody business license point at an increasing regulation. Virtual currencies are usually acquired using traditional methods, e.g., by transferring electronic funds to a bank account, !e-wallet, card or other storage media. In general, virtual currencies may perform similar functions to physical currencies (see Fig. 9). As means of payment, natural persons and legal entities can use virtual currencies as a medium of exchange, whereby the transfer, safekeeping or trading is completely electronic and usually occurs in real-time (!real-time processing). Although they are not a legally recognized means of payment, virtual currencies are accepted in various environments (!e-commerce, !electronic markets). With an increasing regulation of !crypto exchanges and support from other parties, !cryptocurrencies are likely to gain in importance as a means of payment. PayPal, for example, has already announced to support payments via !cryptocurrencies. Regarding the unit of account and the

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yes

limited

yes

limited

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Means of payment Money as medium for conducting exchange transactions Unit of account Money as benchmark for assets Retention of value Money to store value for purchasing other goods

Virtual currencies

Coins and bills

Electronic money, book money

regulated

Traditional currencies

Certain regional currencies

Virtual currencies

physical Virtual currencies are often not accepted (means of payment), not used for pricing goods (unit of account) and volatile (value retention)

digital

Money type

Virtual currencies are only gradually being regulated in comparison to the traditionally regulated fiat currencies (e.g. stable coins, crypto-custody business)

Fig. 9 Distinction between traditional and virtual currencies

value retention function, virtual currencies feature important shortcomings. In particular, !cryptocurrencies are volatile in their exchange rate development and due to possible further developments (!forks) or the competition between the different !cryptocurrencies and !blockchain frameworks, their future existence is rather uncertain when compared to classical investments in scarce goods such as precious metals. However, due to the limitations of the money supply (e.g., 21 million !Bitcoins), !cryptocurrencies are increasingly suggested as investments in combination with scarce resources (e.g., gold, water) and crypto investments have been included in numerous funds or investment portfolios. Virtual Reality (VR) In this case, information technology (!IT) is being used to create interactive virtual environment based on digital media in which physical laws can be modified. Virtual worlds or environments are based on three-dimensional visualizations that are transmitted via large screens in special rooms (e.g., caves, !CAVE) or via !wearables such as head-up displays. With the diffusion of VR, several variations have emerged, for example augmented reality (!AR) that extends physical reality with visualizations (e.g., via AR-or data glasses) or !mixed reality, which links real and virtual worlds. A recent form or VR that is strongly promoted by !big tech firms is !metaverse. Virtualization In the technological sense, virtualization describes the creation of a virtual version of something, for example, a server, a desktop, an !operating system, or a network. Usually this is done by separating software and hardware, by emulating the hardware with software (e.g., !HCE). The main objective is to manage system loads to improve !scalability and resource utilization. Virtualization is at the heart of !cloud computing, which—despite early concerns regarding data protection and security—has also spread for !fintech solutions. In addition to this technical view of virtualization, there is an organizational view that conceives firms with a high degree of !outsourcing as virtual. Thus, even small companies with few employees may achieve a significantly higher virtual size by !outsourcing their tasks to partners and by becoming part of a larger business !ecosystem.

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Voice Recognition As an area of computational linguistics, voice or speech recognition involves procedures (!NLP) that use input and output devices on the computer to make spoken language accessible for automatic data acquisition. Similar to text recognition methods, speech recognition methods rely on artificial intelligence (!AI) and may be found in automated customer interaction (!chatbot) as well as in the interpretation of customer conversations (!sentiment analysis).

W–Z

Walled Garden An access-restricted user environment that only grants authorized users (!authorization) access to a defined number of data or services. It may be implemented as a protected environment on mobile devices for corporate applications (e.g., during mobile work) or to prevent minors from accessing certain content. In a broader sense, !ecosystems also form a walled garden if they are successful in creating entry barriers for competitors and thus in attaining customer and partner loyalty. Wallet In the !fintech context, wallets or !e-wallets refer to an !application, which resembles a customer’s purse and enables the virtual storage of !electronic money such as !cryptocurrencies or personal digital documents. Wallets are an important element in !cryptocurrency transactions (see the example of a !Bitcoin transaction). Wallet Import Format (WIF) This data exchange format in !blockchain systems allows the exchange of !private keys between different !wallets by means of the base58Check encryption method. Wealthtech The words “wealth” and “technology” have given rise to solutions for digitalized asset management (!DAM) and investment (i.e., wealth management). As a part of !fintech, wealthtech comprises digital solutions such as !robo advisory, digital !brokers, and internet-based investment applications. Since wealth management is an area of private banking, it is characterized by close personal relationships between bank advisors and their clients. For example, !family offices often offer comprehensive services that go beyond banking to comprise legal advice or support with organizing personal affairs. It has been observed that many approaches of !digitalization are not directly applicable with the wealthy clients who value personal relationships and disapprove waiting loops in call centers or standardized !chatbot interactions. However, solutions in the field of !robo advisory aim to © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2022 R. Alt, S. Huch, Fintech Dictionary, Contributions to Finance and Accounting, https://doi.org/10.1007/978-3-658-36056-6_6

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leverage !digitalization to provide private banking services also to less wealthy customers. An example is Quirin bank in Germany. Wearable Refers to computer (chips) or miniature electronic devices that people wear under, with or on their clothing. These include trackers for measuring bodily functions such as pulse, blood pressure or heart rate, as well as smartwatches for using electronic services (e.g., telephone, e-mail, navigation, !apps), glasses or headphones. In combination with !bots, they allow voice-based interactions with electronic services, for example, with financial service providers. In the insurance sector, wearables have spread to support flexible rates that are based on the user’s activity (!PAYU). Web Service Technology that has emerged from the field of object orientation and component software to enable the design of flexible modular !application system architectures. The web service stack comprises a collection of technologies that allow application components or web resources with an encapsulated functionality to be called via a defined interface (!API, !RFC). Due to these standardized interfaces, individual components should be composed more flexibly towards larger !application systems or content in web pages should be composed flexibly from various sources. The web service concept comprises two main areas. On the one hand, these are the standards of the World Wide Web Consortium (W3C) in the context of serviceoriented architectures (!SOA), which were developed at the beginning of the 2000s and include XML data formats for message transmission (so-called SOAP protocol), for describing and calling web services (web service description language, WSDL) and for cataloguing web services in directories (universal description, discovery and integration, UDDI). They were adopted particularly in the business application environment, as they comprise defined security functionalities (e.g., ensuring ACID requirements in the database area). On the other hand, !REST technologies have emerged as a more lightweight concept, which is considered to be less complex and more performant, but also less secure. REST is also present among !fintech solutions, both in the !front-end area (e.g., !PFM) and in the !back-end area (e.g., modular bank). The term !microservices, which is used in this context, emphasizes that these technological !services feature functionalities of finer granularity, which are implemented by means of !REST. Web3 This combination of the World Wide Web (WWW) and the third generation has evolved with decentralized technologies, such as !blockchain and !distributed ledgers. It recognizes the early phase of the WWW from 1992 until the beginning of the 2000s as first distributed ledgers. It recognizes the early phase of the WWW from 1992 until the beginning of the 2000s as firstauthority from centralized !platform providers (e.g., !GAFA, !BATX) to the users themselves, thus leading to more decentralization and democratization in the web. Web3 questions the role of established third parties such as banks, insurance companies

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and exchanges by replacing them with structures and processes of decentralized finance (!DeFi). Among the examples are !electronic payments with !cryptocurrencies, !crowdfunding platforms, !crypto exchanges for fungible and non-fungible !tokens as well as decentralized organizations (!DAO). However, it is still an open question to which extent Web3 solutions will replace existing structures since decentralized solutions tend to favor !cybercrime and responsibilities (e.g., for liabilities or after-sales inquiries) in decentralized settings are often unclear. WeChat Available since 2011 and comparable to WhatsApp, the WeChat messaging service is widely used worldwide, with approximately 1.2 billion users, primarily in China. A key functionality of WeChat Pay is the !wallet, which may be used for most types of !electronic payments. WeChat Pay’s main competitor in China and the market leader in !electronic payments is Alibaba Group’s !Alipay. Wertpapierkennnummer (WKN) ! Securities identification number (WKN). White Label Originating from the media sector where records that can be individually designed are marked with white labels, the term is also used for electronic services that a provider offers in a standardized form to several customers, who in turn market or use them under their own name. Digital !services such as !online banking, personal finance management (!PFM) or !robo advisory solutions, use the bank’s brand name, company logo and choice of color. It thus makes them appear as solutions from that bank, although they are standard solutions from a third-party provider (!TPP), such as the Mangopay payment solution. A whitelabel strategy allows users to take advantage of numerous services from an !ecosystem and thus achieve a larger virtual company size (!virtualization). Wisdom of Crowds (WoC) Also called swarm intelligence, WoC refers to the intelligence of the masses, which is largely based on the extraction of knowledge from a multitude of data (!big data). Following the idea of !collective intelligence, it is expected that with an increasing number of opinions, the quality and significance of the cumulative estimate improves. The intelligence of the crowd means that individuals who independently collect, analyze and evaluate information benefit when sharing this information in social interactions since innovation and decision-making processes are strongly social in nature. Thus, the collective opinion of a group of individuals in the information age leads other individuals to access social media such as Wikipedia, Yahoo!, Quora, Stack Exchange, and other web resources as knowledge bases in the sense of trustworthy and even scientific sources (!network effect).

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Wrapped Bitcoin (WBTC) This !cryptocurrency features a one-to-one relationship from !Bitcoin (BTC) to traded !tokens built on !ERC-20. It enables the use of BTC in !wallets, !DApps as well as !smart contracts on the !Ethereum !blockchain. Wrapped Ether (WETH) This !cryptocurrency !token is traded one-to-one with !Ether (ETH) and based on !ERC-20. It is used for !real-time payments on !platforms (e.g., the decentralized !e-commerce system Opensea) that are based on ERC-20. Xetra !Application system of Deutsche Börse for executing stock orders at !electronic exchanges. Introduced in 1997, the system allows registered traders to access the market from any location and supports the entire transaction process with an electronic !order book and !clearing system. This is particularly the case if the traders are !robots such as those found in high-frequency trading (!HFT). Numerous products of !fintech companies are listed on centralized exchange systems such as Xetra, e.g., !ETF or !ETP. In addition to the trading of financial products, Xetra is also used for trading energy products (e.g., on the European Energy Exchange, EEX). Xrp !Coin issued by the !cryptocurrency !Ripple, which was initiated in 2012 and is mainly used to support international payment transactions (!cross-border payment). The generation of these !coins is based on the XRP Ledger Consensus Protocol, which is similar to !PBFT and comprises a small number of validation !nodes. Since !Ripple also holds large amounts of Xrp in an !escrow scheme and determines access to the network, Xrp may be conceived a !permissioned blockchain. ZCash Zcash is a !cryptocurrency based on the original !Bitcoin code base. The goal is to improve the privacy of the users compared to other !cryptocurrencies, in particular !Bitcoin. Due to the underlying zero-knowledge proof concept (!ZKP), Zcash participants may decide for themselves which data they intend to make transparent. For example, encrypted data and the corresponding balances on the !blockchain are not visible. Payment disclosure and special view keys are used to exchange transaction details with trusted third parties (!TTP) for !compliance purposes or audits. Zero-Knowlege Proof (ZKP) Within !cryptography, a knowledge-free proof or a knowledge-free !protocol refers to the communication between two or more parties (the prover and the verifier). The prover convinces the verifier with a predetermined probability that he knows an information, without disclosing this information itself. A prominent method is the Feige-Fiat-Shamir protocol that is also used in the context of !cryptocurrencies like !Zerocoin or !ZCash.

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Zerocoin !Cryptocurrency based on !Bitcoin, which has been created to clear the transaction history that is associated with the linked blocks in a !blockchain system. It uses a collective !escrow pool to draw !coins and verifies transactions by means zeroknowledge proofs (!ZKP). Although originally proposed for use with the !Bitcoin network, Zerocoin may be integrated in other !cryptocurrencies as well. Zombie Bank A bank that would not continue to exist without state warranties, such as rescue packages as a type of guarantee or loans. Since the economic net assets after deduction of all assets and liabilities are negative, the zombie bank is de facto a bankrupt business. Zombie Loan Zombie loans are corporate loans that keep debtors alive by raising capital at favorable (e.g., extremely low) interest rates. These companies are unable to earn their own cost of capital over a longer period of time, and therefore would be bankrupt if the cost of raising capital were higher (e.g., in a normal interest rate environment). The loans therefore have an increased risk of default. Zombie Startup A company financed with venture capital (!VC) that requires additional funding to continue its growth but has already consumed the funds from previous rounds of financing. Although revenues exist, these are not sufficient for long-term profitmaking and to sustain an independent existence. This makes it difficult for the venture capitalists to make a profitable exit or sell their shares. As a result, the investors and the !startup company tend to stick to the !business model and continue to invest, benefitting from low capital costs. Since the company remains in the market rather artificially, it acts to a certain extent as a “brainless” zombie company and harms the emergence of new !business models or !disruptions driven by market forces.

Numerical Terms

3D Secure 3D Secure is an XML-based !protocol that serves as an additional security check for online payment card transactions. The credit card company Visa was the first to use the “Verified by Visa” procedure to improve the security of !authentication for electronic card payments. 42 The number 42 is commonly encountered in the !fintech and !startup environment as a reply to the question of the meaning of life or of “why you do something the way you do it”. It originates from the science-fiction novel by Douglas Adams “Life, the Universe and Everything” from 1982. 5G The fifth-generation mobile communications technology provides an increased speed of data transfers compared to its predecessor technology 4G (LTE). While 4G reaches up to 100 Mbit/s, 5G should achieve up to 10 GBit/s. These improvements are the basis for new use cases, in particular in the areas of !pervasive computing and the internet of things (!IoT). As for most infrastructure goods, there is an interdependence between the availability of the network infrastructure and the availability of 5G-capable end devices on the one hand and 5G-capable applications and !services on the other hand. While the technological infrastructure is increasingly available, applications are still scarce and thereby harm !network effects. Potential applications in the financial sector could include !location- and usagebased services (!LVS, !PAYU) and !smart services, the seamless use of multiple interaction channels (!omni-channel) and real-time processing in !mobile banking (e.g., with regard to security and regulatory requirements such as in the area of !AML). Although 5G infrastructures have become only partly available, the next generation 6G is looming at the horizon and promises higher speeds of up to 1 Tbit/s.

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Appendix

Top 30 cryptocurrencies (as of 28.03.2020)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Name Bitcoin Ethereum Xrp Tether Bitcoin cash Bitcoin SV Litecoin Eos Binance coin Tezos Unus Sed Leo Monero Stellar Cardano Tron Chainlink Huobi token USD Coin Crypto.com Coin Dash Ethereum Classic HedgeTrade Neo Iota Cosmos Nem Maker Zcash Okb Paxos Standard

Market capitalization (USD) 114’045’581’582 14’241’607’343 7’422’526’479 4’622’453’283 3’839’716’514 2’919’933’940 2’432’945’393 2’020’790’830 1’906’593’681 1’114’032’217 1’006’152’432

Price (USD) 6’234.96 129.14 0.169054 0.995710 209.19 159.11 37.79 2.19 12.26 1.58 1.01

Coin BTC ETH XRP USDT BCH BSV LTC EOS NBB XTZ LEO

Foundation 2009 2015 2012 2015 2009/17 2009/11 2011 2017 2017 2018 2019

Consensus PoW PoW LCP PoW PoW PoW PoW PoS PoS PoS PoW

803’896’573 797’841’155 743’542’964 742’262’655 740’015’630 735’546’378 679’007’745 609’761’208

45.94 0.039333 0.028678 0.011131 2.11 3.25 0.993889 0.042847

XMR XLM ADA TRX LINK HT USDC CRO

2014 2016 2017 2017 2017 2018 2018 2016

PoW PoS PoS PoS PoW PoS PoR PoW

599’553’858 556’906’682

63.76 4.79

DASH ETC

2014 2015/16

PoS PoW

HEDG NEO MIOTA ATOM XEM MKR ZEC OKB PAX

2018 2017 2016 2019 2015 2017 2016 2017 2018

PoW PoS PoW PoS PoI PoW PoW PoS PoW

458’568’110 449.425’869 382’629’327 369’820’962 328’950’408 299’208’976 287’167’506 249’058’247 248’533’993

1.59 6.37 0.137660 1.94 0.036550 298.17 29.96 4.15 0.994043

Sources: https://coinmarketcap.com/, https://en.wikipedia.org/wiki/List_of_cryptocurrencies, Alt (2022) own research + available,
not available, PoI Proof-of-Importance, PoR Proof-of-Reserve, PoS Proof-of-Stake, PoW Proof-of-Work, LCP Ledger Consensus Protocol (!XRP LCP), cryptocurrencies that are no longer included in the Top30 listing from January 16, 2021 are bolded

Appendix

217

Top30 cryptocurrencies (as of 16.01.2021)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Name Bitcoin Ethereum Tether Xrp Polkadot Litecoin Cardano Bitcoin Cash Chainlink Stellar Binance Coin USD Coin Wrapped Bitcoin Bitcoin SV Monero Eos Tron Theta Tezos Nem Uniswap Aave Synthetix Neo Crypto.com Coin Cosmos VeChain Maker Dai Unus Sed Leo

Market capitalization (USD) 701’221’245’579 139’355’967’928 24’224’535’048 13’088’842’909 12’434’035’045 9’830’243’465 9’753’783’605 9’320’740’130 7’634’600’544 6.489.633.019 5’838’908’203 4’738’427‘961 4’172’906’303

Price (USD) 37’398.01 1’207.05 0.99 0.28 13.52 147.06 0.31 499.73 19.45 0.29 41.02 0.99 37’752.98

3’903’986’196 2’850’462’510 2’619’331’021 2’174’345’143 2’104’207’022 2’017’553’379 1’957’357’779 1’946’150’646 1’920’201’184 1’749’389’506 1’698’328’205 1’660’794’224

209.85 160.54 2.79 0.03 2.10 2.78 0.21 7.05 157.05 14.94 24.07 0.07

1’650’125’193 1’626’686’091 1’533’342’538 1’417’108’106 1’333’221’455

7.76 0.02 1’522.97 1.00 1.33

Coin BTC ETH USDT XRP DOT LTC ADA BCH LINK XLM BNB USDC WBTC

Foundation 2009 2015 2012 2015 2017 2009/11 2011 2017 2017 2018 2019 2014 2016

Consensus PoW PoW LCP PoW PoS PoW PoW PoS PoS PoS PoW PoW PoS

BSV XMR EOS TRX THETA XTZ XEM UNI AAVE SNX NEO CRO

2017 2017 2017 2018 2018 2016 2014 2018 2017 2017 2016 2019

PoS PoS PoW PoS PoS PoW PoS PoS PoS PoS PoW PoS

ATOM VET MKR DAI LEO

2015 2015 2016 2017 2018

PoI PoW PoW PoS PoW

Sources: https://coinmarketcap.com/, https://en.wikipedia.org/wiki/List_of_cryptocurrencies, Alt (2022) own research PoI Proof-of-Importance, PoR Proof-of-Reserve, PoS Proof-of-Stake, PoW Proof-of-Work, LCP Ledger Consensus Protocol (!XRP LCP), cryptocurrencies that have entered the Top30 listing compared to the listing from March 28, 2020 are bolded

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Index

A Aave, 1, 37, 64, 125 Accelerators, 1 Access-to-account (XSTA, XS2A), xvi, 1 Account information service (AIS), 1, 2 Account information service provider (AISP), xi, 2 Acquiring bank/acquirer, 2 Advanced encryption standard (AES), xi, 3, 14, 190 Agents, 3, 5, 6, 68, 74, 115 Aggregators, 3, 31, 63 Agile organization, 3 Agility, 3, 65, 68 AI application areas, 4–6, 14, 163, 167, 168 Airdrop, 6 Algorithmic banking/Algo banking, 6 Algorithmic trading/Algo trading, 6 Algorithmization, 6, 7, 20 Algorithms, xii, 6, 7, 36, 44, 55, 126, 144, 159, 161, 162, 173, 174, 180 Alipay, 7, 132, 143, 209 Altcoins, 7, 30 Alternative credit scoring, 8 Alternative currency, 7, 8, 204 Alternative financing, 8 Alternative lending, 8 Alternative trading platform (ATP), xi, 8, 58 Ambient intelligence, 9 Anti-money laundering (AML), xi, 9, 103, 133 API banking, 9, 11, 17, 21, 46, 144, 145, 148, 165 App economy, 10 Application (App), vii, xii, 4, 5, 9–12, 14, 16, 17, 19, 20, 23–25, 30, 33, 40, 42, 51, 63,

65, 72–75, 77, 82, 93, 94, 111, 113–115, 118, 122, 128–130, 132, 134, 143, 144, 146, 152, 153, 158, 165, 167, 168, 170–172, 177, 180, 185, 188, 189, 191, 197, 199, 201–204, 208 Application programming interface (API), xi, 9–12, 15, 16, 20, 46, 56, 59, 144, 146, 147, 150, 151, 165 Application-specific integrated circuit (ASIC), xi, 10, 11 Application systems, 9–13, 17, 18, 20, 22, 34, 38, 39, 46, 59, 67, 73, 77, 81, 82, 88, 91, 94, 111, 114, 124, 128, 139, 142, 144, 146, 147, 149, 153, 158, 159, 163–165, 168, 210 App stores, 10, 46, 71, 139 Architecture 4.0, 12, 13, 20, 87 Artifact, 13, 167, 172 Artificial intelligence (AI), xi, 3–7, 11–14, 20, 31, 33, 38, 40, 42, 60, 64, 74, 114–116, 118, 120, 126, 137, 163, 165, 168, 181, 199, 206 Asymmetric encryption, 3, 14, 26, 55, 71, 85, 87, 158, 162, 163, 170, 173 Atomic swap, 14 Augmented reality (AR), xi, 14, 129, 131 Authentication, 1, 15, 29, 64, 71, 83–85, 91, 111, 123, 140, 142–144, 149–151, 154, 158, 160, 173, 180, 191, 195, 198, 204, 213 Authorization, 15, 55, 70, 84, 107, 111, 123, 124, 129, 142, 159, 175, 189, 190, 207 Automated clearing house (ACH), xi, 15, 20, 39, 137, 164, 196 Automated market maker (AMM), 15, 125

© Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2022 R. Alt, S. Huch, Fintech Dictionary, Contributions to Finance and Accounting, https://doi.org/10.1007/978-3-658-36056-6

223

224 Automated teller machine (ATM), xi, 16, 97, 120 Average revenue per user (ARPU), xi, 16

B Back-end, 4, 16, 17, 23, 75, 98, 208 Back-office, 16, 65, 67, 111, 112, 114, 130, 180, 196 BaFin, xi, 11, 17, 18, 50, 90–93, 95 Baidu, Alibaba, Tencent and Xiaomi (BATX), 22 Baking, 17, 191 Bancassurance, 3, 17, 95, 143, 177, 178 Bank-as-a-service, 39, 46 Bank code (BLZ), 18, 73, 116 Bankers’ automated clearing system (BACS), xi, 15, 20 Bank identification number (BIN), xi, 18, 120 Bank identifier code (BIC), xi, 33, 73, 120 Bank informatics, 18 Banking 2.0, 20, 21 Banking-as-a-service, 11, 21, 87, 142, 185 Banking industry architecture network (BIAN), xi, 20, 21, 23 Banking innovation, 21, 114 Banking of things (BoT), xi, 22 Banking platform, 2, 22 Bank license, 17–19 Bank model, 19–21, 73, 158, 164 Basic Bank Account Number (BBAN), 22 Batch processing, 22, 144, 164 Beacon, 23, 89 Best-of-breed, 23 B3i, 16, 45 Big data, 7, 13, 23, 32, 33, 40, 42, 59, 74, 114, 163, 165, 180, 209 Big tech, 14, 23, 24, 69, 71, 83, 85, 140, 152–154, 185, 205 Bilateral interchange fee (BIF), 24, 136 Binance coin, 24, 46, 193 Biometrics, 15, 24, 64, 91, 198 BiPRO, 24, 83, 118, 177 Bitbond, 24 Bitcoin, 7–9, 16, 22, 24–30, 42, 44, 45, 53–55, 58, 59, 62, 63, 75, 85, 89, 91, 92, 98, 99, 105–107, 109, 117, 125, 126, 128, 138, 139, 141, 148, 151, 156, 157, 161, 162, 166, 170, 171, 178, 186, 187, 191, 193, 197, 201, 204, 205, 210, 211 Bitcoin Cash (BCC/BCH), xi, 7, 25, 26 Bitcoin improvement proposal (BIP), xi, 25, 26, 172

Index Bitcoin SV (BSV), xi, 26, 28 Bitcoin transactions, 22, 26, 27, 70, 162, 207 Bittorrent, 28 Blockchain, 13, 14, 16, 17, 24, 25, 27–30, 33, 36, 37, 39, 44, 45, 47, 49, 52, 54, 55, 63, 64, 66, 71, 74, 76, 85, 88, 92, 95, 97, 98, 102–109, 111, 114, 116, 117, 120, 125, 127–129, 131, 133–135, 137, 138, 141, 146–149, 152, 153, 156, 157, 159–162, 164, 165, 170, 171, 174, 178, 185, 186, 189, 193, 197, 198, 202, 205, 207, 210, 211 frameworks, 12, 29, 30, 46, 53, 62, 118 sharding, 30 split, 7, 30 x.0, 12, 30, 193 Blockchain-as-a-service (BaaS), xi, 29, 30, 39 Block directed acyclic graph (blockDAG), xi, 28 Blocklet, 30 Block reward, 27, 28, 31, 131 Bluetooth low energy (BLE), xi, 23, 31 Bootstrapping, 31 Bot, xi, 31, 168 Bounty, 28, 31 Bridge finance, 31, 123 Broker, 3, 31, 32, 45, 68, 83, 93 Brokerage mandate, 32, 68 Business analytics, 23, 32, 59, 62, 91, 144, 175, 186, 202 Business angel, 32, 79, 176 Business case, 16, 33, 35 Business identifier code (BIC), 18, 33 Business information systems (BIS), 18, 21, 33, 34, 72 Business model, 1, 3, 10, 13, 16–18, 22, 31, 32, 34, 35, 41, 48, 53, 57, 58, 62, 64, 65, 67–69, 72, 73, 75, 84, 85, 87, 92, 101, 114–116, 118, 124, 127, 134, 139, 154, 162, 170, 171, 175, 176, 178, 182, 185, 187, 196, 199, 202, 211 Business model canvas (BMC), xi, 34, 35, 60 Business network, 35, 41, 192, 199 Business plan, 33–35, 48 Business process outsourcing (BPO), xi, 36 Buy now, pay later (BNPL), xi, 36 Byzantine agreement, 36, 45, 153, 157

C Call level, 157 Cardano, 30, 37, 161 Card scheme, 36, 70, 172

Index Cave automatic virtual environment (CAVE), xi, 37 Central banks digital currency (CBDC), xi, 8, 37 Chainlink, 37, 118 Challenger bank, 37, 38 Chargeback, 38, 53 Charity crowdfunding, 38 Chatbot, 3, 31, 38, 56, 115, 167, 182, 206, 207 Chief digital officer (CDO), xii, 38 Clearing and settlement mechanism (CSM), 39, 70 Client-server, 39, 152 Cloud computing, 12, 21, 29, 39, 42, 46, 62, 71, 74, 80, 109, 113, 139, 142, 149, 155, 165, 179, 185, 186, 205 Cockroach, 40 Cognitive computing, 40, 65 Coin, 6–8, 14, 17, 24, 25, 28, 37, 40, 41, 51, 53–55, 66, 68, 77, 141, 148, 157, 159, 160, 167, 175, 187, 193, 194, 198, 201, 202, 204, 210 Coin burn, 41 Cold storage, 41, 108, 141 Collaborative, 5, 41, 72, 115, 118, 140 business, 35, 41, 71 consumption, 41 experiences, 42 finance, 42 insurance, 42 Collective intelligence, 42, 51, 175, 184, 209 Colocation, 42, 43 Colored coins, 42 Combating the financing of terrorism (CFT), xii, 43 Combined ratio, 43 Committee on uniform securities identification procedures (CUSIP), 43, 73 Community banking, 44, 146 Compliance, 9, 21, 44, 91, 158, 165, 174, 180, 186, 195, 210 Consensus, xvi, 11, 26, 36, 44–46, 49, 64, 75, 104, 109, 141, 178, 188, 198, 210 Consensus mechanism, 25, 28–30, 41, 44, 59, 64, 76, 88, 89, 98, 104, 106, 107, 128, 131, 137–139, 141, 153, 156, 157, 159–162, 186–188, 191, 198, 202, 203 Consortium blockchain, 45 Contech, 45, 95, 161 Contextual finance, 45, 87 Contract for difference (CFD), xii, 45 Corda, 16, 30, 45, 46, 98, 118, 141, 158, 163, 186

225 Core banking system, 4, 10, 11, 13, 20, 21, 23, 39, 43, 46, 47, 73, 81, 158, 164, 168, 179, 201 Corporate startup, 46 Cosmos, 46, 118 Cost-income ratio (CIR), xii, 33, 47, 48 Counter terrorist financing (CTF), xii, 47 Covesting, 47 Co-working space, 39 Credit auctions, 48, 50, 113 Critical mass, 48, 125, 139 Critical success factor (CSF), 48, 68 Cross-border hub, 48 Cross-border payment, 49, 97, 210 Cross-chain, 49, 116, 125 Cross-ledger interoperability (CLI), 49, 53 Crowd, 49, 52, 91, 172, 184, 209 Crowddonating, 38, 49, 50, 135 Crowdfunding, 8, 38, 49–52, 64, 114, 135, 178, 194, 195 Crowdinsurance, 49, 50 Crowdinvesting, 8, 42, 49, 50 Crowdlending, 1, 8, 31, 44, 48–51, 113, 125–127, 130, 135, 152, 158, 163, 178, 183, 199 Crowdrewarding, 49–51 Crowdrisk, 51 Crowdsale, 51, 113 Crowdslapping, 51 Crowdsourcing, 42, 49, 52, 64, 135, 152 Crowdsupporting, 51, 52 Crowdtesting, 49, 52 Crypto anchor, 52 Crypto asset, 53 Crypto asset management (CAM), 53, 67 Crypto bank, 53 Crypto.com coin, 52 Cryptocurrency, vii, 1, 2, 6–9, 14, 16, 17, 19, 22, 24–26, 28–31, 36, 37, 40–42, 45, 49, 52–55, 58, 59, 62–65, 67, 70, 74, 75, 80, 84, 85, 87–92, 95, 97, 98, 102, 104, 106–109, 117, 118, 125, 127, 128, 131, 133–135, 137, 140, 141, 147–149, 151, 156, 159, 160, 165, 175, 178, 184, 187, 188, 190, 191, 196–198, 200–202, 204, 205, 207, 210, 211 Crypto custody, 9, 19, 53–55, 204 Crypto economics, 54 Crypto exchanges, 7, 9, 31, 44, 52–54, 58, 67, 68, 83, 84, 92, 141, 147, 191, 201 Crypto finance, 54 Cryptography, 3, 14, 28, 53, 55, 71, 76, 105, 158, 163, 171, 210

226 Crypto license, 53–55 CryptoKitty, 55 Cryptopunk, 55, 140 Crypto valley, 55 Curated shopping, 55 Custodial wallet, 55, 56, 175 Custodian, 53, 198 Customer experience, 55–57, 87, 103, 114, 134, 135, 140, 144, 158, 182, 190 Customer journey (CJ), xii, 56, 57, 60, 141, 144, 156 Customer relevance, 57 Cybercrime, 41, 58, 59, 75, 152 Cyber-physical system (CPS), xii, 57, 112 Cyber risks, 58

D Dai, 1, 58 Darknet, 59, 133 Dark pool, 58, 147 Dark processing, 59, 189 Dash, 59, 63, 128, 197 Data aggregation, 59, 92, 153, 183 Data-driven approach, 20, 59, 60, 154 Data-driven product, 60 Data-driven service, 60, 62 Data innovation board (DIB), 60, 61 Data structure, 28, 29, 62, 74, 77, 98, 105, 106, 118, 124, 127, 134, 156, 165, 190 Dealer commission, 62 Decentralized application (DApp), xii, 12, 55, 63 Decentralized autonomous organization (DAO), xii, 63 Decentralized exchange (DEX), xii, 1, 63, 64 Decentralized finance (DeFi), xii, 1, 15, 63, 64, 89, 123, 125, 187, 190, 194, 200 Decentralized identifier (DID), xii, 64 Deep learning, 11, 13, 40, 64, 167 Degree of digitalization, 64, 138 Delegated proof-of-stake (DPoS), xii, 64 Design thinking, 57, 60, 65, 72, 105, 112, 133 Desktop automation, 40, 65, 168 Dev, 65, 172, 173 Development environments, 29, 46, 65, 75, 98, 186 DevOps, 65, 66, 69, 105, 112, 185, 202 Diem, 8, 37, 53, 65, 66, 125, 184 Digirati, 66 Digital, xii, 3, 9–11, 22, 23, 37, 39, 54, 57–60, 64–72, 75, 77, 79–82, 85, 87, 89–91, 101–103, 105, 107, 112, 115, 123, 125,

Index 133, 138, 140, 141, 152, 153, 155, 156, 158, 161–163, 166, 167, 171, 173, 174, 178, 179, 182, 188, 192, 193, 195, 199, 205, 207, 209 assets, 1, 49, 53, 54, 56, 67 banking, 68, 143 champion, 66, 68 coin, 68 commerce, 68 currency, 9, 19, 54, 65, 66, 68, 77, 104, 204 identity, 68, 111, 118 insurance broker, 32, 68 management, 68 marketplace, 69, 82–84, 116, 127, 197 master, 68, 69 native, 69 payment, 69, 70, 133, 197 platform, 8, 10, 18, 23, 29, 49, 50, 52, 67, 69–71, 83, 133, 153, 155, 196 signature, 71, 158 transformation, vii, 12, 13, 20, 38, 67–69, 71, 72, 85, 112, 118, 124, 140, 188 twins, 72 value creation, 72, 124 Digital asset management (DAM), 53, 67 Digital currency exchange (DCE), 68 Digitalization/digitization, 72, 73 Digital markets act (DMA), xii, 69, 71, 74, 101 Digital personal assistant (DPA), xii, 70 Digital services act (DSA), xii, 69, 71 Digital voice assistant (DVA), xii, 72 Digithon, 72, 105 Direct bank, 47, 73 Directed acyclic graph (DAG), xii, 28, 62, 74, 76 Direct market access (DMA), xii, 74 Disaster recovery-as-a-service (DRaaS), xii, 74 Disintermediation, 74, 116, 152, 193 Disruption, 14, 38, 72, 74, 123, 124, 167, 199, 211 Distributed artificial intelligence (DAI), xii, 74 Distributed computing, 75 Distributed denial of service (DDoS), 75 Distributed ledger, 30, 37, 44, 47, 49, 53, 63, 64, 75, 76, 84, 100, 128, 139, 151, 152, 157, 158, 178–180, 193 Distributed ledger framework, 75 Distributed ledger technology (DLT), xii, 12–15, 28–30, 36, 37, 39, 44, 46, 47, 49, 53, 63, 64, 74–76, 136 Divesting stage, 76 Dodd-Frank act, 76 Domain name system (DNS), xii, 77

Index Domain specific language (DSL), 77 Dotcom bubble, 77 Double opt-in, 77 Double spending, 27, 77, 107, 159, 178, 201 Drop, 58, 78, 140

E Early stage financing, 79 Ecosystem, 10, 13, 20, 30, 35, 36, 40, 41, 54, 55, 71, 79, 80, 82, 87, 115, 142, 146, 148, 155, 192, 205, 209 Edge computing, 80 Electronic banking (e-banking), xii, 80 Electronic banking internet communication standard (EBICS), xii, 80, 81, 94 Electronic bill (e-bill), xii, 81 Electronic bill presentment and payment (EBPP), xii, 81 Electronic business (e-business), xii, 81 Electronic commerce (e-commerce), xii, 68, 70, 80–82, 85, 87, 88, 102, 142, 143, 150, 154, 155, 166, 196 Electronic data exchange, 24, 82 Electronic data interchange (EDI), xii, 73, 81, 82, 94, 189, 201 Electronic exchange, 5, 8, 15, 31, 58, 63, 82, 83, 90, 93, 107, 128, 135, 196, 201 Electronic health (e-health), xii, 83 Electronic identity (eID), xii, 83 Electronic identity verification (eIDV), xii, 83, 103 Electronic market (e-market), xii, 69, 83, 155 Electronic money (e-money/e-cash/e-money), 84, 207 Electronic payments (e-payments), 81, 84, 86, 97, 173, 178, 184, 189, 190, 194 Electronic value creation, 85 Electronic venture (e-venture), xii, 85 Electronic wallet (e-wallet), xii, 85 Elliptic curve digital signage algorithm (ECDSA), xii, 85 Embedded finance (EFI), xii, 9, 20, 41, 45, 55, 85, 140, 142 E-Money directive (EMD), xii, 79 EMV, 2, 26, 84, 87, 90, 108, 116, 132, 139, 171, 172, 194 Enabler, 20, 23, 36, 87 Encryption, 3, 14, 55, 59, 71, 87, 126, 162, 163, 173, 174, 192, 207 Enterprise architecture (EA), 87

227 Enterprise blockchain, 46, 88, 157, 163 Enterprise Ethereum alliance (EEA), xii, 80, 88 Enterprise resource planning (ERP), xiii, 81, 88 Environment, social and governance (ESG), 88 Eos, 7, 30, 64, 88, 140, 146, 162, 197, 201, 202 ERC-20, 1, 24, 30, 42, 77, 88, 89, 125, 141, 149, 174, 191, 193, 200, 202, 210 Escrow service, 89 Ether, 8, 25, 55, 89, 151, 193, 210 Ethereum, 1, 8, 24, 26, 28–30, 37, 40, 42, 44, 53, 58, 62, 63, 88, 89, 98, 99, 106, 108, 127, 140, 149, 156, 162, 171, 172, 174, 178, 180, 186, 190, 191, 194, 197, 198, 200–202, 210 Ethereum Classic, 89 Euro-on-ledger, 37, 89, 90 European banking authority (EBA), xii, 1, 15, 90 European central bank (ECB), xii, 18, 37, 85, 90, 164, 191, 196 European committee for banking standards (ECBS), 90 European payments initiative (EPI), 90 Exchange-traded fund (ETF), xiii, 90, 91 Exchange-traded product (ETP), xiii, 91 Expansion phase, 91 Extract transform load (ETL), xiii, 91

F Face recognition, 40, 91, 195 Face-to-face (F2F), xiii, 91 Federal financial supervisory authority (BaFin), xi, 11, 17, 18, 50, 90–93, 95 Fiat currency/fiat money, 92 Fiat gateway, 92 Financial inclusion, 92 Financial industry business ontology (FIBO), xiii, 92 Financial information eXchange (FIX), xiii, 93 Financial instrument global identifier (FIGI), xiii, 93 Financial intermediary, 53, 93 Financial Market Supervisory Authority (FINMA), 93 Financial service provider (FSP), 7, 62, 93, 94, 141, 142, 175 Financial transaction services (FinTS), xiii, 81, 83, 94, 108 Financial wellness, 94 Financing round, 94, 176, 203

228 Fintech, vii, viii, 1–4, 6, 8, 11, 13, 15–22, 32–35, 37–39, 41–45, 47, 48, 52, 55–59, 64–69, 71–73, 75, 76, 83, 87–96, 98, 101–103, 109, 112–116, 120, 124, 126, 127, 130, 132, 134, 138–140, 144, 151–157, 161, 164, 166, 168, 170, 171, 173–175, 177, 178, 180, 182, 185, 186, 197, 199, 200, 202, 204, 205, 207, 208, 210, 213 Fintech incubator, 95, 112 First-stage financing, 76, 95, 188 5G, 213 Flow of fees, 97 Flow of information, 97 Follower, 47, 97 Foreign exchange (FX), xiii, 20, 36, 97, 196 Forging, 97, 161 Fork, 6, 25, 26, 30, 89, 97–99, 105, 185, 191, 205 Four-corner model, 1, 2, 49, 70, 84, 98, 100, 116, 120, 132, 151, 172, 191, 192, 194, 195 42, 213 Framework, 12, 20, 22, 29, 30, 46, 49, 76, 81, 87, 95, 98, 107–109, 112, 116, 120, 134, 146, 156, 158, 165, 171, 172, 179, 186, 198, 199, 205 Front-end, 16, 23, 63, 75, 98, 104, 118, 179, 208 Front-office, 100, 130, 180 Full node, 100, 128 Fundraising, 100

G GAFA, 23, 100 Gamification, 101, 102 Gatekeeper, 101 Gateway, 101, 107, 139, 141, 163, 170, 190 General data protection regulation (GDPR), xiii, 91, 101 Generation, 31, 45, 60, 101, 102, 138, 146, 167, 210, 213 X, 101, 102 Y, 102 Z, 102 Genesis block, 28, 102, 103, 127 Gentleman agreement, 103, 156 Geo-IP, 75, 103 Geolocation, 103 Gesture control, 103 Global gateway, 103 Goal-based investment, 103

Index Gossip, 104, 106, 107 GovCoin, 104 Governance, 25, 35, 45, 54, 63, 104, 120, 202 Graphical user interface (GUI), 98, 104

H Hackathon, 72, 104, 105 Halving, 27, 28, 105 Hard fork, 25, 26, 98, 105 Hashed timelock contract (HTLC), 106 Hashgraph, 62, 104, 106, 107 Hash rate, 106, 107, 186 Hash tree, 105, 129 Hash value, 28, 41, 105, 140, 160, 161 Headend, 101, 107 Healthtech, 107 HedgeTrade, 107 High frequency trading (HFT), xiii, 6, 107 Hold on for dear life (HODL), xiii, 107 Holochain, 62, 106, 107 Home banking computer interface (HBCI), xiii, 94, 108 Host card emulation (HCE), xiii, 108, 132, 174 Hot storage, 41, 108 Howey test, 108 Huobi token, 108 Hyperledger, 28, 30, 98, 108, 109, 111, 157, 158, 160, 164, 186 Hyperscaling, 109

I Identity management, xiii, 15, 30, 64, 68, 71, 83, 111, 123, 154, 158, 175, 192 Identity verification, 15, 24, 40, 83, 111, 191 Immediate payment service (IMPS), xiii, 111 InCar, 111 Incremental, 112, 120 Incubator, 1, 95, 112, 165 Incumbent, 24, 35, 37, 49, 112, 115, 124, 143, 167, 178, 182, 186, 196, 197, 199 Industry 4.0 (I4.0), xiii, 72, 112, 118, 126 Influencer, 112 Information technology (IT), vii, xiii, 4, 6, 9, 13, 23, 32–34, 37–39, 42, 47, 55, 58, 64, 72–74, 77, 82, 83, 87, 95, 102, 104, 105, 108, 112–114, 120, 124, 140, 154, 171, 173, 177, 181, 196, 204, 205 Infrastructure-as-a-service (IaaS), 39, 113 Initial coin offering (ICO), xiii, 51, 113, 114 Initial exchange offering (IEO), xiii, 114 Initial public offering (IPO), xiii, 113, 174

Index Innovation, vii, 13, 21, 37, 57, 60, 65, 70, 72, 74, 95, 114, 120, 123, 127, 133, 146, 150, 165, 166, 187, 202, 203 Insourcing, 114, 186 Instant payment, 90, 115, 164 Insurance IT, 115 Insurtech, 112, 115, 132 Integrator, 35, 115, 116 Intelligent personal assistant (IPA), xiii, 115 Intelligent virtual assistant (IVA), xiii, 115, 116 Interchain, 106, 116, 118, 125 Interchange fee (IF), xiii, 116, 129 Intermediation, 7, 26, 29, 31, 32, 44, 50, 54, 55, 63, 74, 83, 93, 115, 116, 127, 151, 152 International bank account number (IBAN), 90, 116–118, 175, 176, 179, 200 International organization for standardization (ISO), xiii, 33, 116, 117, 120, 121, 162, 185, 188 International payment instruction (IPI), 117 International securities identification number (ISIN), xiii, 43, 73, 117, 174, 188, 200 International token identification number (ITIN), xiii, 117 Internet bubble, 117 Internet of things (IoT), xiii, 118, 138, 213 Internet of things Iota (IOTA), xiii, 118 Interoperability, 14, 30, 37, 46, 49, 53, 88, 116, 118, 120, 134, 156, 165, 178, 202 Intrachain, 118 Investtech, 120 ISO 20022, 73, 117, 118, 120, 121, 149, 179, 185, 196, 201 ISO/TC 307, 117, 120 Issuer, 2, 18, 24, 70, 83, 84, 98, 101, 107, 116, 120, 136, 141, 142, 149, 150, 157, 159, 170, 172, 192, 196, 197 Issuer identification number (IIN), xiii, 120, 157 Iterative, 72, 112, 120, 172

J JavaScript object notation (JSON), xiii, 122

K Kanban, 4, 112, 122 Key information documents (KID), xiii, 122 Key performance indicator (KPI), xiii, 47, 122, 123, 166 Know your customer (KYC), xiii, 111, 122, 123

229 Knowledge-based authentication (KBA), xiii, 123 Kodak trap, 72, 74, 123

L Late stage financing, 76, 123 Launch, 18, 52, 95, 124, 170, 187, 188 Lean startup, 124 Ledger, xvi, 44, 75, 124, 152, 153, 210 Legacy systems, 4, 124 Legitimation, 15, 124, 142, 203 Lending club, 125 Lending pool, 1, 125 Libra, 65, 66, 125 Lightning network, 26, 125, 141, 172 Liquidity, 1, 15, 48, 91, 125, 147, 157, 166, 167, 179, 201 Liquidity pool, 15, 63, 125 Litecoin, 106, 125 Loan-to-value (LTV), xiii, 126 Location-based service (LBS), xiii, 126

M Machine learning (ML), xiv, 126, 127 Machine-to-machine (M2M), xiii, 118, 126, 129 Machine-to-machine payment (M2M payment), 126 Magic, 127 Main-chain, 127, 165 Makers, 15, 58, 125, 127 Marketplace lending, 127 Markets in financial instruments directive (MiFID), xiv, 127 Mass customization (MC), xiii, 128 Master node, 28, 75, 128 Media break, 11, 82, 128 Mempool, 26, 128 Merchant service charge (MSC), xiv, 116, 129, 196 Merkle tree, 28, 105, 129 Message authentication code (MAC), 129, 190 Message queuing telemetry transport (MQTT), xiv, 129 Messaging commerce, 129 Metaverse, 14, 129, 205 Microfinance/microfinancing, 130 Micropayment, 130 Microservice, 130 Middle-office, 16, 130 Middleware, 118, 130, 131, 141

230 Miner, 27, 75, 105, 128, 131, 159, 161 Minimum viable product (MVP), 131 Mining, 7, 11, 17, 25, 28, 31, 32, 40, 64, 104, 125, 131, 147, 159–161, 183, 186–188, 191, 192, 195, 202 Mining pool, 131, 161 Mixed reality, 80, 131, 205 Mixing service, 131, 198 Mobile banking, 16, 24, 73, 132, 143, 165, 194, 199, 213 Mobile brokerage, 132 Mobile claims processing, 132 Mobile payment (m-payment), 7, 69, 85, 91, 108, 129, 130, 132, 133 Mobile wallet, 7, 132 Mobility services, 7, 178 Mock-up, 72, 133 Monero, 7, 133 Moneta, 133 Money laundering, 9, 19, 37, 54, 122, 132, 133, 157, 175 Mortgage comparison, 114, 134, 143 Multi-bank, 1, 2, 11, 56, 76, 81, 94, 108, 111, 123, 134, 143, 151, 153, 180, 199 Multi-chain, 49, 116, 134, 202 Multi-channel, 111, 141, 143 Multi-dealer platform (MDP), xiv, 135 Multi-home, 135 Multilateral interchange fee (MIF), xiv, 136 Multilateral trading facility (MTF), xiv, 8, 136 Multi-sided platform (MSP), xiv, 135 Multi-signature, 135 Multi-version concurrency control (MVCC), xiv, 136 Mutual distributed ledger (MDL), xiii, 136

N National electronic funds transfer (NEFT), xiv National securities identifying number (NSIN), 137, 138 Natural language processing (NLP), xiv, 4, 14, 137, 167 Near field communication (NFC), xiv, 137 Nem, 30, 137, 160 Neo, 138, 140, 162, 197 bank, 17, 34, 35, 37, 138, 162 insurance, 138, 175 Net present value (NPV), xiv, 122, 138, 139 Network effect, 10, 138, 139, 155 Network service provider (NSP), 139

Index New economy bubble, 139 No-code, 139 Node, 13, 25, 27, 28, 30, 37, 44, 45, 62, 64, 75, 104–107, 128, 139, 152, 157–161, 178, 179, 185, 188, 189, 202 Non-bank, 140, 152 Nonce, 28, 140, 161 Non-fungible token (NFT), xiv, 42, 55, 78, 140 Now generation, 140

O Objectives and key results (OKA), xiv, 140 Offline wallets, 141 Off-/on-chain, 46, 141 Off-us transaction, 39, 141 OKB, 141 Omni-channel, 20, 56, 111, 135, 141, 143, 156, 186, 213 Onboarding, 15, 142, 203 Once-only principle, 142 One-click checkout, 142, 195 One-time password (OTP), xiv, 143, 198 Online banking, 2, 17, 68, 73, 80, 81, 100, 132, 134, 143, 144, 164, 175, 182, 209 Online credit application, 143 Online-to-offline (O2O), xiv, 143 Online transaction processing (OLTP), xiv, 144 On-premise, 12, 39, 142, 185 On-us transaction, 142 Open API, 144, 145 Open banking, 9–11, 20–23, 30, 35, 36, 46, 56, 63, 73, 80, 118, 130, 142, 144, 146, 155, 177, 197, 199, 200 Open data, 146 Open innovation, 146 Open insurance, 146 Open source, 26, 30, 37, 88, 89, 91, 97, 98, 106, 108, 109, 125, 146, 149, 166, 185, 188, 191, 196 Operating system (OS), xiv, 79, 98, 101, 146, 154 Opt-in, 23, 77, 126, 144, 147, 153, 154, 183 Opt-out, 147 Oracle, 29, 37, 91, 109, 147, 148 Order book, 16, 58, 63, 74, 84, 125, 147, 210 Orphan block, 147 Outsourcing, 9, 35, 36, 114, 142, 147, 148, 166, 177, 179, 186, 192, 196, 205 Overlays, 148 Over-the-counter (OTC), xiv, 8, 84, 148, 196

Index P Para-chain, 148, 165 Paxos Standard, 149 Pay-as-you-drive (PAYD), xiv, 149 Pay-as-you-use (PAYU), xiv, 40, 62, 74, 103, 148, 149, 154, 181 Payment card industry (PCI), xiv, 149, 154 Payment initiation message (PAIN), 149 Payment initiation service (PIS), 1, 149 Payment initiation service provider (PISP), xiv, 150 Payment service, 1–3, 9, 15, 25, 52, 62, 69, 92, 132, 149–151, 154, 182, 184, 192 Payment service provider (PSP), xiv, 108, 150 Payment services directive 2 (PSD2), xiv, 1, 2, 11, 76, 146, 149–151, 153, 165 Payment services supervision act (ZAG), 79, 92, 150, 151 Payment system, 7, 27, 48, 66, 85, 90, 97, 98, 120, 132, 143, 151, 156, 172 Payment token, 40, 50, 151, 193 Paytech, 95, 151 Peer-to-peer (P2P), xiv, 14, 26, 28, 44, 59, 63, 80, 88, 91, 151 insurance, 42, 50, 152 lending, 50, 152 payments, 132, 152 Permanode, 152 Permissioned blockchain, 29, 66, 88, 98, 109, 152, 153, 156, 158, 160, 162, 210 Personal assistant, 70, 72, 153 Personal finance management (PFM), xiv, 2, 32, 59, 91, 134, 143, 151, 153, 175, 180 Personal information management system (PIMS), xiv, 153 Personalization, 42, 55, 59, 62, 80, 128, 153, 154, 156, 190 Pervasive computing, 9, 154, 198, 213 PIN on glass, 149, 154 Pivot, 124, 154 Platform, 3, 7–10, 12, 16, 24, 30, 46, 48, 50–52, 54, 56, 58, 63, 69–71, 79, 80, 82–84, 87, 97, 101, 104, 108, 109, 113, 118, 127, 129, 130, 135, 136, 139, 144, 148, 152–155, 158, 166, 168, 171, 173, 175, 177–179, 182, 183, 191, 196–198, 202 Platform-as-a-service (PaaS), 39, 155 Platform banking, 9, 11, 20, 22, 80, 144, 155 Point of contact (PoC), 114, 155, 179 Point of interaction (PoI), 156, 195 Point of purchase (PoP), xiv, 156 Point of sale (PoS), xiv, 2, 69, 97, 126, 129, 132, 137, 139, 143, 156

231 Point of sales selection (PoSS), xiv, 156 Polkadot, 26, 37, 49, 134, 148, 156, 161, 165, 178 Portfolio optimization, 94, 156, 167 Practical byzantine fault tolerance (PBFT), xiv, 157 Prediction market, 157 Primary account number (PAN)/Payment card number, 157 Privacy coin, 58, 157 Private blockchain, 28, 45, 157, 158, 189 Private key, 14, 26, 55, 71, 87, 129, 158, 162, 175, 192 Private lending, 158 Process automation, 11, 158, 167, 172 Process mining, 159, 180 Processor, 70, 101, 118, 132, 159 Proof-of-activity (PoA), xiv, 159 Proof-of-authority (PoA), 159 Proof-of-burn (PoB), xiv, 41, 45, 159 Proof-of-capacity (PoC), xiv, 160 Proof-of-concept (PoC), xiv, 72, 160 Proof-of-elapsed time (PoET), xiv, 160 Proof-of-importance (PoI), xiv, 160 Proof-of-object (PoO), xiv, 160 Proof-of-reserve (PoR), xiv, 160 Proof-of-stake (PoS), xiv, 11, 17, 36, 45, 59, 64, 138, 156, 159–161, 187, 198, 202 Proof-of-work (PoW), xiv, 28, 45, 161, 187 Proptech, 45, 95, 161 Protocol, xvi, 26, 28, 37, 63, 77, 94, 105, 106, 118, 129, 161, 162, 166, 173, 186, 188, 191, 193, 208, 210, 213 Pseudonymization, 58, 157, 162 Public blockchain, 29, 152, 157, 162, 189 Public key, 14, 26, 27, 87, 158, 162 Pure digital insurer (PDI), xiv, 162

Q Quantum computing (QC), xiv, 162, 163 Quick response code (QR code), xv, 163

R R3, 29, 45, 109, 157, 163 Radio frequency identification (RFID), xv, 137, 156, 163 Real-time credit transfer payments (RTP), 149, 163, 164 Real-time gross settlement system (RTGS), xv, 164, 196

232 Real-time processing, 11, 15, 22, 45, 73, 112, 126, 144, 147, 149, 164, 167, 168, 191, 204, 213 Rebundling, 164, 199 Reference model, 19, 164, 165 Regtech, 9, 43, 95, 163, 165 Regulatory sandbox, 165, 171 Relay chain, 148, 156, 165 Remote payment, 165 Remote procedure call (RPC), xv, 165 Representational state transfer (REST), xv, 144, 165 Research online, purchase offline (RePo), xv, 166 Retained organization (RO), xv, 166 Return on investment (ROI), xv, 50, 122, 166 Return on product development expense (RoPDE), xv, 166 Ripple, 8, 15, 30, 49, 70, 104, 157, 164, 166, 167, 180, 200, 210 Robo advisor, 167 Robo advisory, 5, 6, 17, 44, 47, 67, 68, 92, 103, 116, 120, 153, 167, 168, 170, 174, 199, 207, 209 Robot, 5, 31, 38, 97, 158, 167, 168, 170 Robotic desktop automation (RDA), xv, 168 Robotic process automation (RPA), xv, 40, 158, 167–170, 172 Robotics, 5, 167, 168 Robotization, 170 Roll-out, 60, 170 Rootchain, 170 Routing, 170, 202 RSA, 3, 14, 81, 85, 94, 170

S Salting, 171 Sandbox, 1, 165, 171 Scalability, 37, 74, 89, 106, 118, 148, 171, 172, 178, 187, 205 Scaled agile framework (SAFe), xv, 5, 172, 188 Scheme, 24, 26, 36, 49, 84, 90, 98, 139, 150, 152, 172, 191, 210 Screen scraping, 168, 172 Scrum, 4, 42, 60, 65, 72, 105, 112, 120, 172, 173 Search engine optimization (SEO), xv, 173 Second-stage financing, 76, 173 Secure code, 173 Secure electronic transaction (SET), 173, 174 Secure element, 174 Securities identification number (WKN), xvi, 137, 138, 174, 209

Index Security token offering (STO), xv, 174 Seed, 32, 76, 94, 174, 187, 188 Self-advisory, 128, 174, 175 Self-hosted wallet, 175 Self-service, 16, 175 Self-sovereign identity (SSI), xv, 175 Sentiment analysis, 4, 40, 56, 57, 137, 175, 183, 195, 206 SEPA credit transfer (SCT), 175, 176, 179 SEPA direct debit (SDD), 120, 175, 179 SEPA payment, 176 Series A, 94, 176, 192 Series B, 176 Series C, 176 Series D, 176 Series E/F, 176 Service, vii, xiv, 1–3, 5, 7–11, 13, 15–18, 20–24, 31, 34–39, 41–44, 46, 47, 49–60, 62, 63, 67–76, 80–85, 87–89, 91–95, 97, 98, 100–103, 108, 109, 111–116, 118, 120, 122–126, 128–131, 133, 135, 139, 140, 142–144, 146–159, 162, 165–167, 170, 171, 173–175, 177–186, 189–196, 198, 199, 202, 204, 207–209, 213 Service desk, 166, 177 Service level agreement (SLA), xv, 177 Service-oriented architecture (SOA), xv, 177, 199 Sharding, 30, 148, 178 Sharing economy, 40–42, 60, 71, 72, 85, 118, 149, 152, 161, 178, 181 Sidechain, 178, 198 Single bottom line, 179, 182 Single dealer platform (SDP), xv, 179 Single European payments rea (SEPA), xv, 117, 120, 164, 175, 176, 179, 191 Single point of contact (SPoC), xv, 155, 166, 177, 179 Single point of failure (SPoF), 179 Single point of truth (SPoT), xv, 44, 179 Single sign-on (SSO), xv, 180, 184 Small and medium-sized enterprise (SME), xv, 180 Small Data, 180 Smart contract, 16, 51, 63, 75, 77, 88, 113, 114, 125, 147, 149, 180, 181, 186, 187, 194, 200 Smartphone bank, 11, 12, 17, 19, 38, 122, 182, 204 Smart process, 181, 185 Smart product, 3, 59, 60, 181, 185

Index Smart service, 3, 9, 34, 59, 60, 62, 72, 80, 115, 118, 133, 181, 182 Social banking, 102, 143, 182 Social CRM, 52, 97, 101, 129, 182, 183, 192, 195 Social data, 6, 8, 183 Social lending, 183 Social login, 184 Social media payments, 183, 184 Social trading, 107, 182–184 Social validation, 184 Social verification, 184 Society for worldwide interbank financial telecommunication (SWIFT), 22, 26, 33, 49, 63, 73, 185, 196, 197, 199, 201 Soft fork, 98, 185 Software-as-a-service (SaaS), xv, 29, 39, 185 Software-defined business, 185 Software-defined networking (SDN), xv, 186 Software development kit (SDK), xv, 46, 65, 186 Solidity, 75, 180, 186 Solo mining, 186 Sourcing, 9, 16, 35, 41, 52, 114, 118, 142, 144, 147, 162, 177, 186, 199 Special purpose acquisition company (SPAC), xv, 187 Stable coin, 50, 58, 66, 127, 149, 187, 188, 191, 202 Staking, 187 Staking coin, 187 Startup, vii, 1, 17, 19–21, 31, 32, 34, 39, 40, 42, 46, 48, 50, 55, 65, 66, 68, 69, 71, 72, 77, 79, 85, 91, 94, 95, 102, 107, 109, 112, 114, 115, 122, 124, 130, 133, 136, 138, 140, 157, 160, 165, 166, 170, 173, 176, 184, 186, 187, 191, 192, 199, 200, 203, 211, 213 financing, 76, 79, 188 phase, 34, 154, 165, 188 Stellar, 157, 188 Stellar consensus protocol (SCP), xv, 188 Stock exchange daily official list (SEDOL), 188, 200 Store of value (SoV), xv, 188 Straight through processing (STP), xv, 189 Strong customer authentication (SCA), xv, 189 Sub-chain, 170, 189 Super peer, 189 Sweet equity, 189 Swiss interbank clearing (SIC), xv, 15, 190 Switch/switching, 135, 161, 190 Symmetric encryption, 3, 14, 87, 129, 190 Synthetix, 64, 190

233 T Tablet advisory, 190 Tangle, 74, 118, 190 TARGET instant payment settlement service (TIPS), xv, 191 Technical acceptance provider (TAP), xv, 191 Tendermint, 46, 191 Tether, 26, 58, 191 Tezos, 17, 28, 30, 191 Theta, 191 Thin file, 191, 192 Third-party issuer (TPI), xv, 192 Third-party payment service providers (TPPSP), xv, 192, 202 Third-party provider (TPP), xv, 192 Third stage financing, 76, 192 3-D Secure, 174, 213 Three-corner model, 172, 192, 193 Token, 1, 15, 16, 24, 28, 30, 37, 40–42, 49–51, 53–55, 64, 67, 77, 88, 89, 98, 108, 113, 114, 117, 125, 140, 141, 143, 147, 149, 151, 160, 174, 175, 178, 186–188, 191–195, 198, 200–202, 210 economy, 49, 193 launch, 194 Token generating event (TGE), xv, 194 Tokenization, 28, 30, 37, 53, 54, 67, 174, 191, 193–195 Token purchase agreement (TPA), xv, 194 Token service provider (TSP), xvi, 194, 195, 202 Total cost of ownership (TCO), xv, 195, 196 Trader commission, 196 Trading platform, xi, 8, 9, 58, 108, 116, 132, 196 Transaction bank, 36, 114, 196, 199 Transaction-based directed acyclic graph (TDAG), xv, 74, 196 Transaction costs, 82, 83, 93, 118, 144, 148, 195–197, 201 Transaction flow, 97, 197 Transactions per second (TPS), xvi, 106, 171, 178, 197 Trans-European automated real-time gross settlement system (TARGET), xv, 4, 11, 15, 35, 52, 58, 60, 90, 103, 138, 156, 164, 196 Tron, 28, 140, 193, 198, 202 Trusted execution environment (TEE), xv, 198 Trusted third party (TTP), 161, 192, 198 Tumbler, 198 Two-factor authentication (2FA), xi, 198 Two-way peg, 198

234 U Ubiquitous computing, 198 Unbanked, 199 Unbundling, 35, 164, 199 Underbanked, 199 Underwriting, 115, 199 Unicorn, 40, 180, 200 Unified Resource Identifier (URI), 199, 200 Unique identifier (UID), xvi, 200 Uniswap, 1, 63, 64, 125, 200 Universal financial industry message scheme (UNIFI), xvi, 201 Unspent transaction output (UTXO), 201 Unus Sed Leo, 201 USD Coin, 26, 134, 160, 202 User experience (UX), xvi, 202 Utility token, 50, 108, 174, 191, 193, 202

V Validator, 49, 191, 198, 202 Value-added service (VAS), xvi, 202 VeChain, 159, 202 Venture, 17, 32, 95, 203 Venture capital (VC), xvi, 40, 76, 112, 173, 174, 176, 188, 192, 200, 203, 211 Venture capital financing, 174, 203 Venture capitalist, 48, 187, 203, 211 Venture client, 203 Verifiable Credentials, 203 Video authentication, 203 Video ID procedure, 191, 203, 204 Virtual assistant, 72, 115, 168, 204 Virtual currency, 25, 29, 37, 55, 68, 84, 85, 89, 90, 113, 184, 188, 199, 202, 204, 205

Index Virtualization, 12, 30, 113, 165, 186, 205, 209 Virtual reality (VR), 37, 205 Voice recognition, 14, 206

W Walled garden, 207 Wallet, 7, 26, 51, 52, 55, 56, 66, 75, 85, 90, 91, 98, 108, 141, 147, 152, 157, 174, 175, 187, 194, 207, 209, 210 Wallet Import Format (WIF), xvi, 207 Wealthtech, 95, 103, 168, 207 Wearable, 14, 146, 208 Web service, 21, 24, 39, 109, 130, 154, 165, 177, 208 WeChat, 7, 129, 132, 143, 209 Wertpapierkennnummer (WKN), 174, 209 White label, 209 Wisdom of crowds (WoC), xvi, 209 Wrapped Bitcoin (WBTC), 210 Wrapped Ether (WETH), xvi, 210

X Xetra, 91, 210 XRP, xvi, 7, 26, 45, 167, 210

Z ZCash, 157, 210 Zerocoin, 148, 157, 210, 211 Zero-knowlege proof (ZKP), xvi, 210 Zombie bank, 211 Zombie loan, 211 Zombie startup, 211