Volume 8 (2023-24)

Each volume of Journal of Digital Banking consists of four 100-page issues. Articles published in Volume 8 are listed below.

Volume 8 Number 4

Editorial
Simon Beckett, Publisher
Practice Papers
Strategies for commercialising open banking: Approaches from around the globe
Shruti Awasthi, Director, Open Banking Strategy; Co-chair, International Professionals Network, CIBC

Open banking is revolutionising the financial industry by opening up new avenues for collaboration, innovation and customer-centricity. This paper delves into the ways in which client-focused open banking can be commercialised and monetised, leveraging industry statistics and global examples. By examining strategies such as application programming interface (API) monetisation, value-added services, platform-based models and partnership ecosystems, the paper provides valuable insights for stakeholders looking to capitalise on the commercial potential of open banking. Furthermore, it explores the dynamic landscape of open banking adoption worldwide, offering a comprehensive view of the opportunities and challenges faced in different regions and how modern technological advances like artificial intelligence and Blockchain have the potential to add to the value and offerings open banking provides to financial institutions to provide consumers with a superior experience.
Keywords: open banking; API strategy; platform banking; partnership ecosystems; data-driven insights; advanced analytics
Secrets to successful bank and FinTech partnerships for credit and deposits
Rebecca Bacon, VP Head of Financial Institutions, Upgrade

This paper aims to provide a road map to a successful long-term partnership between traditional financial institutions (FIs) like banks and credit unions with a financial technology (FinTech) platform. This is a summary of lessons learned from developing and launching over 200 bank/credit union partnerships with a FinTech lending platform. Drawing on experience with financial institutions of all shapes and sizes, this paper details best practices to create a scalable way of providing custom solutions to the problems faced by the modern depository institution. This includes a particular focus on lending/ credit products, and how the effect of FI and FinTech lending programmes can add value while mitigating risk. The paper focuses on depositories domiciled in the USA and the American banking system’s regulatory environment, but many of its themes will be applicable to international organisations.
Keywords: FinTech/bank partnerships; digital lending; FinTech; neo-banks; deposits; liquidity solutions
Compliance redefined: Using GenAI to navigate a complex regulatory landscape with reduced risks and costs
Irene Liu, Managing Director and Michael Wongsosaputro, Consultant, Digital Finance, Risk, Regulatory and Compliance (South East Asia), Accenture

In recent times, generative artificial intelligence (GenAI) has emerged as the next frontier in artificial intelligence (AI) capabilities. With its ability to create original content from training data sets, it is expected to significantly influence the way we work. A number of banks have already started experimenting with GenAI on use cases ranging from content creation and personalised customer marketing to fraud and financial crime detection. Yet as rapidly as technologies such as GenAI have arisen, so have the regulatory demands faced by the financial services sector, which have become more complex and voluminous in the face of increasing types of risks. Financial institutions are seeking ways to achieve efficiency gains from their reporting processes to combat such risks and the rising costs of reporting. This paper proposes that GenAI is a potential answer to financial institutions’ quandary. The recommendations proposed support the notion that GenAI is able to help financial institutions reap cost savings and resolve some of the common challenges of regulatory reporting, such as data quality. Furthermore, GenAI could also transform regulatory reporting as we know it, through its visualisation capabilities and real-time monitoring. The paper concludes with a view of industry initiatives on GenAI and regulatory reporting and considerations for moving the landscape forward.
Keywords: Generative AI; GenAI; regulatory reporting; compliance; RegTech; technology; artificial intelligence; data and analytics; data quality
Expanding the horizons of FinTech: A comprehensive geographical analysis of expansion in Europe and beyond
Axel Cateland, CEO, Kulipa

The financial technology (FinTech) industry has experienced an unprecedented surge in growth over the past decade, reshaping the financial services landscape worldwide. This paper examines the multifaceted geographical expansion of FinTech, with a specific focus on Europe as the initial launching point and an in-depth exploration of global prospects. By delving into the fundamental catalysts, intricate challenges and nuanced strategies for expansion, this offers insights into the dynamic evolution of FinTech across diverse geographical regions.
Keywords: FinTech; financial services; Europe; geographical evolution; global expansion; regulatory compliance; consumer needs
Why open data and compliance will drive open banking and the role AI will play
Abhinav Desai, Head of Sales, EMEA, Pelican AI

This paper discusses the latest approaches in intelligent payments, data enrichment and compliance that would drive open banking into a viable platform for consumers and businesses alike — for making payments instantly, making credit decisions with less risk and at greater speed and hyper-personalising customers to offer uniquely targeted solutions. The paper further lays out the premise that open banking is a stepping stone to open finance — an extension of open banking, which allows consumers to share their financial data to include a wider range of financial products and services, such as investments, insurance and pensions. This means that consumers will have more control over their financial data and be able to use it to access better products and services from a wider range of providers. This is then a dynamic ever-evolving place that will constantly innovate. Open banking will bring out exciting new use cases that challenge the norm and bring to life new ways of doing things cheaper, faster and safer.
Keywords: AI; intelligent payments; open data; compliance; open banking; credit decisions; hyper-personalisation; open finance
Ensuring operational resilience in Japan: The rise of new regulations and their implications
Eiichiro Yanagawa, Senior Analyst, Financial Services, Celent

In 2022, regulators around the world began to take steps to instil greater operational resilience throughout the financial services sector to deal with unforeseen systemic risks. Regulations vary from region to region, but they all mandate an integrated risk management approach that combines multiple aspects of operational risk into a single framework, identifies crucial business services and identifies how to respond in the face of a system failure with enterprise-wide agreement. Financial institutions need urgent and significant assistance in transforming their risk capabilities, as many regulators are calling for enhanced processes and systems by 2025. Many financial institutions are realising that a higher level of collaboration is needed across the enterprise to meet regulatory requirements. Financial institutions need to improve both enterprise-level visibility into risk and compliance activities and enterprise-level crisis response capabilities. This paper analyses the latest developments and provides implications through its primary research in the Japanese market.
Keywords: operational resilience; OR; enterprise risk management; ERM; integrated risk management; IRM; risk management; operational risk; business continuity
Case study
The role of bank–FinTech partnerships in creating a more inclusive banking system
Alan Chernoff and Julapa Jagtiani, Senior Economic Adviser and Economist, Federal Reserve Bank of Philadelphia

FinTech firms are often viewed as competing with banks. Instead, more recently, there has been increased partnership and collaboration between FinTech firms and banks. These partnerships have allowed banks to access more information on consumers through data aggregation, artificial intelligence/machine learning (AI/ML) and other tools. This paper explores explore the demographics of consumers targeted by banks that have entered into such partnerships. Specifically, the paper tests whether banks are more likely to extend credit offers (by mail) and/or credit originations to consumers who would have otherwise been deemed high risk, either because of low credit scores or lack of credit scores altogether. The paper uses data on credit offers based on a survey conducted by Mintel, as well as data on credit originations based on the Federal Reserve’s Y-14M reports. Additionally, the paper analyses a unique data set of partnerships between FinTech firms and banks compiled by CB Insights to identify the relevant partnerships. The paper concludes that banks are more likely to offer credit cards and personal loans (and grant larger credit limits) to the credit-invisible and below-prime consumers after the FinTech partnership period. Similarly, it finds that FinTech partnerships result in banks being more likely to originate mortgage loans (and grant larger loan amount) to nonprime homebuyers. Overall, the paper concludes that bank/FinTech partnerships could help to move towards a more inclusive financial system.
Keywords: FinTech; alternative data; FinTech partnership; financial inclusion; credit invisible

Volume 8 Number 3

Editorial
Simon Beckett, Publisher
Practice Papers
Hyper-personalisation: Inducing behaviours through data — how machine learning and automation can help customers make valuable and informed decisions
Luís Coelho and Gonçalo Cachola, Celfocus

While personalisation is not an entirely new topic, there is currently massive hype around it. This is because service providers realise that they need to be more cost-effective in engaging with their customers, and also because customers now demand to be treated individually and in a personalised way. Several market trends have been adopted in recent years, bringing service providers to the level where they currently stand. The previous trends were both beneficial and applicable in a particular context; however, today, new approaches are required for service providers to progress, improve and move to the next level. Achieving a hyper degree of personalisation can be challenging — it requires investment, time and the right strategy. Furthermore, it is not a straightforward path, and it is essential to understand the business and technical challenges that service providers must address and overcome to succeed — challenges for which hyper-personalisation is the answer. This paper explores the concept of hyper-personalisation and its potential to induce customer behaviour through datadriven insights. It highlights the importance of knowing customers and leveraging their preferences and habits to deliver valuable and informed decisions. The financial services industry has the significant advantage of having access to a huge installed customer base and its data. In general, it is not a problem of lack of data that these industries face but rather one of how to derive actionable insights from it. The hyper-personalisation approach is bridging data with cognitive and digital capabilities to deliver unique, in-context and highly relevant experiences. With hyper-personalisation, service providers can scale up the personalisation leveraged by artificial intelligence (AI) and machine learning (ML) to deliver experiences and recommendations in real time to individuals, creating a true one-to-one personalisation.
Keywords: hyper-personalisation; data; advanced analytics; banking
Data strategy in connected business models
Christoph Berentzen, Commerzbank and Benjamin Schaefer, Business Engineering Institute

In today’s business environment, data and data strategies are crucial in developing customer-centric business models. The emergence of platforms and ecosystems, in particular, is driving the significance of data as a vast amount of it is generated in such organisational settings that participating corporates can leverage to ensure the viability of their future business models.1 In this context, standardised data management and interfaces are becoming vital to guarantee necessary collaborative readiness and enhanced customer-centric business models. As data volume grows, corporations and financial institutions utilise application programming interfaces (APIs) to access internal and external data sources. However, they face challenges that must be addressed. To succeed, corporates and financial institutions must establish adequate data strategies with state-of-the-art data management based on internal and external data sources that serve their long-term corporate strategy. This paper outlines two essential data strategies: defensive and offensive strategies, along with selected use cases from various industries, highlighting the opportunities and challenges faced by corporates and financial institutions.
Keywords: data; data strategy; IoT; ecosystems; open banking API
Unmet payment needs and a central bank digital currency
Christopher S. Henry, Bank of Canada et al

This paper analyses the payment habits of Canadians both in the current payment environment and in a hypothetical cashless environment. The paper also considers whether a central bank digital currency (CBDC) would address unmet payment needs in a cashless society. Most adult Canadians do not experience gaps in their access to a range of payment methods, and this would probably continue to be the case in a cashless environment. Some people could, however, face difficulties making payments if merchants no longer generally accepted cash as a method of payment. For a payment-oriented CBDC to successfully address unmet payment needs, the main consumer groups — who already have access to a range of payment options — would have to widely adopt the CBDC and use it at scale. This is necessary to encourage widespread merchant acceptance of CBDC, which would, in turn, encourage further consumer adoption and use. Most consumers, however, face few payment gaps or frictions and therefore might have relatively weak incentives to adopt and — especially — to use CBDC at scale. If that were the case, widespread merchant acceptance would also be unlikely. This suggests that addressing unmet payment needs for a minority of consumers by issuing a CBDC could be challenging under the conditions explored in this paper. The minority of consumers with unmet payment needs will only be able to benefit from a CBDC if the majority of consumers experience material benefits and therefore drive its use. Adoption by the majority may have added policy implications that are beyond the scope of this paper.
Keywords: bank notes; central bank research; digital currencies and FinTech; financial services
How to use AI to shape efficient digital and omnichannel experiences
Jeremy O’Niel, HAPO Community Credit Union

This paper delves into the growing significance of artificial intelligence (AI) in transforming financial services and improving customer experience. Using AI, financial institutions can elevate their omnichannel approach, ensuring a seamless and personalised customer journey across a diverse set of interactions. AI has the potential to forecast financial behaviours, assist in prudent financial management, and provide predictive solutions to pre-empt issues such as overdrafts or late payments. The analysis emphasises the essence of service in the financial sector, advocating for AI-powered tools, like conversational chatbots, advanced fraud protection capabilities, as well as financial education and personalisation. By leveraging natural language processing and machine learning, these tools not only react to customer queries but also proactively engage, ensuring enhanced customer service in line with evolving expectations. AI’s capabilities in creating personalised customer experiences through dynamic visual and audio content point to a more tailored future for customer journeys. The challenge, however, remains in balancing AI with the human touch. For organisations, it is pivotal to start small with AI and omnichannel experiences, prioritising incremental changes that bring immediate value.
Keywords: artificial intelligence; AI; omnichannel; personalisation; chatbots; customer/member journey
New skills in an AI world in finance
Tram Anh Nguyen, CFTE

The financial industry has undergone a transformation over the last 10 years, with FinTech now being worth more than a third of banking, and five of the top 10 financial services are now digital-based businesses. Nowadays, an increasing number of AI technologies, notably the Large Language Models (LLMs) like ChatGPT, are accelerating the disruption in the industry. The industry has changed, and the skills required in today’s landscape are different from the ones needed previously, resulting in a widening knowledge gap. This paper maintains that skills in an AI-powered world in finance are not confined to hard skills alone, but also encompass soft skills, industry knowledge, mindset and experience. The paper provides a long-term solution for the industry to acquire up-to-date skills and build a more resilient ecosystem in finance.
Keywords: skills; finance; FinTech; AI; education; lifelong learning
Personalisation as a strategy for reversing traditional banks’ market share erosion in primary financial relationships and how to get started
Katie Pagenkopf, Stellar Elements

From primary research conducted in 2022, customers said, ‘What personalisation?’ when asked if they received digital experiences or communications from their bank that seemed tailored to their unique account history. Although the concept of personalisation was described as early as 19891 and is effectively deployed in other industries (eg advertising, e-commerce, video streaming), customers report that their bank does not use customer knowledge to proactively anticipate their needs or wants. Enter FinTechs. Thanks to technology advancements, an entire subindustry within financial services has bloomed that provides banking services, including deposit accounts, lending and wealth management. For the first time, customers now have a choice outside traditional institutions for managing their money. This paper argues that effective deployment of personalisation is an experience that customers are looking for and that it can be deployed to help mitigate the market erosion of primary financial relationship (PFR) to FinTechs. The paper describes what we learned from customers and propose a framework that banks can use to deploy personalisation experiences that are minimally viable.
Keywords: personalisation; customer experience; customer mindsets; qualitative research; primary financial relationship
Case study
Operationalising ethics for AI in the financial industry: Insights from the Volksbank case study
Joris Krijger, Erasmus School of Philosophy, Erasmus University Rotterdam, Ethics and De Volksbank

This paper seeks to advance the development of responsible artificial intelligence (AI) practices within the banking industry through an in-depth case study analysis of De Volksbank’s governance framework for AI ethics. While the financial sector has historically embraced technological innovation, the increasing integration of AI into customer - and operations-focused systems has raised ethical concerns. Despite regulatory initiatives and the broad availability of ethical frameworks for responsible AI, numerous challenges related to operationalising these frameworks persist. Addressing the existing gap between ethical principles and AI practices in finance, this paper examines De Volksbank’s ethical governance framework as a potential organisational configuration of structures and processes necessary to meaningfully operationalise AI ethics. The paper provides a comprehensive overview of De Volksbank’s governance framework, detailing its requirements, roles and responsibilities across various dimensions of AI ethics governance. Additionally, it elaborates on four important insights of operationalising ethics, focusing on AI ethics as a challenge in (1) organisational design, (2) interdisciplinary expertise and responsibilities, (3) proactive governance and (4) high-quality processes for ethical inquiry. Given the indispensability of trust for the financial sector, trustworthy AI is of crucial importance for its long-term legitimacy and existence. Consequently, this paper seeks to enhance the understanding of operationalising AI ethics in banking and to serve as an impetus for other organisations aspiring to establish ethical frameworks for their AI systems.
Keywords: AI ethics; technology adoption; banking; ethics operationalisation

Volume 8 Number 2

Editorial
Simon Beckett, Publisher
The next digital inflection point for US banks
Michael Carter, Finalytics.ai

This paper explores the effect of technology on the American banking landscape in the 21st century. The number of US banks and bank branches has been consistently decreasing in this century, partly owing to technological advances. Existing legacy delivery channels, however, have slowed the rate at which banks in the United States have adopted and deployed the technology available to them. This slower rate of innovation by US banks has resulted in a level of consumer dissatisfaction that has created opportunities in the banking sector for FinTechs and Big Techs, especially since 2009.
Keywords: engaged banking; hyper-personalisation; AI; journey orchestration; datadriven digital; banks
Generative artificial intelligence and large language models for digital banking: First outlook and perspectives
Jean-Pierre Sleiman, N26 Operations

After several years of steady progress, the Generative artificial intelligence (AI) and large language models (LLMs, their applications to text) fields have accelerated tremendously since the end of 2022 and the public launch of ChatGPT. This is due to record-breaking model sizes and performances in the last couple of months, triggering unprecedented adoption curves from end users across the world. Even though regulators reacted fast, sharing their first recommendations, auditing emerging players, amending their AI regulation drafts or launching dedicated working groups, these efforts will require several months or years to come to fruition. There are multiple reasons for this. LLMs are complex technological objects made of gigantic foundational models trained on enormous quantities of texts, coupled with dedicated interfaces and action agents. They present a huge potential to perform high varieties of tasks with very high quality but also important risks in terms of costs, content accuracy, transparency, data privacy, security and ethics. Finally, the current ecosystem of stakeholders is very dynamic but also immature. In this uncertain context, the digital banking industry has been reacting ambivalently, with major players banning employee access to ChatGPT and publicly communicating on new LLM initiatives at the same time. This can be explained by the huge potential offered by these technologies to transform their business, coupled with many open questions in terms of technological set-up, usage, compliance and profitability. As these technologies seem to be too transformative for the industry incumbents to just wait and see, they should start creating the right conditions to learn how to use them, by identifying relevant use cases, choosing adapted and simple solutions, designing relevant user experiences, building the right teams, environment, data sets and operating model, and actively engaging in regulatory conversations.
Keywords: artificial intelligence; AI; Generative AI; large language models; LLMs; machine learning; digital banking; innovation
Effective risk management for financial institutions’ partnerships with FinTechs
Meredith F. Piotti, Wolf & Company

The aim of this paper is to provide insights into the regulatory concerns and challenges faced by financial institutions when partnering with FinTech companies. The paper highlights the recent consent orders issued against well-known financial institutions for their FinTech relationships and risk management programme shortcomings, as well as how financial institution and FinTech collaboration can overcome these shortcomings. It acknowledges the frustration caused by the limited guidance provided by regulators on incorporating FinTech into financial institution operations. However, it encourages financial institutions to learn from the published consent orders and improve their risk management programmes. The paper also discusses the factors that need to be considered in FinTech partnerships, such as overborrowing, bias and discrimination in algorithms, and data privacy and reliability. It emphasises the importance of compliance professionals in analysing regulatory considerations early and creatively to meet future demands. Furthermore, the paper explores the changing landscape and increasing reliance on technology, highlighting areas that need to be considered in financial institution risk management programmes. It addresses concerns related to alternative credit models, bias and discrimination in algorithms, and data privacy and reliability. Overall, readers can expect to gain knowledge and insights into the regulatory concerns and challenges associated with FinTech partnerships, as well as practical actions and considerations to mitigate risks and ensure compliance.
Keywords: FinTech partnership; digital transformation; regulatory compliance; third-party risk management
What is the hype about hyper-personalisation? A three-dimensional view to implementation
Mirella Reznic, Valley Strong Credit Union

The banking landscape has been transformed by rapid advancement of digital technology, enabling financial institutions to reach their customers through multiple channels seamlessly. Omnichannel banking has become the new norm, allowing customers to access banking services across mobile devices, websites, ATMs and branches. As customer expectations continue to evolve, however, banks and credit unions must go beyond offering multiple channels and focus on delivering hyper-personalised experiences seamlessly between these channels. In this paper, we will explore three dimensions of this journey: (1) the customer experience, (2) data readiness and (3) humanistic artificial intelligence (AI).
Keywords: hyper-personalisation; artificial intelligence; customer experience; customer journey; predictive analytics; machine learning; humanistic AI
Where are the customers’ bots? The AI paradigm shift in retail banking
David G.W. Birch, 15Mb and Kirsty Rutter, Lloyds Banking Group

Financial institutions are already using artificial intelligence (AI) to cut costs and deliver new services. Robo-advisers, chatbots and ‘copbots’ auto-detecting fraudulent transactions are increasingly common. These uses are undoubtedly valuable, but the business model is still the consumers being sold a financial product by a bank, whether by a call centre agent or a robot that impersonates a mortgage vendor. The big change in financial services will come when customers use AI to assess offers from financial institutions for themselves. They will have access to AI as powerful as the banks have, because Google, Facebook, Apple and Amazon (and companies like them) will be giving it to them. And this will mean individuals will not be the customers: their bots will be. Since most retail financial services offer products that just service a need at a point in time (eg paying for parking) rather than create an extraordinary user experience or are too complicated for normal people to make informed decisions about (eg pensions), we might expect most consumers to abdicate in favour of intelligent agents operating under the new duty of care umbrella. This has been a subject of futurist speculation for some time, but the rapid growth of ChatGPT and its ilk means that banks now have an urgent need to develop strategies to take advantage of this significant change in the nature of the financial services in the mass market. This paper looks at the imminent confluence of open finance and AI to consider the consequences of giving bots access to consumers’ cash (through open banking, for example). This will mean a world of smart wallets, capable of making decisions on behalf of consumers. They will be capable of deciding what services to use, who to get them from and how to maximise their financial well-being, leaving their users to spend more time on human activities.
Keywords: AI; LLM; smart wallet; open banking; open finance
Banks offer crypto: Why does not yours?
Sai Agnikhotram, Fritz Jost and Simon Kühne, Sygnum Bank

This paper shares the perspective of market practitioners who are enabling regulated digital assets services within an institutional context. The authors represent one of the world’s first banks that has a full, Swiss banking licence and that enables clients to buy, hold and sell cryptocurrencies within a fully regulated set-up. The paper first argues why recent market events indicate a strong demand for regulated digital asset services. More so, these events prove that banks are best positioned to offer them in the close future. This work further explains the unique challenges and opportunities in enabling such an offering within a bank. Finally, the authors highlight a set of product criteria and value drivers that allow for a winning digital asset product offering.
Keywords: digital assets; banking; crypto; crypto banking; digital asset banking
Case study: How RegTech tools enable regulatory compliance for cryptoassets: A case study for cryptoasset transaction monitoring
Magdalena Boškic´, Sygnum Bank

BBVA, BNP Paribas, Citigroup, DBS, JPMorgan, Société Générale — these are the names of just a few well-known traditional banks that have already established or are in the process of establishing a cryptoasset offering to their clients. While various challenges need to be overcome in introducing a cryptoasset offering, some might see the true challenge starting once customers can not only ‘buy and hold’ cryptoassets but also transfer these assets to a wallet outside the banking environment or bring their already existing cryptoassets into the banking environment. Compliant yet efficient cryptoasset transaction monitoring as part of an effective cryptoasset compliance framework is an important component of a successful cryptoasset offering by a traditional bank. This paper discusses some of the challenges related to cryptoasset transaction monitoring, provides insights on regulatory technology (RegTech) tools that address those challenges and illustrates in a case study the approach of Sygnum Bank, the world’s first digital asset bank, to overcome these challenges.
Keywords: Blockchain; cryptoassets; banks; compliance; RegTech; transaction monitoring; Travel Rule

Volume 8 Number 1

Editorial
Simon Beckett, Publisher
How can banks continue digital transformation in a downturn?
Rishi Khosla

Digital technologies have come to play an increasingly important role in our lives. Their availability to customers has set expectations for personalised experiences with the banking services they use, making it imperative for banks to innovate and continuously evolve their product offerings to keep up. The banks that are able to do this most successfully are new entrants with advanced technological capabilities that can adapt to changes in the economic environment and consumers’ shifting expectations more quickly. It is this adaptability and technological knowledge that ensures that these new entrants are best positioned to capitalise on periods of downturn. This paper will examine digital transformations that have reshaped the world of banking to date, including the shift to digital banking in the wake of the COVID-19 pandemic, the uses of data and analytics, as well as data-driven tools like AI in present-day retail banking. Furthermore, the paper will detail areas where digital transformation is yet to exert a profound effect on banking, particularly lending to small and medium-sized enterprises (SMEs), an essential area given the contribution that small-to-medium businesses make to economic growth. Finally, the paper will explore ways that new entrants can use digitalisation to support these crucial businesses, as well as detail other examples of digital innovations that are shaping the future of banking; for example, AI automation in know your customer (KYC) and the rise of ‘open banking’.
Keywords: banking; digitalisation; SMEs; downturn; data; innovation
Optimising the customer experience: Lessons for banks from tech giants
Silke Finken and Katharina Rusp

Customer experience has received growing attention as an essential element of the overall customer relationship for banks. The omnipresence of tech giants, their customer centricity and their highly intuitive and user-friendly customer experiences are changing users’ expectations regarding banks’ digital and digitally provided services and points of customer contact. This raises the question of which aspects customers value in their interactions with tech giants and which insights banks can derive for optimising their customer interfaces, experiences and journeys. The present paper is among the first to analyse these various aspects and to derive relevant insights and lessons learned for banks. The study is based on a quantitative online survey with 573 participants. Participants were asked about their degree of satisfaction and loyalty regarding their current bank, the aspects they value most in their interaction with tech giants, in general as well as with their favourite tech giant, and which of these aspects they would like their bank to adopt. Convenience and ease of usability of services, products and interfaces; the constant availability of services regardless of time and place; the seamless integration across different channels and access devices; and the high aesthetics of interfaces and services were considered valuable by more than 70 per cent of the respondents. In particular, the degree of convenience, extensive availability, speed and easily understandable interfaces were also rated highest in terms of characteristics that users would like their banks to adopt. For banks, this means that the design and optimisation of their digital customer experiences should be customer-centric and should focus on intuitive usability, timely delivery of services and information, comprehensive availability of functionalities and relevant data as well as an appealing design of their customer interfaces.
Keywords: Big Tech; tech giants; customer experience; customer journey; open banking
Best practices and important considerations for AI and digital transformation in an economic downturn
Brendan Deakin

Banks surged ahead with digital transformation during the pandemic — largely out of necessity — when faced with lockdowns and the shift to digital-first transactions. Now, as the banking industry moves into the post-pandemic era, and given the current state of economic uncertainty, the adoption of digital transformation is even more crucial. A large proportion of investment will involve AI to improve automation and personalisation while improving the speed and accuracy of decision making. This is essential for banks to address today’s ever-changing risk landscape, especially as consumers and businesses navigate economic uncertainty, rising inflation and energy prices. In the midst of the current economic downturn, organisations must be purposeful in their digital transformation efforts. This paper provides an overview of best practices for digital transformation in the banking sector when every dollar is coming under increased scrutiny.
Keywords: AI; digitisation; fraud prevention; alternative data; machine learning
Evolving consumer expectations and the future of digital banking
Srini Kasturi

The financial services industry has a long history of deploying new technology to respond to evolving customer expectations. The rise of digital banking in recent years represents a significant acceleration of technological change, fuelled by factors like the COVID-19 pandemic and shifting demographics. In the vanguard of sweeping industry changes are the FinTech providers. Advances such as cloud computing APIs and machine learning are being deployed to deliver seamless, 24/7 finance and banking services to consumers who now expect immediate, accessible digital solutions that provide both safety and convenience. Banks need to keep up with the incredible pace of change but face challenges in the form of entrenched legacy systems, siloed operations, a vast beachfront of propositional enhancements and compliance with regulations — issues that typical single-minded FinTechs are less burdened with. Many banks, however, are seeking to overcome these challenges, knowing that otherwise they face diminished market relevance. For many, the answer lies in partnering with existing FinTechs in mutually beneficial engagements that can deliver for increasingly digitally savvy users, such as a partnership between Barclays and TransferMate to deliver advanced cross-border payment services. Regulatory developments like Open Banking have set the scene for increased market competition as well as integrated disparate systems between multiple providers for the benefit of the end user. Onto this stage have entered traditional big-tech firms like Apple, Amazon Google and Meta, seeking opportunities to reshape the digital payments space. In parallel with these developments has emerged decentralised finance (DeFi) offerings that leverage concepts like Blockchain technology, smart contracts and distributed ledgers to provide solutions outside of the centralised processes of traditional finance. This paper explores the changing shape of digital banking; the potential for both competition and collaboration between banks, FinTechs and traditional tech companies; and examines how consumer demands are driving innovation.
Keywords: digital transformation; FinTech; decentralised finance; Open Banking; banking as a service
Case study: Moving towards the scalable service-oriented data management organisation at OTP Bank
Gergely Babos

This paper discusses data and data asset management, topics that are growing in importance in organisations, specifically in regard to managing data consciously as a strategic resource to create business value and building the real self-service data consumption capability. You can read a relevant use case in connection with establishing and transforming the data management organisation — which is basically the back-end function — into a service-based operation model from a component-focused one. By the end of the paper, you will have understood the importance of data strategy and the whole data galaxy focusing on the data modernisation programme in a Hungarian banking group. We were able to reduce data expenses (eg maintenance and license costs of data warehouses, implementation costs of new data elements) by modernising the IT architecture, despite the constantly growing amount of data and the multitude of different data storage solutions. As the hunger for data emerges in the organisation, there is a huge demand for data services. The paper introduces the solution of OTP Bank to flexibly scale the organisation in a way that meets the demand.
Keywords: data management; data asset; data services; data strategy; data-driven company
Practice articles: Modernising intra-day liquidity optimisation for commercial banks
Jeremie Feuillette, Will Towning and Kimmo Soramäki

Commercial banks are facing a period of exceptionally difficult funding conditions amidst a challenging economic environment. To address this, banks need to optimise their liquidity flows and usage. But existing liquidity optimisation and management methods fall short of materially reducing liquidity costs and can generate large operational risks. This paper describes how advanced analytics and algorithms can be used to optimise liquidity flows and usage in a real-time environment through payment resequencing. This approach can enable banks to significantly and consistently reduce liquidity usage and costs, potentially turning more effective treasuries into profit centres. This paper also describes the fundamental requirements for embarking on a modern liquidity optimisation project and also presents some recommendations for best practices in operational and technological infrastructure.
Keywords: liquidity; optimisation; resequencing; networks; algorithms; simulation
The future of cryptocurrency and Blockchain technology in finance
Wong Wanyi and Alan Megargel

Cryptocurrencies have been all the rage in recent years, drawing many to hold them as speculative investment assets. Its proponents also champion the secure and decentralised nature of the technology it is based on, called the Blockchain. Given the secure nature of Blockchain technology, the idea of adopting cryptocurrencies as legal tender currency has also been mooted and experimented with — the most famous example being the Central American nation of El Salvador’s bold move to adopt the cryptocurrency Bitcoin as legal tender in September 2021. In theory, this would provide a solution to the high transaction costs faced by overseas El Salvadoreans when transferring money home and to the lack of bank accounts in the case of 70 per cent of its population — Bitcoin does not require a bank account and can be transferred across borders easily. However, even though individual consumers seem to evince interest in adopting cryptocurrencies as legal tender, most countries have little appetite to do so or to integrate their use into their citizens’ lives. Does cryptocurrency have a future as a legal tender currency or as an investment asset? If not, what are the potential future developments? This paper examines and attempts to answer these questions by (i) analysing the pros and cons of adopting cryptocurrencies as legal tender; (ii) discussing alternative uses for the Blockchain technology behind cryptocurrency; and (iii) reviewing regulatory challenges to cryptocurrency as an investible asset.
Keywords: cryptocurrency; Blockchain; stablecoin; decentralised finance; central bank digital currency
Account aggregator ecosystem: A step towards revolutionising digital lending in India
Venkat Yellapantula and Venu Madhav Miriyala

An essential contributor to a nation’s economic success is providing individuals with access to established financial systems. India, through innovative use of digital finance infrastructure, aka India Stack, provided as a public good, removes obstacles in offering financial products to the unbanked and underbanked. The three pillars of the India Stack are: the identity rail (Aadhaar), the payment rail (universal payment interface) and the data-sharing rail of account aggregators (AAs). The next phase in the India Stack is the Open Credit Enablement Network (OCEN), which promises to transform the digital lending industry by shifting the business model from asset-based to cash-flow-based lending. OCEN is a standard set of application programming interfaces (APIs) that pull data based on customer consent from financial information providers and offers it to financial information users to decide on credit requests. AA manages consent on behalf of the customer using data empowerment and protection architecture (DEPA). The rest of the paper explains the interoperability and portability features of the AA ecosystem, the pricing model that the AA can adopt for a sustainable business model, describes the current state of the AA ecosystem in terms of consents provided and fulfilled and concludes with the use cases of OCEN in credit extension and continuous loan monitoring.
Keywords: account aggregator (AA); India Stack; Open Credit Enablement Network (OCEN); open banking; digital lending; data empowerment and protection architecture (DEPA)