Issue 88
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CONTENTS
CEO & Editor In Chief Varun SASH Managing Director Mayha Das Managing Director Martin Murphy Editor Barnali email: editor@gbafmag.com Editor Regional Shaharban T Project Management Megan S | Raj G Assistant Operations Manager Anupama KU Director of Operations Babitha G Digital Sales Rohit D Nominations Adam L | Sarah F Research Varshitha K | Jyothi P Video Production & Journalism Phil Fothergill Graphic Design Shiva K Advertising Phone: +44 (0) 208 144 3511 marketing@gbafmag.com GBAF Publications, LTD Alpha House 100 Borough High Street London, SE1 1LB United Kingdom Global Banking & Finance Review is the trading name of GBAF Publications LTD Company Registration Number: 7403411 VAT Number: GB 112 5966 21 ISSN 2396-717X. The information contained in this publication has been obtained from sources the publishers believe to be correct. The publisher wishes to stress that the information contained herein may be subject to varying international, federal, state and/or local laws or regulations. The purchaser or reader of this publication assumes all responsibility for the use of these materials and information. However, the publisher assumes no responsibility for errors, omissions, or contrary interpretations of the subject matter contained herein no legal liability can be accepted for any errors. No part of this publication may be reproduced without the prior consent of the publisher.
editor Dear Readers’ Welcome to Issue 88 of Global Banking & Finance Review. This issue explores a question increasingly shaping boardrooms, financial institutions and technology strategies: how do organisations prepare for change before that change becomes unavoidable? Our cover story, “Why Business Reinvention Starts Long Before Markets Change,” examines why companies need to build new capabilities while their existing models are still performing. From strategic optionality and capital allocation to workforce development and technology readiness, the article considers why reinvention is most effective when it begins from a position of strength rather than under pressure. Technology is another major theme. We look at the decisions surrounding cloud infrastructure, artificial intelligence, cybersecurity, data and automation, and why long-term value depends not simply on spending more, but on making technology choices that support measurable business outcomes. Our client perspectives bring these themes into sharper focus. Christian Beine, Director Product and Solution Security at Diebold Nixdorf, examines the Cyber Resilience Act and the growing importance of transparency, vulnerability assessment and cybersecurity across banking and retail infrastructure. In a Q&A, Lakshitha Fernando, General Manager of Solarelle Insurance, discusses how the Maldivian insurer is approaching innovation, digitalisation, evolving customer expectations and emerging risks. The discussion also explores Solarelle’s work around epidemic and pandemic risk protection, and the role insurance can play in supporting greater resilience across the Maldives. Elsewhere, we examine the approaching deadline for faster and cheaper cross-border payments, the real economic use of stablecoins, accountability when AI systems influence lending decisions, the changing battle for control of the checkout experience, and the growing importance of human judgement in private banking. Together, these articles reflect a financial landscape being reshaped by technology, regulation, changing customer expectations and new forms of competition. Thank you for reading. We hope Issue 88 provides valuable perspectives as you navigate what comes next.
Barnali Pal Sinha Editor, Global Banking & Finance Review
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Issue 88 | 03
CONTENTS
Inside... TECHNOLOGY
BUSINESS
18
The Technology Decisions That Shape Long-Term Growth
14
Why Business Reinvention Starts Long Before Markets Change
28
Who Is Responsible When an AI System Rejects Your Loan?
38
Who Owns the Checkout? The New Business Battle for Payments
48
Why Human Judgment Is Becoming Private Banking’s Most Valuable Competitive Advantage
BANKING
08
FINANCE
22
The Cross-Border Payments Deadline: Why the World Is Still Waiting for Faster, Cheaper Transfers
34
The $35 Trillion Stablecoin Illusion: How Much Is Actually Used in the Real Economy?
42
Stablecoins Challenge the Future of Bank Deposits
Christian Beine, Director Product and Solution Security, Diebold Nixdorf
Cyber Resilience Act: Progressing Transparency in Cybersecurity 04 | Issue 88
CONTENTS
INTERVIEW
10
Lakshitha Fernando MBA, General Manager
Solarelle Insurance: Leading a New Era of Risk Protection in the Maldives Issue 88 | 05
BANKING
Cyber Resilience Act: Progressing Transparency in Cybersecurity This month marks a milestone in transparency for consumers in the European Union: the reporting obligation, the first part of the Cyber Resilience Act (CRA), is coming into effect. The goal of this new legislation is to improve the cybersecurity of products at multiple levels, including communication on vulnerabilities.
As a major provider of banking and retail products and solutions, Diebold Nixdorf (DN) has focused on security since the company’s founding, and security is part of our DNA. DN shares the goals of the legislation, and none of the requirements are new for us as an organization. But adjusting our processes to fit was an interesting challenge.
While the legislation is mostly focused on consumer goods, it also applies to ATMs and Retail equipment. Manufacturers who sell their devices in European Union (EU) member states will be required to guarantee security by design from the get-go and provide constant updates to devices throughout their lifecycle. For critical equipment like ATMs, this effort will require audits by external parties to verify if all aspects of the legislation are covered. Not just that. Should a vulnerability be discovered, they are required to report it to an official agency.
For computer systems, this already exists as the Common Vulnerability Scoring System (CVSS). This is an industry standard created in 2005 by the Forum of Incident Response and Security Teams (FIRST) and is currently published in its 4th version. Aside from an initial score, it also gives an environmental score that informs users about the effects of different mitigation mechanisms and countermeasures that may be in place.
What’s the problem? Sounds good, doesn’t it? Unfortunately, there are still issues that make this regulation less actionable than it seems at first glance. Over the past years, we have seen an explosion in the number of vulnerabilities discovered day by day. The vulnerability statistics of the National Institute of Standards and Technology (NIST) demonstrate a rapid growth in reported vulnerabilities globally. So many that it is basically already impossible to keep up with each report. This is further increased by the emergence of AI tools that are used by both good and bad actors to discover vulnerabilities in IT systems. Meanwhile, not all these vulnerabilities are critical or require immediate action. Especially in a hardened environment like an ATM. However, among the huge number of reports, it is nearly impossible to identify which vulnerabilities are actionable and require updates. Some reported vulnerabilities reported by AI may even be false positives. To put it simply: There is too much noise. Then how can I find out if I need to do something? So, what can you do to cut through the noise and focus on the important topics? We need to create a way to prioritize: Findings should not only be reported but also validated and assessed. Rather than simply informing users about vulnerabilities, we need an environment-specific scoring approach that clearly identifies which weaknesses require immediate action.
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At Diebold Nixdorf, we were inspired by that and decided to not only fulfill the requirements posed by the CRA but also implement the DN Vulnerability Scoring System (DNVSS) to provide the best possible information. Like the CVSS, in the future we will assign a base score to every vulnerability found in our products and solutions as well as a Hardened Score that takes into account additional security measures, such as access restrictions, configuration changes and monitoring controls installed on a device. The Hardened Score is the core value of DNVSS, as it provides actionable risk within a hardened environment. This provides clear guidance on where to focus resources for updating the fleet. Where can I get access to it? This score will be freely available to all users of the Diebold Nixdorf Global Security Portal, our central point for security information on all our solutions. Attack type definitions, countermeasures, current attack trends and our yearly cybersecurity Threat Report can be found in the portal already. The DN Vulnerability Scoring System was added to further improve transparency and help our customers focus their efforts where they are needed the most. If you are not yet subscribed, you can sign up to become a user via this form. Even with the scoring system, we are aware that ATM security remains a complex topic and helping our customers navigate it is one of my team’s core tasks. To do so, we offer to perform individual security assessments for your fleet. If you are interested in scheduling one, you can signal your interest via this form, and we will get in contact with you. If you require more information you can always contact the Product and Solution Security Team at Diebold Nixdorf via security@dieboldnixdorf.com.
BANKING
Christian Beine,
Director Product and Solution Security, Diebold Nixdorf
Issue 88 | 09
INTERVIEW
Solarelle Insurance: Leading a New Era of Risk Protection in the Maldives 1 ) What do you believe were the key factors that contributed to Solarelle Insurance being recognised as Best General Insurance Company Maldives 2026, and what does this recognition mean for your organisation, employees and customers? I believe this recognition reflects a combination of strong financial performance, disciplined underwriting, innovation, customer focus, and, most importantly, the commitment of our people. Over the years, Solarelle Insurance has focused on understanding the evolving needs of the Maldivian market and developing solutions that are relevant to our customers, while maintaining strong partnerships with leading international reinsurers. Our continued investment in product innovation, risk management, technology and service quality has helped us differentiate ourselves in a competitive market. We are particularly proud of introducing innovative solutions such as our Epidemic and Pandemic Insurance product, supported by Munich Re, demonstrating our ability to address emerging risks affecting the Maldives. For our employees, this recognition is a tremendous source of pride and motivation. It validates their hard work and encourages us to raise our standards even further. For our customers, the award is a reassurance that they are partnering with an insurer that is financially responsible, innovative, reliable and committed to delivering quality protection and service. Ultimately, this recognition is not just an award for Solarelle; it is a responsibility to continue building trust, creating value and setting higher standards for the Maldivian insurance industry. 2) Solarelle Insurance has also been recognised with the Decade of Excellence - General Insurance Maldives 2026 award. Looking back over the past decade, what have been the most important milestones in the company's development, and how has Solarelle evolved to meet the changing insurance needs of the Maldivian market? Looking back, I believe Solarelle Insurance’s ten-year journey is truly remarkable and, in many respects, unmatched in the Maldivian insurance industry. Since entering the market in 2016, we have built Solarelle from the ground up with a clear vision of becoming a strong, innovative and trusted Maldivian insurer. Over the past decade, we have achieved several key milestones from establishing strong financial and operational foundations
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and building long-term partnerships with leading international reinsurers, to continuously expanding our product portfolio and strengthening our presence across key sectors of the Maldivian economy. We have also invested significantly in our people, underwriting capabilities, claims management, technology and customer service. What makes this journey particularly special is that we have never remained static. We have continuously evolved with the changing needs of our customers and the market, moving beyond traditional insurance solutions towards innovative, risk-focused and customer-centric offerings. Throughout this journey, Solarelle has established itself as a landmark in the Maldivian insurance industry, setting new benchmarks through innovation and consistent growth. The Decade of Excellence recognition is therefore more than an award it is a reflection of ten years of achievement and our unwavering commitment to shaping the future of insurance in the Maldives. 3) Customer expectations and risk profiles continue to change across the insurance industry. How does Solarelle ensure that its general insurance products, service standards and claims processes remain relevant, accessible and responsive to the needs of individuals and businesses in the Maldives? At Solarelle Insurance, we believe that understanding our customers is at the heart of delivering relevant and effective insurance solutions. We maintain a very close understanding of the Maldivian market, continuously monitoring changing customer expectations, emerging risks and sectorspecific requirements across both the retail and corporate segments. Our strength lies in our ability to combine this deep local market knowledge with international insurance standards and best practices. Whether it is an individual customer seeking simple and accessible protection or a large corporate client requiring complex risk solutions, we focus on providing the right coverage, flexibility and service to meet their specific needs and preferences. We continuously review and enhance our products to ensure they remain competitive, relevant and responsive to evolving risks. At the same time, we place strong emphasis on efficient claims management, clear communication and timely customer support, because we believe our commitment to customers is truly tested when a claim occurs. Ultimately, Solarelle’s approach is centred on giving customers choice, understanding their individual needs and delivering solutions that provide genuine value. This combination of local insight, customer focus and international standards enables us to remain agile and responsive in a rapidly changing Maldivian insurance landscape.
INTERVIEW
Lakshitha Fernando MBA, General Manager
Issue 88 | 11
INTERVIEW 4) Innovation is becoming increasingly important in insurance. What role do technology, digitalisation, data and operational improvements play in enhancing Solarelle's underwriting capabilities, customer experience and overall service delivery?
A major epidemic or pandemic can significantly affect tourist arrivals, travel patterns and business operations. We therefore believed the market needed an innovative solution that could provide businesses with greater financial resilience during such extraordinary events.
At Solarelle Insurance, we strongly believe that investing in technology is not simply an operational requirement, it is a key driver of our future growth and competitiveness. With the rapid pace of change globally, the insurance industry must continuously embrace digitalisation, data and smarter ways of working to remain relevant and responsive.
This led us to develop the Epidemic & Pandemic Insurance Cover specifically for the Maldives tourism sector. The product was developed after carefully analysing historical data, global pandemic experience and the specific risk characteristics of the Maldivian market. It was structured on a parametric basis, with predefined triggers that can activate the coverage. This approach provides greater clarity and transparency while enabling faster financial support without relying on lengthy traditional lossassessment processes.
For Solarelle, enhancing our digital presence is particularly important given the unique geographical landscape of the Maldives, where customers and businesses are spread across many islands. Technology provides us with an opportunity to make insurance more accessible, convenient and efficient, regardless of where our customers are located. We are therefore focused on strengthening our digital capabilities across the customer journey from product information and quotations to policy administration, communication, claims handling and customer support. At the same time, better use of data will enable us to strengthen underwriting decisions, identify emerging risks and develop products that are more accurately aligned with customer needs. Operational improvements and automation will also help us improve efficiency, reduce turnaround times and enhance service consistency. Ultimately, we see technology and digitalisation as a long-term strategic investment that will enable Solarelle to build a more agile, data-driven and customer-centric insurance business for the future. 5) Solarelle has been recognised for the Most Innovative Insurance Product (Epidemic & Pandemic Risk Solution) Maldives . What inspired the development of this solution, and what specific protection gaps or customer challenges was it designed to address? I am particularly proud that Solarelle Insurance is recognised as the first insurance company in the Maldives to collaborate with Munich Re and introduce the country’s first-ever dedicated Epidemic & Pandemic Insurance Policy, backed by the strong reinsurance capacity and expertise of Munich Re. For me, this achievement represents much more than launching a new insurance product. It demonstrates our willingness to identify emerging risks, challenge traditional insurance thinking and develop solutions specifically for the needs of the Maldivian market. The inspiration behind this product came directly from the lessons of the COVID-19 pandemic. It demonstrated how vulnerable economies, businesses and particularly the Maldives’ tourism industry can be to global health emergencies. Traditional insurance products generally do not adequately respond to pandemicrelated losses, while business interruption coverage often requires physical damage to trigger a claim. This created a significant protection gap for businesses that could experience substantial financial losses even without any physical damage to their assets. We recognised that this was particularly important for the Maldives given our strong dependence on tourism and international travel.
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I am especially proud that the inaugural policy was issued to the Maldives Association of Tourism Industry (MATI) at the official launch ceremony. This made the initiative particularly meaningful because it demonstrated that the product was not simply an idea, but a practical solution developed to address the needs of one of the most important sectors of our economy. The successful development of this product was made possible through our strategic collaboration with Munich Re, one of the world’s leading reinsurers. The strong reinsurance backing brought global technical expertise, financial strength and credibility to the solution. We also worked closely with local and international reinsurance brokers to structure and implement the product effectively. Ultimately, our objective was to redefine what insurance can offer in response to emerging risks. We wanted to move beyond simply responding to traditional risks and instead anticipate future challenges by creating meaningful protection before the next crisis occurs. Being recognised with the Most Innovative Insurance Product Pandemic and Epidemic Risk Solution Maldives is therefore a very proud milestone for Solarelle. More importantly, it reinforces our belief that true innovation in insurance starts with understanding unique customer risks and having the courage to develop solutions that genuinely address those protection gaps. 6) Looking ahead, what are Solarelle Insurance's key strategic priorities for strengthening its market position, developing new products and supporting greater resilience and insurance awareness across the Maldives? Looking ahead, our key priority at Solarelle Insurance is to strengthen our position as a leading, innovative and trusted Maldivian insurer while continuing to create meaningful value for our customers and the wider economy. One of our main strategic focuses will be product innovation. We want to move beyond traditional insurance solutions and develop products that respond to emerging risks and the changing needs of both individuals and Corporate businesses. This includes greater focus on parametric solutions, specialised corporate covers, and innovative retail products designed around real customer needs. We also see technology and digitalisation as critical to our future growth. Given the geographical spread of the Maldives, enhancing our digital capabilities will allow us to make insurance more accessible, convenient and efficient for customers across the country. We will continue investing in digital platforms, data-driven underwriting, automation and improved claims processes.
INTERVIEW
Another important priority is strengthening our technical and human capabilities. We believe that a strong insurance company is built on strong people, and therefore we will continue investing in professional development, underwriting expertise, claims management, risk management and leadership capabilities. At the same time, we want to contribute to greater insurance awareness and financial resilience across the Maldives. There is significant opportunity to educate customers about the importance of proactive risk protection rather than viewing insurance simply as a requirement after a loss occurs. Ultimately, our ambition is to build Solarelle into an even more customer-centric, digitally enabled and innovation-driven insurer, while maintaining international standards and a deep understanding of the unique risks and opportunities within the Maldivian market. Our focus will remain on sustainable growth, stronger partnerships and creating insurance solutions that genuinely protect our customers and support the resilience of the Maldives. 7) As Solarelle Insurance enters its next phase of growth, how do you see the company contributing to the future development of the Maldivian insurance sector, particularly in areas such as innovation, resilience and evolving customer needs? As Solarelle Insurance enters its next phase of growth, our ambition is to contribute to the long-term development of the Maldivian insurance sector by focusing on innovation, customer centricity approch with sustainable growth.
Strategically, we want to position Solarelle as a more agile, technologydriven and forward-looking insurer that can anticipate emerging risks rather than simply respond to them. Our focus will be on continuously identifying gaps in the market, understanding changing risk profiles and developing solutions that are relevant to the evolving needs of individuals and businesses. Digital transformation and data-driven decision-making will be central to this strategy. Given the geographical nature of the Maldives, technology can play a significant role in making insurance more accessible, improving service efficiency and creating a more seamless customer experience across the country. We also intend to strengthen our focus on risk management and resilience by helping customers better understand their exposures and encouraging a more proactive approach to risk protection. At the same time, strengthening our technical capabilities, talent, governance and operational efficiency will remain fundamental to our sustainable growth. Another strategic priority will be building greater insurance awareness and customer trust. We believe the future of insurance depends not only on selling policies, but on educating customers and demonstrating the real value of insurance when they need it most. Ultimately, our goal is to help shape a more innovative, resilient, digitally enabled and customer-focused insurance sector in the Maldives, while maintaining international standards and remaining deeply connected to the unique needs of our local market.
Issue 88 | 13
BUSINESS
Why Business Reinvention Starts Long Before Markets Change
Reinvention is not a rescue plan Corporate reinvention is often narrated backwards. A market shifts, a competitor appears, margins collapse or a technology becomes unavoidable; only then does management announce a transformation programme. That sequence makes for a clear story, but it is usually the least attractive moment to begin. Once the pressure is visible to everyone, the company is already competing for the same scarce engineers, suppliers, acquisition targets, distribution partners and leadership attention as every other incumbent that reached the same conclusion. The better model is to treat reinvention as a standing strategic capability. PwC’s 2026 Global CEO Survey, based on 4,454 chief executives across 95 countries and territories, found that only 30% were confident about their company’s revenue growth over the coming 12 months. Yet CEOs were simultaneously pushing into new sectors, investing in AI and rethinking how their companies create value. That combination matters: uncertainty does not remove the need for long-term change; it makes the timing of that change more consequential. The central lesson is simple. A company should not ask whether its current business is broken. It should ask whether the capabilities that make it successful today are likely to remain sufficient when customer economics, technology, talent and industry boundaries move. Reinvention begins when the answer becomes uncertain— not when the answer becomes no. The market usually changes before the numbers do Financial statements are lagging indicators. Revenue, margin, market share and return on capital tell management what has already happened. The earliest signs of structural change are usually weaker and more ambiguous: a new customer behaviour that looks niche, a technology whose economics are improving faster than expected, a competitor entering from an adjacent
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sector, a change in distribution economics, or a new skill becoming disproportionately valuable. That is why strong companies can appear healthy at the beginning of a strategic decline. Their installed base, brand, contracts and operating discipline continue to generate cash even as the assumptions underneath the model start to erode. Waiting for deterioration to show up in headline financial performance can therefore create a false sense of safety. By the time a threat is visible in the income statement, the organization may be trying to build new capabilities under pressure rather than from strength. PwC’s 2025 survey captured this tension directly: 42% of CEOs said their company would not remain viable beyond the next decade if it continued on its current path. At the same time, companies that had taken more actions to reinvent how they create, deliver and capture value reported higher profit margins, even after PwC adjusted for factors including industry, geography and company size. The correlation does not prove that every transformation produces better margins, but it challenges the idea that reinvention is mainly a defensive move for businesses already in trouble. Strategic optionality is built before it is needed Early reinvention is valuable because it creates options. A business with only one product logic, one route to market, one critical technology stack or one source of growth may be efficient in stable conditions, but it is fragile when the environment shifts. By contrast, a company that has already tested adjacent products, developed new channels, formed partnerships, modernised its data architecture or learned to sell into a neighbouring customer segment has more room to manoeuvre. This is increasingly visible in cross-sector expansion. In PwC’s 2026 survey, 42% of CEOs said their companies had started competing in new sectors over the previous five years. Among CEOs planning at least one major acquisition in the next three years, 44% expected to pursue deals outside their existing sector or industry. These moves are not always about abandoning the core business. Often they are about building a second source of relevance before the first one weakens.
BUSINESS
Optionality also changes the economics of decision-making. A company that has already run small experiments can scale a proven capability when conditions turn. A company that has done nothing must first learn whether the idea works, then secure resources, then build the operating model—all while the market is moving against it. The first company is choosing among options; the second is purchasing time at a premium. Technology creates pressure long before it creates displacement Artificial intelligence is the clearest current example. The World Economic Forum’s Future of Jobs Report 2025 found that 86% of surveyed employers expected AI and information-processing technologies to transform their business by 2030. Sixty per cent expected broader digital access to transform their business, while 58% pointed to robotics and automation. These are not forecasts of a single sudden shock. They describe multiple capability curves advancing at the same time. The strategic mistake is to wait until a technology has completely changed customer behaviour before building the internal ability to use it. At that point, the difficult work is not procurement; it is redesign. Data must be accessible, processes need to be simplified, governance must be clear, teams require new skills, and managers need to understand where automation improves economics and where it merely accelerates a bad process. PwC’s 2026 CEO survey also shows the gap between experimentation and value capture. Only 12% of CEOs said AI had delivered both cost and revenue benefits, while 56% reported no significant financial benefit to date. That does not imply AI is failing. It suggests that the value of a general-purpose technology
depends on the organisational foundations around it. Reinvention therefore starts with operating architecture, not with the moment a new tool becomes fashionable. Workforce reinvention has the longest lead time Business models can be redrawn on a slide in an afternoon. Workforces cannot. Skills take time to develop, teams need practice with new ways of working, and leadership systems have to learn how to make different trade-offs. This makes talent one of the strongest arguments for starting reinvention early. The World Economic Forum reports that 63% of employers see skills gaps as a primary barrier to transformation over the 2025–2030 period. It also estimates that nearly 40% of skills required on the job are expected to change by 2030. Employers are responding with large-scale upskilling plans: 77% say they plan to upskill workers as AI reshapes roles and tasks. The implication for leadership is not simply to spend more on training. It is to connect workforce design to strategic direction. If a company believes data, automation, cybersecurity, advanced manufacturing or new distribution models will matter more in five years, those capabilities should influence hiring, internal mobility and leadership development today. Otherwise, the company may discover that it has correctly predicted the future but lacks the people required to compete in it. The strongest core businesses can be the hardest to reinvent Paradoxically, success can delay change. A profitable core business creates evidence that the current model works, rewards managers for protecting it and makes experimentation look less economically attractive. The organization learns to optimise what it already knows rather than question what customers may value next.
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BUSINESS
This creates a familiar allocation problem. New businesses initially look worse than mature ones: lower revenue, weaker margins, uncertain demand and higher unit costs. If every new initiative is judged against the economics of the established core, promising adjacencies can be killed before they have had time to develop. Reinvention therefore requires a portfolio mindset in which different businesses are assessed according to their stage, strategic role and learning value—not only their immediate profitability. That does not justify undisciplined experimentation. PwC’s 2026 findings point to a meaningful execution gap: only about one in four CEOs said their organisations consistently tolerate high risk in innovation projects, stop underperforming initiatives with discipline, or operate a defined innovation centre or corporate venturing function. Reinvention needs permission to experiment and permission to stop. Without both, innovation becomes either timid or wasteful. Capital allocation reveals whether reinvention is real Strategy becomes credible when resources move. A company may speak about transformation, AI, customer experience or new markets, but if almost all capital and senior talent remain tied to the legacy model, the organisation is effectively betting that the future will resemble the past.
cost-cutting, and close weak initiatives before reputational or financial stakes become too high. Once the market turns, by contrast, every investment decision is made under scrutiny and often against a shrinking pool of available capital. Reinvention should be measured by learning velocity Traditional transformation programmes often measure activity: systems installed, employees trained, projects launched, offices consolidated or processes digitised. Those metrics are useful, but they do not answer the strategic question. A company can complete every programme milestone and still fail to improve its position. A more useful measure is learning velocity. How quickly can the organisation test an assumption about customer demand? How fast can it move a product from experiment to scaled offer? How easily can it shift people and capital when evidence changes? Can it identify an underperforming initiative and stop it without political delay? Can insights from one business unit become reusable capabilities elsewhere? These questions matter because reinvention is not one decision. It is a repeated cycle of sensing, testing, allocating, learning and scaling. The companies best prepared for market change are therefore not those with the most elaborate five-year plans. They are the ones that have built institutional mechanisms for changing their minds without losing strategic coherence.
This is one reason resource reallocation matters. PwC’s 2025 survey found that roughly half of CEOs said their companies reallocated 10% or less of financial and human resources from year to year, while more than two-thirds reallocated less than 20%. The same survey reported that only about 7% of revenue over the previous five years came from distinct new businesses on average. Those figures illustrate a central reinvention problem: strategic language can change much faster than resource architecture.
Leadership must protect the future from the present
Early reinvention gives leaders a more forgiving environment in which to move resources gradually. They can fund experiments from a healthy core, build new capabilities without emergency
Boards and senior leaders can protect long-term work by creating explicit investment envelopes for new capabilities, setting milestones around learning rather than only near-term revenue, and assigning accountable
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Short-term performance will always dominate executive attention because it is measurable, urgent and visible to employees, boards and investors. PwC’s 2026 survey found that CEOs spend 47% of their time on issues with a horizon of less than one year and only 16% on decisions looking more than five years ahead. That imbalance is understandable. It is also why long-horizon reinvention requires deliberate governance.
BUSINESS
executives to future businesses before those businesses become material. They can also separate two questions that are often confused: whether the core business should be optimised, and whether the company should be building alternatives. Most durable firms need to do both at once. The point is not to predict the future perfectly. Prediction is too fragile for that. The point is to reduce the cost of being wrong. A business with adaptable technology, transferable skills, diversified channels, disciplined experimentation and flexible capital allocation can absorb surprise better than one whose efficiency depends on a single stable version of the world. What early reinvention looks like in practice Early reinvention is usually quieter than a corporate turnaround. It can begin with small but consequential changes: building a common data layer before AI use cases become mission-critical; piloting direct-to-customer channels while intermediated sales remain profitable; developing subscription or usage-based pricing before customers demand it; creating partnerships in adjacent sectors; reskilling employees before roles disappear; or simplifying processes before automation makes complexity harder to unwind. It also involves deliberate scenario work. Leaders do not need a single confident forecast. They need to identify which capabilities would remain valuable across several plausible futures. Better customer data, faster product development, stronger cybersecurity, improved cash visibility, flexible supply chains and a workforce comfortable with continual learning tend to have option value even when the exact disruption differs from the scenario originally imagined. This approach turns reinvention from an event into an operating discipline. Instead of asking when the next market change will arrive, management asks which assumptions the current model depends on and which of those assumptions are becoming less certain. That is a much earlier warning system.
The risk of reinventing too early There is, of course, a counterargument. Companies can waste enormous amounts of money chasing technologies that never mature, markets that remain niche, or strategic fashions that disappear after a few years. Constant reinvention can exhaust employees, fragment brands and weaken a profitable core. A company that is always transforming may never become excellent at anything. That is why early reinvention should not mean permanent organisational upheaval. The objective is optionality with discipline: small experiments, explicit hypotheses, protected learning budgets, clear kill criteria and staged capital commitments. The organisation should make uncertainty cheaper, not convert every uncertainty into a major transformation programme. The distinction is crucial. Reactive transformation bets the company after the evidence is obvious. Disciplined early reinvention buys information before the bet becomes unavoidable. Conclusion: change before change becomes compulsory Markets rarely send a formal notice before they change. Customer expectations drift, technologies become cheaper, adjacent competitors cross industry boundaries, talent migrates, and economics move one assumption at a time. The companies that look most prescient afterwards are often those that treated these weak signals as reasons to build capability rather than reasons to predict catastrophe. That is why business reinvention starts long before markets change. The goal is not to abandon what works. It is to make sure that what works today does not become the reason the organisation is unable to compete tomorrow. When the external environment finally makes reinvention obvious, the advantage no longer belongs to the company with the best presentation about transformation. It belongs to the company that has already done the difficult, unglamorous work of becoming capable of something new.
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TECHNOLOGY
The Technology Decisions That Shape Long-Term Growth Technology investment has become inseparable from business strategy. Cloud infrastructure, artificial intelligence, cybersecurity, data platforms and automation now influence how quickly companies can launch products, serve customers, manage risk and scale operations. Yet higher technology spending does not automatically create stronger performance. The longterm difference increasingly lies in the quality of the decisions surrounding technology: what to modernise, where to standardise, which capabilities to build internally, what to automate and how to connect investment with measurable business outcomes. This distinction matters because technology decisions compound. An architecture choice made today can determine whether a company can integrate an acquisition five years from now. A data-governance decision can shape whether artificial intelligence produces reliable insights or simply accelerates poor information. A cybersecurity investment can protect not only systems but also customer trust and business continuity. Conversely, short-term technology choices made primarily to solve an immediate problem can create technical debt, fragmented data and rising operating costs that constrain future growth. Technology Strategy Must Begin With Business Value The most important technology decision is often the first one: deciding what business outcome the investment is intended to improve. Organisations that treat technology as an isolated IT agenda risk accumulating tools without creating meaningful operating advantage. By contrast, companies that connect technology portfolios to revenue growth, customer experience, productivity or resilience can evaluate investments against a clearer strategic standard. McKinsey's research on technology transformations found that top-performing organisations were more likely to anchor technology and digital strategy in overall business strategy. In its survey, 87% of top performers reported a positive impact from technology transformation on generating new revenue streams, compared with 58% of other respondents. This does not imply that technology alone produces growth; it illustrates the importance of strategic alignment and execution discipline. Source: McKinsey & Company
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Architecture Decisions Determine Future Flexibility A second long-term decision concerns architecture. Businesses frequently face pressure to add systems quickly, especially when new customer demands or operational requirements emerge. The immediate solution may work, but repeated point solutions can leave the organisation with duplicated applications, disconnected data and expensive integration requirements. A more durable approach considers interoperability, scalability and portability at the start. Cloud computing has become central to this discussion because it can provide flexible access to computing resources and enable organisations to scale capacity as requirements change. The National Institute of Standards and Technology describes cloud computing as on-demand access to a shared pool of configurable resources that can be rapidly provisioned and released. For businesses, the strategic value is not simply hosting infrastructure elsewhere; it is the ability to design operations around greater flexibility and speed. Source: NIST - The Definition of Cloud Computing AI Investment Requires a Portfolio, Not a Single Bet Artificial intelligence is now one of the most visible technology priorities, but long-term value depends on selecting use cases carefully. The strongest opportunities tend to combine measurable business need, usable data, appropriate human oversight and a workflow that can actually change. Buying an AI tool without redesigning the surrounding process often produces limited benefits because the bottleneck remains elsewhere. A portfolio approach can separate exploratory use cases from scaled operational deployments. Low-risk applications such as knowledge search, document summarisation or internal productivity support can help organisations build experience, while higher-impact applications in pricing, risk, customer service or forecasting may require stronger controls and validation. This staged approach allows businesses to learn without committing the entire technology strategy to a single platform or model. OECD research on AI adopters also highlights the importance of complementary assets. Firms using AI tend to be more productive, particularly among larger adopters, but the research notes that ICT skills, high-speed digital infrastructure and the use of other digital technologies play a critical role. The implication is important: AI value is often a system
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outcome, not the result of one software purchase. Source: OECD - A Portrait of AI Adopters Across Countries
foundations that allow new capabilities to diffuse through everyday operations rather than remain isolated pilots. Source: OECD Technology Diffusion
Data Quality Is a Growth Infrastructure Decision
Cybersecurity Should Be Designed Into Growth
Every major technology initiative increasingly depends on data. Customer personalisation, automation, forecasting, fraud detection and AI-assisted decision-making all require data that is accessible, consistent and appropriately governed. As a result, decisions about data architecture are becoming long-term growth decisions.
Cybersecurity is sometimes treated as a defensive cost, but its strategic role is broader. Growth creates new users, suppliers, applications, devices and data flows, each of which can expand the organisation's risk surface. If security is added only after systems are deployed, controls can become expensive, disruptive and inconsistent.
Businesses can invest heavily in advanced analytics and still struggle if core definitions differ between departments, important records remain trapped in legacy systems or ownership is unclear. A mature data strategy addresses common definitions, stewardship, access controls, quality measurement and integration. It also distinguishes between data that should be centralised for consistency and data that can remain distributed closer to the teams that use it. The OECD identifies technology diffusion as a critical driver of productivity growth and notes that adoption varies considerably across firms. This reinforces a broader point: access to technology is not enough. Companies need the organisational and data
A long-term approach integrates cybersecurity into architecture, procurement, software development, identity management and thirdparty oversight. NIST's Cybersecurity Framework 2.0 is designed for organisations of all sizes and sectors and adds explicit emphasis on governance alongside identifying, protecting, detecting, responding and recovering. This makes cybersecurity a management responsibility rather than a purely technical one. Source: NIST Cybersecurity Framework 2.0 For growth-oriented companies, the objective is not to eliminate all risk. It is to understand which risks matter, establish appropriate controls and create enough resilience that innovation can continue without exposing the organisation to avoidable disruption.
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Technology Choices Must Include Workforce Capability A technology investment can only create value if employees can use it effectively. This makes workforce capability one of the most important and frequently underestimated components of long-term technology strategy. Training should not begin after implementation; it should influence the design of the investment itself. The World Economic Forum's Future of Jobs Report 2025 found that nearly 40% of skills required on the job are expected to change by 2030, while 63% of employers identified skills gaps as a major barrier to business transformation. Demand is expected to rise for AI, big data and cybersecurity skills, but human capabilities such as resilience, flexibility, creative thinking and collaboration remain important. Source: World Economic Forum - Future of Jobs Report 2025 Businesses therefore need to decide whether a technology programme is simply deploying software or building a new organisational capability. The latter requires role redesign, learning pathways, manager support and clear expectations about how work should change once the technology is available. Avoiding Technical Debt Protects Future Investment Capacity Technical debt is the accumulated cost of shortcuts, outdated systems and temporary fixes that remain in place long after their original purpose. Some debt is rational: speed may justify a temporary workaround. The problem arises when temporary choices become permanent without review. Over time, technical debt absorbs technology budgets through maintenance, integration work and specialist support. It can also
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slow product launches because every new initiative must navigate a more complex environment. A disciplined technology portfolio therefore includes explicit decisions about retirement, consolidation and simplification, not only new investment. This is where long-term thinking matters. The absence of immediate failure can make legacy systems appear inexpensive, even when they create hidden costs in staff time, security exposure and reduced flexibility. Leaders should assess the total cost of ownership and the strategic constraint created by ageing technology, rather than evaluating systems only by current operating expense. Governance Should Accelerate Good Decisions Technology governance is often associated with approval processes, but effective governance should make decisions faster by clarifying accountability. The organisation should know who owns architecture standards, cybersecurity risk, data quality, vendor concentration, AI governance and investment outcomes. Current research also shows technology leadership becoming more integrated with enterprise strategy. McKinsey's Global Tech Agenda 2026 reports that nearly two-thirds of top-performing companies say technology leaders are very involved in crafting enterprise strategy, compared with 52% of other organisations. This suggests that technology governance is moving closer to the centre of corporate decision-making. Source: McKinsey Global Tech Agenda 2026 The objective should be a governance model that allows experimentation while preserving common standards. Small pilots may need lightweight approval, while enterprise-scale systems affecting regulated data, financial reporting or critical operations require deeper review. Treating every decision identically creates bureaucracy; treating every decision as an exception creates fragmentation.
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Measuring Technology Value Over the Long Term Technology programmes frequently begin with investment cases but lose measurement discipline after implementation. Long-term growth requires a clearer view of whether technology is improving the business after the launch date. Useful measures depend on the investment but may include revenue enabled by digital channels, customer retention, process cycle time, automation rates, cost-to-serve, employee adoption, system availability, cybersecurity resilience, development speed and time-to-market. Importantly, organisations should distinguish between activity metrics, such as licences purchased, and outcome metrics, such as time saved or additional revenue generated. A balanced measurement approach also recognises option value. Some infrastructure investments may not produce immediate revenue but create the ability to launch products faster, integrate data more easily or support future AI applications. Leaders should make these strategic benefits explicit rather than allowing them to remain vague assumptions. A Practical Framework for Better Technology Decisions Long-term technology decisions can be evaluated through a simple set of questions. First, what measurable business problem does the investment solve? Second, does it strengthen or fragment the existing architecture? Third, what data, skills and process changes are required for value to materialise? Fourth, how does it change cyber, vendor and operational risk? Fifth, what will the organisation stop doing or retire as a result? Finally, what metrics will determine whether the investment should be scaled, redesigned or discontinued?
This framework shifts the focus from acquisition to capability. It also helps leadership teams resist two common mistakes: pursuing technology because competitors are using it, and keeping technology simply because the organisation has already invested in it. Growth depends on making deliberate choices at both ends of the lifecycle - selecting what to build and knowing what to remove. Conclusion: Technology Decisions Compound The technology decisions that shape long-term growth are rarely limited to choosing one platform over another. They concern the architecture, data, skills, governance and operating model that determine how effectively the organisation can use technology over time. Cloud infrastructure can create flexibility, but only when architecture is disciplined. AI can improve productivity and decision-making, but only when data and workflows are ready. Cybersecurity can protect growth, but only when it is integrated into business governance. Workforce technology can raise performance, but only when employees develop the skills to use it effectively. The common principle is that technology should be managed as a compounding business capability. Organisations that align investment with strategy, measure outcomes, reduce technical debt and build complementary human and organisational capabilities are better positioned to turn technology spending into durable growth rather than a sequence of short-lived projects.
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The Cross-Border Payments Deadline: Why the World Is Still Waiting for Faster, Cheaper Transfers International payments have spent the better part of a decade being described as ripe for disruption. Domestic transfers can now move in seconds in many markets, smartphones have compressed the customer experience to a few taps, and new payment networks promise near-continuous settlement. Yet sending money across a border can still produce an old-fashioned result: uncertain fees, opaque foreign-exchange spreads, manual compliance reviews and a beneficiary who waits far longer than the underlying payment message took to travel. That gap matters more now because the policy clock is running. The Financial Stability Board (FSB) targets for enhancing crossborder payments set most of the G20 outcome targets for the end of 2027. For retail cross-border payments, the global average cost is meant to be no more than 1%, with no corridor above 3%; 75% should make funds available to the recipient within one hour, with the rest within one business day. Remittances have a similar speed ambition, while their cost target follows the UN Sustainable Development Goal of a global average below 3% by 2030 and no corridor above 5%. The uncomfortable reality is that the deadline is approaching faster than the outcomes. The FSB said in its 2025 consolidated progress report that global indicators had improved only slightly since the first KPI calculations in 2023 and that satisfactory global improvement was unlikely to arrive on the original 2027 timetable. In March 2026, the FSB moved the programme into a more implementation-heavy phase, asking authorities for jurisdictional and regional action plans and placing greater emphasis on publicprivate delivery rather than additional high-level policy design.
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The deadline was always about outcomes, not faster messaging It is tempting to judge cross-border payments by the fastest segment in the chain. That produces impressive numbers. Swift says that around 75% of payments on its network reach beneficiary banks within ten minutes, many in seconds. But the G20 target is end-to-end: the customer must actually have the money. A message arriving at the beneficiary bank is not the same thing as funds being credited to the beneficiary account. This distinction explains much of the apparent contradiction between rapid infrastructure progress and stubborn customer frustration. A payment can traverse the international messaging leg quickly and then stall at the receiving institution because of local operating hours, sanctions screening, missing beneficiary data, exchange-control rules, liquidity management, manual exception handling or legacy core-banking processes. Swift itself highlights this last-mile problem, noting that local processes can extend a payment that moved quickly between banks into an experience measured in hours or days. The evidence therefore does not show that nothing has changed. It shows that the bottleneck has moved. International messaging and correspondent-bank processing are materially faster than they were. The remaining delays are increasingly concentrated in the parts of the chain that are hardest to standardise globally: the point where a transaction meets domestic regulation, local data requirements, local banking systems and the recipient account. The global scorecard: faster in places, still expensive in aggregate The cost picture is more sobering. The European Central Bank, drawing on FSB data, reported in 2026 that for nearly one-third of the cross-border business payments in its dataset, costs exceeded 3% of the transaction value, while only about 40% of international business-to-business
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payments were settled within one working day. The ECB also noted that the global provision of correspondent banking services had declined by roughly 20% compared with the mid-2000s, a trend that can reduce choice in lightly served corridors. ECB Economic Bulletin analysis also finds that interlinking fast-payment systems is associated with higher bilateral trade, illustrating why payment efficiency is an economic infrastructure issue rather than merely a bank-service issue.
The result is a system of fast domestic islands with incomplete bridges. The BIS Committee on Payments and Market Infrastructures (CPMI) said in its May 2026 monitoring survey covering 82 jurisdictions that expanded payment-system access, longer operating hours and interoperability by design are foundational to better cross-border services. It also highlighted ISO 20022 alignment and standardised API frameworks as ways to reduce inefficiency. The important word is alignment: introducing a modern format in one market does little if every market implements it differently.
Retail transfers show the same unevenness. The Eurosystem comprehensive payments strategy says that nearly one-fifth of global retail payment corridors in 2025 still exceeded the G20 maximum-cost ambition of 3%, against a target global average of 1%. For migrants sending smaller amounts home, the World Bank Remittance Prices Worldwide programme reported a global average cost of 6.36% for sending remittances in its third-quarter 2025 data - more than twice the 3% long-term global objective.
This is why the cross-border payments problem has proved resistant to simple technological narratives. A faster rail can reduce transmission time, but it does not by itself harmonise legal liability, sanctions obligations, customer-identification rules or FX liquidity. The infrastructure can be instant while the institutional process around it remains sequential.
Those averages hide enormous corridor-level variation. Competitive digital corridors can be cheap and fast, while low-volume routes with weak local competition, cash-heavy distribution or currency controls can remain expensive. This is one reason global targets are difficult: a handful of world-class corridors cannot compensate for structurally weak ones when the policy ambition is broad accessibility and consistently low cost. Why domestic instant payments did not automatically become global instant payments Domestic instant-payment systems solved a comparatively bounded problem. Participants operate under one legal framework, one currency regime, one settlement asset and a relatively coherent set of data and consumer-protection rules. Crossborder payments add foreign exchange, multiple legal systems, sanctions regimes, anti-money-laundering obligations, datalocalisation rules, different operating hours and sometimes several intermediaries.
ISO 20022 is becoming the unglamorous centre of the reform Few payment reforms sound less dramatic than message standardisation, but richer and more consistent data may do more for the 2027 agenda than another consumer-facing app. The CPMI updated its harmonised ISO 20022 data requirements in February 2026, with adoption expected by the end of 2027. The goal is not simply to make messages more detailed. It is to ensure that banks and payment systems carry consistent structured information across the chain so that screening, reconciliation, repair and exception management can be automated rather than repeatedly reconstructed by each intermediary. Poor payment data creates real cost. A truncated beneficiary name, inconsistent address fields or unstructured remittance information can trigger manual investigation, false-positive compliance alerts and requests for clarification. Those interventions are individually rational for banks managing legal risk, yet collectively they make the system slower and more expensive. Standardisation is therefore an operating-model reform disguised as a data project. There is also a limit to what data harmonisation can achieve. Banks will still apply different risk appetites, national authorities will still interpret some requirements differently, and privacy or localisation rules can restrict data movement. ISO 20022 can reduce avoidable friction; it cannot erase legitimate differences in law and supervision.
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Compliance is not a removable friction The industry often speaks about removing friction, but some friction exists because the financial system is expected to stop illicit money, sanctions evasion, fraud and misdirected payments. The relevant question is not whether to remove controls, but whether the same control can be executed with better data, clearer responsibility and more automation. That is the direction of travel in the Financial Action Task Force revision of Recommendation 16. Agreed in June 2025, the changes standardise information requirements for certain peerto-peer cross-border payments above USD/EUR 1,000, clarify responsibilities across the payment chain and require technologies that help prevent fraud and error. The changes are due to take effect by the end of 2030, well after the G20 2027 deadline. That timing itself illustrates the coordination challenge: important global rule changes operate on a slower calendar than infrastructure innovation. For banks, this means the future of faster payments is inseparable from the future of financial-crime operations. Real-time settlement leaves less time for manual intervention. Screening, name matching, beneficiary verification and transaction monitoring need to become more precise before institutions can safely remove queues and cut-offs. Faster payments without faster risk decisions can simply move fraud faster. Interlinking fast-payment systems may be the most practical bridge One of the strongest alternatives to rebuilding global payments from scratch is to connect domestic systems that already work. The logic is simple: if two countries already have low-cost instantpayment rails, linking them can shorten the correspondent chain and allow customers to benefit from infrastructure that has already been paid for domestically.
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The BIS Innovation Hub developed Project Nexus as a standardised model for connecting instant-payment systems, with the aim of enabling most cross-border payments to reach recipients in under 60 seconds. In Europe, the ECB is using TIPS to develop cross-currency and external fast-payment links. Its cross-currency service for euro, Swedish krona and Danish krone was implemented in 2025, while work is progressing on links with systems including India's UPI and other international arrangements. The case for interlinking is strengthened by the ECB research finding that countries with connected fast-payment systems trade about 4% more with one another on average, after controlling for other factors. That is evidence of an association derived from econometric analysis, not proof that every new link will create the same gain. The inference for policymakers is nevertheless important: payment interoperability can have effects beyond consumer convenience, especially where existing cross-border payment costs are high. The counterargument is scale and governance. Bilateral links can become a web of bespoke connections; multilateral hubs can reduce technical duplication but introduce common rulebooks, shared governance and concentration questions. Interlinking also works best where participating systems have compatible access rules, operating models and compliance standards. The technology is only one layer of the agreement. Correspondent banking is changing, not disappearing New rails are often framed as replacements for correspondent banking. That is plausible in selected retail corridors, but too sweeping as a global forecast. Correspondent banks still provide deep currency liquidity, credit, treasury services, sanctions expertise and reach into markets that are unlikely to build direct system links with every trading partner. Large-value corporate payments also require features that retail instant-payment systems may not provide, including complex FX execution, liquidity facilities and richer transaction services. The more likely architecture is hybrid. Correspondent chains become shorter and more data-rich; fast-payment links handle a growing share of retail and SME flows; specialist fintechs compete aggressively on customer experience and FX; and tokenised or blockchain-based settlement is
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introduced where it solves specific coordination problems. That is an inference from the direction of current projects, not a settled end-state. Swift is itself evidence of that hybrid path. Rather than waiting to be displaced, the network has pushed ISO 20022 adoption, payment tracking, pre-validation and new retail service standards. In March 2026, Swift said more than 25 banks would participate in a retail payments framework designed to provide cost certainty, full-value delivery and end-to-end traceability across selected corridors. At the same time, Swift is exploring blockchain-based infrastructure for 24/7 cross-border payments. The incumbent network is therefore trying to improve the present architecture while creating options for a different future one. Why cost is harder to fix than speed Speed can often be improved by engineering: longer operating hours, faster clearing, better routing and automated exception handling. Cost is more political and commercial. A cross-border price contains not only technology costs but also FX margins, liquidity costs, regulatory overhead, fraud losses, customeracquisition expense, agent commissions, capital use and the economics of serving a particular corridor.
That is why some providers can make a payment technically instant without making it cheap. A customer may receive funds in seconds but still pay through a wide exchange-rate spread. Conversely, a bank may offer low explicit fees while recovering economics through FX. The G20 transparency target matters because competition cannot work well if customers cannot see the full price. Competition is therefore as important as infrastructure. Expanded access for non-banks, interoperable systems and common APIs can lower barriers to entry, but regulators must balance those benefits against operational resilience and financial-crime risk. A market with more participants is not automatically a market with lower all-in costs if access to FX liquidity or last-mile distribution remains concentrated. Stablecoins and tokenisation: catalyst, alternative or distraction? The slow progress of conventional reform has created space for a more radical argument: if existing cross-border chains are structurally inefficient, why not route around them using tokenised deposits, stablecoins or shared ledgers? The attraction is obvious. Digital settlement assets can move around the clock, support programmable workflows and reduce the need for sequential reconciliation across separate systems.
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But new settlement technology does not eliminate the core questions that slowed the old system. Users still need trusted conversion between currencies, legal finality, identity and sanctions controls, safeguarding of funds, dispute processes and regulated access points into the real economy. Tokenisation may compress the chain; it does not make governance optional. The Eurosystem's 2026 strategy explicitly takes a two-track view, improving existing infrastructure while also exploring tokenised settlement assets rather than treating the two as mutually exclusive. The practical question is therefore not which rail wins in the abstract. It is which architecture can deliver lower all-in cost and faster end-to-end availability while preserving compliance, resilience and monetary trust. In some corridors that may be a linked instant-payment system. In others it may remain a modernised correspondent model. In wholesale markets, tokenised approaches may become more important. The global system is likely to converge on interoperability among several rails, not a single universal network. What the approaching deadline means for banks For banks, the 2027 deadline should be treated less as a compliance date than as a competitive benchmark. Customers will increasingly compare international payments with the instant domestic experience they already know. Institutions that can expose total cost upfront, commit to delivery times, automate
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beneficiary validation and reduce manual exceptions will have a defensible advantage even if the global targets are missed. The investment priority is consequently not a single new rail. It is orchestration across rails. Banks need payment engines that can choose between correspondent routes, instant-payment links and emerging digital settlement options based on currency, destination, value, cost, urgency and compliance requirements. They also need cleaner reference data and stronger observability, because a bank cannot promise end-to-end performance if it cannot see where a payment is failing. What it means for fintechs, regulators and investors For fintechs, the remaining friction is an opportunity, but the easy part of the market is becoming crowded. Customer interfaces and low-cost routing are increasingly replicable. Durable advantage is more likely to come from regulatory licences, local payout reach, FX liquidity, fraud controls and direct connectivity to payment systems. The companies that can turn fragmented infrastructure into a predictable end-to-end service may capture more value than those that simply advertise faster rails. For regulators, the next phase is about domestic execution of global principles. The FSB implementation phase launched in March 2026 reflects that shift. Authorities have to decide who can access domestic systems, how operating hours can be extended, where data rules can be harmonised, how non-bank participation should be supervised and how to align consumer protection with instant irrevocable settlement. Global targets ultimately depend on national rulebooks.
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For investors, the approaching deadline is a reminder to distinguish infrastructure claims from customer economics. A provider may demonstrate impressive transaction speed but still depend on expensive FX, third-party payout networks or regulatory arbitrage. The most valuable payment businesses are likely to be those that own or secure scarce advantages at the difficult points in the chain: regulated access, liquidity, identity, compliance, distribution and interoperability.
That is the central lesson of the approaching deadline. Cross-border payments are not slow because the world lacks fast technology. They are slow and expensive because technology has to cross institutions, currencies, laws and risk frameworks that were never designed as one system. The next phase of reform is therefore less about inventing speed than making speed survive the entire journey.
The likely 2027 outcome: a missed target, but not a failed reform
The world is unlikely to wake up on 1 January 2028 to a universally instant, one-percent cross-border payment system. The G20 deadline is more likely to mark a transition from global standard-setting to corridor-by-corridor execution. That may sound less dramatic than a payments revolution, but it is probably how the revolution will actually happen.
The FSB has already prepared the market for the possibility that the global objectives will not be fully achieved on schedule. That should not be confused with zero progress. Payment messages are moving faster, domestic instant-payment systems are proliferating, ISO 20022 is becoming a common data foundation, and new cross-border links are moving from prototypes toward implementation. The reform has created infrastructure and standards that can compound over time. The more critical test is whether those improvements become visible to ordinary users. A policy programme cannot ultimately be judged by the number of standards published, pilots launched or systems connected. It must be judged by what a small exporter pays, how long a migrant family waits, whether a corporate treasurer can predict settlement, and whether a payment reaches the right account without a manual investigation.
Conclusion
Banks will shorten chains, interlink domestic systems, improve data and automate compliance. Fintechs will exploit gaps in price and service. Regulators will have to make access and rulebooks more interoperable. New digital-money rails will compete with, and increasingly connect to, existing infrastructure. The winners will not necessarily be those with the fastest technology. They will be the institutions that can make the entire cross-border transaction - from quote to final credit - behave like one coherent service.
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Who Is Responsible When an AI System Rejects Your Loan? A consumer applies for a loan on a phone, connects a bank account, consents to a credit check and receives a rejection before the kettle boils. Behind that apparently simple answer may sit a bank's underwriting policy, a fintech interface, a credit-bureau file, an alternative-data feed, a fraud model, a machine-learning score and a vendor's decision engine. If the result is wrong, discriminatory, inexplicable or based on bad data, who is responsible? The intuitive answer - the algorithm - is legally useless. Software has no licence to lose, no board to question and no customer complaint desk. Accountability attaches to the organisations that design, deploy, supply data to, rely on and supervise the system. The harder question is how that responsibility is divided when several firms participate in a decision that no single employee fully reconstructs in real time. That division is becoming clearer, but not uniform. In the United States, current Regulation B still requires creditors to give specific reasons for adverse action, while bank regulators make clear that outsourcing does not outsource compliance. In Europe, dataprotection case law has pushed accountability upstream toward credit scorers, and a new consumer-credit regime will add explicit rights to human intervention and review from 20 November 2026. The EU AI Act adds another layer, although its key high-risk requirements for Annex III systems were delayed in July 2026. The result is not one global rule, but a common direction: automated lending must remain attributable to accountable humans and legal entities.
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The first principle: a lender cannot point at the machine For a regulated bank, the starting point is blunt. The Federal Reserve, FDIC and OCC say in their interagency guidance on third-party relationships that using a third party does not diminish a banking organisation's responsibility to operate safely and comply with applicable law to the same extent as if the activity were performed in-house. That matters because many AI lending stacks are assembled rather than built: a bank may buy the score, rent the model, outsource the onboarding interface and rely on a cloud provider, yet still own the regulated activity. Responsibility can also overlap. Under the current Regulation B definition of a creditor, a person that regularly participates in a credit decision including by setting the terms of credit - can itself be a creditor. The official interpretation says the term includes all persons participating in the credit decision. A fintech that merely supplies generic software may therefore occupy a different legal position from a fintech that determines eligibility, sets pricing or materially participates in underwriting. The commercial label on the partnership is less important than what each party actually does. This creates an accountability stack rather than a single accountable actor. The bank cannot contract away its own regulatory duties. A vendor may separately face contractual, data-protection, consumer-reporting or AIprovider obligations. A credit bureau can be responsible for the accuracy and handling of its data. Senior management remains responsible for governance and escalation. When a system fails, regulators and courts can ask several different questions at once: who made the credit decision, who supplied the decisive data, who controlled the model, who could have stopped the outcome and who owed the consumer a remedy?
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In US law, the rejection notice is where accountability becomes visible US law does not give every rejected applicant a right to inspect a lender's source code. It does, however, force the lender to translate a denial into a humanly intelligible reason. Current Regulation B section 1002.9 requires adverse-action reasons to be specific and to identify the principal reason or reasons. Saying that an applicant failed to meet an internal policy or did not achieve a qualifying score is insufficient. The official interpretation adds a crucial constraint for automated underwriting: the reasons disclosed must relate to and accurately describe factors that were actually considered or scored. That distinction is important. An adverse-action notice is not the same thing as a complete technical explanation of a model. Regulation B does not require the creditor to explain every mathematical step or disclose proprietary code. But a model that cannot reliably map its output back to the real factors that drove the decision creates an operational compliance problem. If the production system says no because of variable A, while the notice generator selects a plausible-sounding variable B, the institution has not merely produced a weak explanation; it may have produced an inaccurate one. US regulatory update: do not rely on superseded AI circulars The CFPB's 2022 circular on complex algorithms and its 2023 circular on adverse-action notices were withdrawn on 12 May 2025. They should not be presented as current CFPB guidance. The underlying notification rule remains in the current text of Regulation B:
reasons must be specific and tied to factors actually considered or scored.
A second US regime can matter when a consumer report contributed to the decision. The Fair Credit Reporting Act requires users of consumer reports to notify consumers when adverse action is taken on the basis of such a report. The FTC's current business guidance explains that the notice identifies the consumer reporting agency, tells the consumer that the agency did not make the lending decision, and gives rights to obtain and dispute the report. This is a different accountability channel: the lender owns the decision, while the consumer can challenge the underlying file with the reporting agency. The US fair-lending backdrop also changed in 2026. A CFPB final rule published on 22 April and effective 21 July 2026 states that ECOA does not recognise disparate-impact liability and removes the regulation's effects test. Intentional discrimination and disparate treatment on a prohibited basis remain unlawful under Regulation B. The change narrows one federal theory of liability; it does not make model governance optional. Other federal statutes, state laws, contractual duties, prudential expectations and reputational risks may still matter, and inaccurate adverse-action reasons remain a separate issue. Europe is pulling the upstream score into the accountability chain Europe approaches the same problem through a denser combination of data protection, consumer-credit law and AI regulation. The GDPR says a person generally has the right not to be subject to a solely automated decision that produces legal or similarly significant effects, subject to specified exceptions and safeguards. Recital 71 uses the automatic refusal of an online credit application as an explicit example. Where the contractual-necessity or consent exceptions apply, Article 22 requires safeguards that include human intervention, the ability to express a point of view and the ability to contest the decision.
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The Court of Justice of the European Union has made clear that responsibility cannot always be parked at the final lender. In the 2023 SCHUFA judgment, the Court held that an automatically generated probability score can itself amount to automated individual decision-making where the third party receiving the score draws strongly on it to establish, implement or terminate a contractual relationship. In other words, an upstream score can become legally significant when it effectively determines the downstream answer. The Court went further on explainability in its February 2025 Dun & Bradstreet Austria judgment. It said that meaningful information about the logic involved in automated decision-making must explain the procedure and principles actually applied in a concise, transparent and intelligible way so the individual can understand how personal data were used to produce the specific result. A complex formula dump is not enough. This does not amount to a universal right to source code; it is a requirement for an explanation that makes the specific automated outcome understandable and contestable. A further shift arrives soon. Article 18 of the EU Consumer Credit Directive 2023/2225 requires Member States, where creditworthiness assessment uses automated processing of personal data, to give consumers the right to obtain human intervention from the creditor, a clear and comprehensible explanation of the assessment and its logic and risks, the ability to express their view, and a review of both the creditworthiness assessment and the lending decision. Member States were required to transpose the directive by 20 November 2025, and the measures are to apply from 20 November 2026.
Actor
Where responsibility usually attaches
Typical failure that exposes the gap
Lender / creditor
Credit policy, eligibility rules, pricing, final adverse action, notices, oversight of third parties.
A model is deployed without sufficient testing; notice reasons do not match production drivers; complaints cannot trigger meaningful review.
AI or decision-system vendor
Model design, documentation, change control, performance evidence and contractual obligations. It may also have direct regulatory duties depending on role and jurisdiction.
Opaque updates, undocumented feature changes, weak reason-code mapping, unreported model drift or subcontractor changes.
Credit bureau / data provider
Accuracy, provenance and dispute handling for data it supplies, subject to applicable consumerreporting and dataprotection rules.
Incorrect identity match, stale balance, corrupted attribute or an unexplained score that materially drives the decision.
Human reviewer / operations team
Meaningful review, authority to correct data, override where appropriate, record rationale and escalate recurring defects.
Rubber-stamp review, no access to relevant evidence, no authority to change the outcome, or no audit trail.
Board and senior management
Risk appetite, governance, accountability structure, vendor oversight and assurance that consumer outcomes are controlled.
Responsibility is diffused across model risk, compliance, data and product teams until no one owns the end-to-end decision.
EU AI Act timing changed in July 2026 The EU AI Act classifies AI used to evaluate the creditworthiness or credit score of natural persons as a high-risk use case, subject to the Act's detailed conditions and exceptions. However, Regulation (EU) 2026/1744, which entered into force on 27 July 2026, moved the application of key Chapter III high-risk requirements for Annex III systems to 2 December 2027. The delay does not suspend GDPR or sector-specific consumer-credit obligations.
Where accountability sits in an AI lending stack The practical mistake is to search for one entity that is responsible for everything. Modern lending systems distribute functions, but regulators usually assign duties according to role. The following map is a governance view rather than a universal statement of legal liability; the exact answer depends on jurisdiction, contract and facts.
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The table shows why contractual indemnities are not the same as regulatory accountability. A bank may obtain compensation from a vendor after a defective model causes losses, but that contract does not erase the bank's duty to oversee the activity. Conversely, a vendor that materially participates in the credit decision may not be able to avoid direct obligations merely by describing itself as a technology supplier. The facts of the workflow matter. A human in the loop can still be a rubber stamp As regulators demand human intervention, institutions face a subtle temptation: insert a person at the end of the workflow and declare the system non-automated. That can be governance theatre if the reviewer sees only the model's recommendation, lacks access to the underlying data, has no practical authority to override it or is measured almost entirely on speed. Meaningful review requires more than a click. The reviewer needs enough information to identify the relevant drivers, a route to correct bad data, authority to change or escalate the outcome, and a record of what happened. Inference from the emerging European framework is straightforward: if the point of human intervention is to let a consumer challenge an automated assessment, the human must be capable of changing something that matters. A human who cannot alter the decision is a control in name rather than substance. There is also a statistical warning sign. If a supposedly meaningful review process handles large volumes but almost never changes an automated outcome, that does not by itself prove the process is defective. It should, however, prompt questions about reviewer independence, information quality, incentives and thresholds. Override rates are not a compliance target, but they can be a useful diagnostic when read alongside complaint themes, error rates and data corrections. The hardest problem is not explainability. It is decision provenance The debate over explainable AI often focuses on whether a complex model can produce a reason code. That is only part of the challenge. A bank needs to reconstruct the decision that was actually made, not a generic approximation of how the model usually behaves. That means preserving decision provenance: the model version, input data, feature transformations, thresholds, policy rules, external scores, reason-code logic and any manual intervention that existed at the time of the application.
This becomes especially difficult when a lending journey combines several models. A fraud model may block an application before the credit model runs. A cash-flow model may generate attributes that feed a second score. A policy engine may override the model because of a minimum income rule. A third-party score may be refreshed between application and review. If the institution cannot identify which component actually caused the adverse action, the consumer-facing explanation can drift away from the production reality. For this reason, explanation should be designed as part of the decision architecture rather than bolted onto it after launch. Each production decision needs an auditable path from source data to feature to model or rule to outcome to notice. That path is also what internal audit, compliance, model risk and customer-service teams need when they investigate a complaint. The same infrastructure therefore serves legal defensibility, operational resilience and customer trust. Britain is taking a principles-based route The UK illustrates a different regulatory philosophy. The Information Commissioner's Office says the data-protection provisions of the Data (Use and Access) Act 2025 are now in force. The Act broadens the lawful bases available for significant automated decisions while retaining safeguards. In financial services, the FCA said in June 2026 that it intends to rely on existing frameworks including the Consumer Duty, the Senior Managers and Certification Regime, and governance and control expectations rather than create a separate AI rulebook. That approach reinforces a broader point: accountability does not depend on a regulator writing the word 'AI' into every rule. Existing duties around consumer outcomes, senior management, data protection, creditworthiness and outsourcing can attach to an automated system because the system is part of the regulated firm's activity. Technology changes the evidence and control problem; it does not automatically change who is answerable for the business outcome. The innovation counterargument: opacity can be the price of better prediction Lenders and model developers have a legitimate counterargument. More complex models can capture interactions that simpler scorecards miss, and alternative data can potentially help evaluate applicants with thin conventional credit files. Forcing every decision into a small set of easyto-explain variables could reduce predictive power, slow approvals or discourage experimentation. A rule that effectively mandates simple models could therefore protect explainability at the expense of access or price competition.
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But the choice is not necessarily between a transparent bad model and an opaque good one. The regulatory question is whether an institution can make a consequential decision and still produce faithful reasons, detect errors, handle disputes and demonstrate control. The 2025 Dun & Bradstreet judgment is instructive because it rejects two extremes at once: a controller cannot satisfy transparency merely by providing a complex formula, yet meaningful information does not require dumping the entire algorithm on the consumer. The target is intelligibility about the specific result. Trade-secret protection raises a similar tension. Vendors may reasonably resist disclosing proprietary model details to customers or competitors. Banks, however, cannot manage what they are contractually prevented from understanding. A workable middle ground is tiered transparency: consumers receive clear, decision-specific reasons; the lender receives enough technical documentation, testing access and audit rights to govern the system; regulators and independent reviewers can obtain deeper evidence when legally entitled. Opacity cannot be the business model for accountability.
testing reason-code logic before launch and after material model changes, including edge cases where multiple rules and models interact. It also requires retaining enough historical data to reproduce a challenged decision months later. Vendor contracts need to support that architecture. Audit rights, change notifications, access to model documentation, data lineage, incident reporting, performance monitoring and subcontractor transparency are not procurement boilerplate when the vendor touches credit decisions. The Federal Reserve's third-party guidance specifically emphasises the bank's need for timely, accurate and comprehensive information, rights to audit and remediation, and ongoing monitoring. If a vendor will not provide the information needed to comply, the vendor may be commercially convenient but operationally unusable for a regulated credit decision.
What defensible AI lending looks like
For fintechs, the key question is role clarity. A company that presents itself as a neutral software layer should examine whether, in practice, it is setting terms, determining eligibility or otherwise participating in the credit decision. That can change the legal analysis. Fintechs also have an incentive to make governance a product feature: versioned model cards, reproducible decisions, configurable reason codes, audit logs and structured complaint feedback can become differentiators when bank partners are choosing systems they can defend to supervisors.
For banks, the core design principle is reason fidelity: the reason given to the applicant should be generated from the same production evidence that drove the adverse action, not from a separate explanatory model that merely resembles it. That requires
For regulators, the challenge is to supervise the chain without assuming that every model is a monolith. A harmful outcome may originate in source data, feature engineering, policy rules, a vendor update, human override or the combination of several components. Supervision that asks only for a
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model validation report can miss the decision system around the model. The more useful question is whether an institution can trace a real consumer outcome end to end and show who owned each control.
A credit bureau or data provider can be answerable for the data it supplies. Senior management is responsible for governance, and a human reviewer is only meaningful if the reviewer can understand, challenge and change the outcome.
For investors, automated underwriting should be treated as a governance and contingent-liability issue, not merely a productivity story. A lender that approves faster but cannot explain denials, reconstruct decisions or control vendor changes may be accumulating legal, remediation and reputational risk off balance sheet. Conversely, strong decision provenance can be evidence that a firm's AI advantage is operationally durable rather than dependent on fragile black-box infrastructure.
The emerging global standard is therefore less about giving algorithms legal personality than about preventing institutions from hiding behind them. US law focuses heavily on accurate, specific adverse-action reasons and third-party oversight. European law increasingly connects explanation and review rights to upstream scoring as well as downstream decisions. The UK is using existing outcome and accountability frameworks rather than a bespoke AI code. Different routes are converging on the same principle: if a machine can say no, a responsible institution must still be able to say why and stand behind the answer.
Conclusion: the algorithm is not the accountable party When an AI system rejects a loan, responsibility rarely belongs to one actor alone. The lender remains accountable for the regulated lending activity it chooses to automate. A fintech may acquire its own obligations if it materially participates in the credit decision.
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The $35 Trillion Stablecoin Illusion: How Much Is Actually Used in the Real Economy? The $35 trillion number is real - and still misleading
A blockchain transfer is not the same thing as an economic transaction
Stablecoins generated one of the most arresting payments statistics of 2025. In an April 2026 speech, the Bank for International Settlements said stablecoin transaction volumes had reached about $35 trillion annually in 2025. In the same paragraph, however, the BIS estimated payment-related flows at only around $390 billion. That is barely more than one dollar of payment activity for every ninety dollars in the headline total.
The distinction has become important enough for the BIS to devote a 2026 working paper to it. The anatomy of stablecoin transactions separates stablecoin transfer events from the broader blockchain transactions in which those transfers are embedded. A single on-chain transaction can bundle several token transfers and other smart-contract actions. Counting each visible movement as if it were a separate payment can therefore exaggerate economic activity.
The later BIS Annual Economic Report 2026 used an estimated $28 trillion for 2025 rather than $35 trillion and stressed that values fall sharply when transfers between wallets owned by the same party are removed. The difference between two authoritative BIS figures is not a contradiction so much as a warning about measurement: totals depend on chain coverage, wallet attribution, filtering rules and whether analysts count transfer events or economically distinct transactions.
The same issue appears when addresses are treated as if they were people or companies. Exchanges, custodians, market makers and protocols often control many addresses. Funds may be swept between hot wallets, cold wallets, liquidity pools and internal treasury accounts without any new buyer, seller, employee or supplier entering the picture. Blockchain data is transparent at the address level but incomplete at the economic-identity level.
That measurement problem is the core of the illusion. A blockchain records movement with extraordinary precision, but it does not automatically tell an analyst why the movement occurred. A transfer of $10 million in stablecoins may represent a corporate payment, a crypto exchange moving its own liquidity, a trader repositioning collateral, an automated smart contract, or the same underlying value moving through several addresses before reaching its economic destination.
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Inference: the stablecoin market is unusually easy to overstate because the ledger makes every technical movement visible. Traditional payment statistics are usually produced after institutions classify transactions by purpose and counterparty. Public blockchains expose the raw plumbing first and force researchers to reconstruct economic purpose afterwards.
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Even adjusted stablecoin volume is not the same as realeconomy payments
reinforces the central point: transaction volume should not be read as a direct measure of day-to-day economic adoption.
Visa has tried to narrow the gap with an adjusted methodology developed with Artemis, Allium Labs and Castle Island Ventures. Its stablecoin analytics framework filters activity such as highfrequency trading bots, exchange treasury rebalancing and repeated smart-contract transactions. The result is dramatically lower than unadjusted volume - but still much larger than a conventional measure of merchant, payroll or supplier payments.
The $390 billion figure is small relative to the hype, not small in absolute terms
Visa reports roughly $33 trillion of overall stablecoin volume over a recent twelve-month window versus about $10.2 trillion after adjustment. Yet the same analysis says 36% of adjusted volume in 2025 came from deposits and withdrawals at centralised exchanges. That is economically meaningful activity, but it is not the same as a consumer buying goods, a company paying a supplier, or a migrant sending money home. The retail picture is smaller still. Visa has previously reported that retail-sized transactions represented less than 1% of adjusted stablecoin volume over the twelve months through March 2025. Size is an imperfect proxy - a small transfer can be investmentrelated and a very large transfer can be commercial - but it
The BIS estimate of around $390 billion in payment-related stablecoin flows during 2025 is the more revealing number for the real economy. It suggests that actual payments remain a small minority of stablecoin activity, but $390 billion is not trivial. It is large enough to support specialised crossborder corridors, business-to-business settlement, treasury transfers, cardlinked spending and dollar access in markets where traditional banking is expensive or constrained. The Federal Reserve has shown how a payment stablecoin can shorten some cross-border chains by allowing users or smaller institutions to transfer a dollar-linked token directly while large international banks provide conversion liquidity. That model does not eliminate foreign-exchange costs, compliance, on- and off-ramp fees or the need for reliable liquidity. It changes where those functions sit. A separate Federal Reserve review of stablecoins in 2025 noted growing links between stablecoin infrastructure and traditional payment providers, including partnerships that let businesses transact or hold payment balances in stablecoins. This is evidence of commercial experimentation. It is not evidence that stablecoins have already displaced cards, bank transfers or domestic instant-payment systems at scale.
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Why crypto trading still dominates the ledger Stablecoins solved a genuine problem inside crypto before they solved one in the wider economy: traders needed a dollar-like settlement asset that could move between exchanges and blockchains without relying on a bank transfer every time. That made stablecoins useful as quote currency, collateral, liquidity and a bridge between cryptoassets. The BIS describes them as a dominant medium of exchange within the crypto ecosystem, and its 2026 work shows how deeply stablecoin activity is intertwined with trading and programmable financial operations. This explains why a token with a market capitalisation in the hundreds of billions can generate transfer volume many times larger than its outstanding supply. The same dollar-equivalent token can change hands repeatedly as traders rebalance, post collateral, arbitrage prices, move assets between chains and settle positions. High velocity is not a defect. It simply answers a different question from the one implied by a headline about payments adoption. The BIS also noted in April 2026 that about 98% of stablecoins were denominated in US dollars. That dollar dominance helps explain another non-commercial use: stablecoins as offshore stores of value, especially in economies where access to dollars is limited or local currencies are volatile. Holding a dollar stablecoin can be economically important even when the holder never uses it to buy a product. The counterargument: payment adoption can accelerate faster than current shares suggest It would be equally misleading to conclude that stablecoins are irrelevant to payments because current real-economy use is a small share of on-chain volume. The infrastructure is being built precisely because companies expect payment use to grow. The United States enacted the GENIUS Act in July 2025, establishing a federal framework for payment stablecoins with one-to-one reserve requirements for permitted issuers. In Europe, MiCA has
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created a supervisory regime for relevant asset-referenced and e-money tokens. Regulation does not guarantee adoption, but it reduces one barrier to institutional use. Financial markets appear to take the competitive threat seriously. An IMF working paper published in March 2026 estimated that US legislative developments supporting stablecoin payments reduced the market value of listed incumbent payment firms by 18%, or roughly $300 billion, in the authors' event-study framework. That is not a forecast of future market share, but it is evidence that investors believe stablecoins could reshape payment economics. The Federal Reserve's July 2026 conference on the international role of the dollar likewise highlighted research suggesting that stablecoin rails may lower the cost of certain cross-border transactions and could reinforce the dollar's international reach. Federal Reserve conference summary. The plausible future is therefore not that today's $390 billion stays fixed, but that real-economy payment use grows from a comparatively small base. Regulation will make the volume easier to trust - but not easier to interpret As stablecoins move closer to regulated payments, data quality should improve. Permitted issuers and regulated intermediaries will have stronger customer-identification, reserve, reporting and compliance obligations. In June 2026, US regulators proposed customer identification program requirements for certain payment stablecoin issuers under the GENIUS Act framework. The European Banking Authority is similarly developing the supervisory architecture around significant tokens under MiCA. But better regulation will not collapse all stablecoin activity into a single clean category called payments. A regulated stablecoin can still be used for exchange settlement, securities trading, collateral, tokenised assets, treasury transfers and cross-border liquidity management. The ecosystem may become more institutionally mature while remaining economically heterogeneous.
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What the real-economy metric should measure The most useful future measure will not be the largest possible on-chain number. It will be the volume that can be linked to economically distinct counterparties and identifiable payment purposes: merchant settlement, payroll, remittances, supplier payments, cross-border invoices, treasury disbursements and other transfers where the stablecoin is functioning as money rather than as trading infrastructure. Researchers will also need to avoid double counting when the same value passes through exchanges, bridges or several wallets before final settlement. That is why the distinction between gross, adjusted and paymentrelated volume matters. Gross volume is useful for understanding blockchain load and liquidity. Adjusted volume is useful for approximating organic user activity. Payment-related volume is the metric that matters most when comparing stablecoins with cards, bank transfers, instant-payment systems or remittance networks. None of the three is inherently wrong; the mistake is using one as a substitute for another. What the gap means for banks, fintechs, regulators and investors For banks, the danger is reacting to the $35 trillion headline rather than the underlying use cases. Stablecoins are not yet processing $35 trillion of commerce, but they are proving that dollar-linked value can move continuously across programmable networks. Banks should focus on the segments where that functionality is genuinely superior - cross-border treasury, digital-asset settlement, after-hours liquidity and programmable workflows - while improving instant payments and tokenised deposit capabilities of their own. For fintechs, the opportunity is similarly narrower and more practical than the headline suggests. The strongest products are likely to solve specific frictions in conversion, compliance, reconciliation and distribution rather than simply advertise blockchain throughput. A stablecoin payment is only competitive if the full journey from fiat into the token and back out again is cheaper, faster or more useful than the alternative.
For regulators, measurement is itself a policy issue. Gross transfer data can overstate retail adoption while underestimating the systemic importance of large institutional flows. Supervisors need transaction classifications that capture who ultimately bears risk, where reserves sit, how quickly redemption can occur and whether activity is concentrated in exchanges, payments, tokenised markets or offshore dollar demand. For investors, the $35 trillion illusion cuts both ways. It can inflate narratives about immediate disruption, but dismissing stablecoins because only a small fraction of activity is currently commercial would also be a mistake. The important signals are growth in payment-specific volume, stable recurring users, corporate treasury adoption, regulated distribution, merchant settlement and the economics of converting between stablecoins and bank money. Conclusion: the smaller number may matter more Stablecoins did not process $35 trillion of real-economy payments in 2025. The BIS's own analysis makes that clear. The headline figure describes a high-velocity on-chain financial ecosystem in which the same tokens support trading, collateral, exchange operations, transfers and payments. Once analysts isolate payment-related flows, the number falls by almost two orders of magnitude. But the correction should sharpen the debate, not end it. Roughly $390 billion of estimated payment flows already represents a meaningful market, especially given stablecoins' advantages in 24/7 settlement, programmability and access to dollar liquidity. The key question is no longer whether stablecoins move large amounts of value. They clearly do. It is whether a growing share of that movement escapes the crypto loop and becomes embedded in ordinary economic activity. That is the number banks, payment companies, regulators and investors should watch. The future of stablecoins will be determined less by how impressive the blockchain ledger looks in aggregate and more by how often businesses and households choose stablecoins when they have a real invoice, wage, remittance or purchase to settle.
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Who Owns the Checkout? The New Business Battle for Payments For decades, payment infrastructure was mostly invisible to the customer. A shopper chose a card, a merchant accepted it and a chain of banks, processors and networks moved the transaction through authorisation, clearing and settlement. The commercial power sat with the institutions that controlled the rails. That structure is now being unbundled. A July 2026 BIS study found that digitalisation has brought new entrants and new technologies into retail payments even as incumbent banks and card networks retain dominant positions in important markets. For business leaders, the important question is no longer simply which payment method grows fastest. It is who controls the customer interface, who decides how a transaction is routed, who captures the data and who earns the economics around the payment. That makes payments a corporate strategy issue, not merely a back-office utility. Payments are becoming a customer-ownership contest The moment of payment is one of the most valuable points in a customer relationship. It is where intent becomes revenue, where loyalty can be reinforced or lost, and where a business can learn how, when and through which channel a customer prefers to transact. Companies that control that moment can influence conversion, repeat purchase, cross-selling and pricing power.
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This is why banks, card networks, fintechs and technology platforms increasingly overlap. Banks want to preserve the account relationship. Card networks want to remain the default route between buyers and sellers. Fintechs want to simplify the complexity of multiple rails. Technology platforms want to own the device, wallet or checkout environment where the customer makes the choice. The payment stack is being unbundled A modern payment is not one service. One company may provide the wallet, another the merchant checkout, another fraud screening, another routing, another foreign-exchange conversion and another the settlement infrastructure. As more of these functions become modular, businesses can combine providers rather than accept a single end-to-end stack. That fragmentation shifts power toward companies that can coordinate multiple routes. GBAF has described the growing importance of payment orchestration, where merchants and financial institutions connect processors, banks, local methods and networks through a common layer. For businesses, orchestration matters because routing can become a software decision based on cost, conversion, fraud, geography or customer preference.
BUSINESS
The strategic consequence is subtle but important: the company that chooses the route can become more influential than the company that owns the route. A merchant may care less about which rail settles a transaction if the payment succeeds quickly, reconciliation is clean and the total cost is acceptable.
Europe has moved further toward making instant account-to-account payments a standard capability. The Eurosystem says its TIPS platform provides 24/7/365 settlement in central-bank money, while the EU Instant Payments Regulation is designed to make instant euro transfers broadly available.
Banks are rebuilding their position with instant payments
For businesses, these rails create a credible alternative to card-based payments in use cases where speed, liquidity visibility and lower transaction costs matter. They also give banks a way to defend the value of the deposit account by making the account itself a faster payment instrument.
Banks were once vulnerable to the argument that account-based payments were too slow for digital commerce. That weakness is diminishing as real-time systems allow commercial-bank money to move in seconds, around the clock. In the United States, the Federal Reserve reported that 1,192 institutions had joined FedNow by the end of 2024, up 33.5% from a year earlier, and that the service processed about 1.5 million transactions during 2024. In April 2026, the Fed also proposed allowing intermediaries in FedNow transfers, noting that the change could support private-sector cross-border solutions in which FedNow handles the US domestic leg. Federal Reserve proposal.
Why card networks remain difficult to displace Cards survive because they solve more than money movement. They bundle global acceptance, authentication, dispute handling, fraud rules, tokenisation, credential management and a familiar customer experience into a system that works across borders and channels. Visa and Mastercard are therefore not standing still while instant payments expand. Their investor materials increasingly emphasise tokenisation, value-added services, fraud tools, open-banking capabilities and new forms of account-to-account or push payments. See Visa investor materials and Mastercard annual reports.
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At the same time, merchant economics remain under scrutiny. The UK’s 2026 annual report on concurrency records findings around increased UK-EEA cross-border card-not-present interchange fees following Brexit. The broader business lesson is that stronger alternative rails can put more pressure on incumbent pricing.
For corporate strategists, this is the key Big Tech lesson: owning the interface can be more valuable than owning the regulated balance sheet. A technology platform can capture customer attention and merchant distribution while leaving settlement, credit and regulated money to financial institutions.
Fintechs are trying to own the control layer
The real business prize is routing economics
Many fintechs do not need to replace a card network, bank or central-bank infrastructure. They can create value by sitting above them. Payment service providers and orchestration platforms increasingly compete on their ability to make multiple rails look like one service to the merchant.
As payment choice expands, merchants are likely to maintain portfolios of routes rather than choose one network. A transaction might travel over a card when international acceptance and consumer protections matter, over an instant rail when cost and immediacy dominate, through a wallet when conversion improves, or through a local method when customer preference makes it essential.
That position can be commercially powerful. If the merchant becomes indifferent to the underlying rail, networks compete more visibly on price and service. If the orchestration platform becomes the default gateway, it can accumulate transaction data, optimisation insight and bargaining power. In other words, fintechs can turn infrastructure into a commodity while making the software layer more valuable.
Software can increasingly make those decisions dynamically. This gives businesses a new lever over payment costs and performance. It also changes the economics of the industry: banks can monetise real-time account infrastructure, card networks can sell trust and intelligence, fintechs can monetise routing and integration, and Big Tech can influence default choices at the interface.
Big Tech is competing for the interface
Cross-border payments remain the hardest market to simplify
Apple demonstrates how a company can influence payments without becoming a bank or owning the underlying card rail. Apple states that cards used in Apple Pay are provided by participating issuers. Yet control of the iPhone, Wallet and checkout experience gives Apple a strong position at the moment when the customer decides how to pay.
Domestic instant payments prove that money can move cheaply and rapidly within one jurisdiction. Cross-border payments remain harder because the problem includes foreign exchange, sanctions and AML controls, data standards, regulatory fragmentation and liquidity. The FSB’s 2025 crossborder payments progress report found that major policy-development milestones had been achieved but that end users had seen only limited global improvement since the first KPI calculations in 2023.
That control has also attracted competition scrutiny. In 2024, the European Commission made Apple commitments legally binding, opening access to iPhone NFC functionality for competing mobile wallets in the European Economic Area. The acceptance layer is changing too. In June 2026, Apple said Tap to Pay on iPhone had enabled tens of millions of merchants in more than 50 countries and regions to accept contactless payments without separate payment hardware.
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In March 2026, the FSB launched a new implementation phase based on deeper public-private cooperation. That is strategically important because no single company can solve cross-border payments alone; the commercial opportunity belongs to firms that can connect regulatory, liquidity and technology systems across markets.
BUSINESS
What businesses should do differently For companies outside financial services, payments should increasingly be treated as a strategic capability. The choice of provider can affect checkout conversion, customer experience, fraud losses, working-capital timing, international expansion and the quality of transaction data available to management. Businesses should therefore avoid thinking only in terms of headline processing fees. The more useful measure is the full economics of a successful transaction: approval rates, fraud, disputes, reconciliation, liquidity, customer support, failed payments and the ability to route intelligently across markets. The strongest payment strategy may also become multi-provider by design. Companies that can switch between rails, wallets and processors are less dependent on a single network and better positioned to negotiate cost and optimise performance. That flexibility is becoming a form of commercial resilience. The winners may be the companies that make the rail invisible The next phase of payments is unlikely to produce one universal winner. Banks, card networks, fintechs and technology companies each possess different strengths. Banks hold regulated accounts and credit relationships. Networks provide global acceptance and trust frameworks. Fintechs simplify complexity. Technology platforms control devices and digital interfaces. The strategic prize is moving upward in the stack. As underlying rails become faster and more interchangeable, value shifts toward the company that determines which route is used, owns the customer experience and learns from the resulting data. That is why the battle for payments now belongs in the boardroom. The transaction itself may become increasingly invisible. The power to decide how it happens will not.
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Stablecoins Challenge the Future of Bank Deposits A Monetary Contest That Is No Longer Theoretical For most of modern banking, the commercial bank deposit has been one of the least questioned pieces of financial infrastructure. Customers place money with a regulated bank, the balance can be transferred through established payment rails, and the bank uses a portion of that funding to support lending and other balance-sheet activity. The arrangement is so embedded that deposits are often treated not as a product category but as the default form of private money. Stablecoins challenge that assumption because they create another form of privately issued money that can circulate digitally outside conventional bank payment architecture. A well-designed fiat-referenced stablecoin can be transferred continuously, held in a digital wallet, programmed into software and used across blockchain-based markets. The challenge to banks is therefore not simply that customers might buy a cryptoasset. It is that some forms of money-like balances may increasingly sit outside the banking system while still being used for payments, settlement and liquidity management. (BIS, 2026) Why Bank Deposits Matter So Much Deposits are economically important to banks for reasons that go far beyond convenience. They are a major source of funding. Stable retail and commercial deposits can provide funding at a lower and more predictable cost than wholesale markets, particularly when customers value transactional convenience and safety more than maximum yield. Deposits also anchor the broader customer relationship, allowing banks to observe cash flows, offer credit, provide payments and cross-sell treasury, wealth and other services. (Nagel, 2026)
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If a meaningful portion of transaction balances migrates to stablecoins, the effect could therefore be larger than a simple substitution between two payment instruments. Banks could face a funding shift, a data shift and a distribution shift at the same time. A customer who stores value in a nonbank digital wallet may also initiate payments, access financial products and interact with financial software outside the bank’s proprietary interface. What Stablecoins Offer That Deposits Often Do Not The strongest stablecoin proposition is operational. Blockchain-based tokens can move across borders and time zones without depending on every conventional banking system being open at the same moment. They can settle within software environments, interact with smart contracts and be integrated into digital-asset exchanges, marketplaces and increasingly payment applications. (BIS, 2026) For businesses operating internationally, these characteristics can be attractive. Stablecoins can function as a bridge asset for cross-border movement, provide a dollar-linked store of transaction value in markets where access to dollars is constrained, and support treasury operations that need to continue outside local banking hours. For developers and fintech platforms, stablecoins can also be easier to embed into programmable workflows than traditional deposit accounts. But a Stablecoin Is Not a Bank Deposit The comparison has limits. A bank deposit is a claim on a regulated deposit-taking institution and, depending on jurisdiction and eligibility, may benefit from deposit-insurance protection. A stablecoin is generally a claim structured around the issuer and the quality, liquidity and legal treatment of its reserve assets. The protections are different, the redemption mechanisms are different and the consequences of issuer failure are different. (FSB, 2023)
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This matters because a token that remains worth one unit of currency in ordinary conditions can still face stress if holders doubt the quality or accessibility of the reserves backing it. The key question is not only whether the token is designed to maintain par value but whether redemption remains credible when many holders want cash simultaneously. (BIS, 2024/25)
in character. If reserves move into Treasury bills or central-bank-eligible assets, deposits may leave commercial-bank balance sheets more directly. The same stablecoin can therefore have different implications for banking depending on how its reserves are managed. (Nagel, 2026) (BIS, 2026)
The Reserve Model Creates a Link Back to Traditional Finance
The clearest banking concern is disintermediation. A household or company that converts a bank balance into stablecoins reduces deposits at the originating bank unless an offsetting deposit returns through the reserve system. If adoption became very large, banks with weaker deposit franchises could need to replace lost funding through more expensive wholesale borrowing or by competing more aggressively on deposit rates. (Nagel, 2026)
Most fiat-backed stablecoins do not eliminate conventional financial assets. They rearrange who holds them. A stablecoin issuer may receive customer funds and invest reserves in cash, bank deposits, short-dated government securities or similar high-quality liquid assets. The customer gives up a direct bank deposit and receives a token; the issuer then holds reserve assets elsewhere in the financial system. (BIS, 2024/25) This means the macroeconomic effect of stablecoin adoption depends heavily on reserve composition. If reserves are held largely as deposits at commercial banks, the funding may remain within banking but become more concentrated and wholesale
The Deposit-Disintermediation Risk
The effect would not be uniform. Banks with sticky operating accounts, strong salary relationships, lending ties or sophisticated cash-management services may retain balances more effectively. Institutions relying heavily on low-yield transactional deposits without offering equivalent digital functionality may be more vulnerable.
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Stablecoins Could Make Deposits More Price Sensitive
The Yield Question Could Decide the Competitive Battle
Even before large-scale substitution, stablecoins can change customer expectations. Money that can move continuously between wallets, platforms and financial products is less likely to remain inert purely because switching is inconvenient. As financial software becomes more capable of monitoring rates and executing transfers automatically, the traditional advantage of customer inertia weakens.
Traditional bank deposits can pay interest because banks use deposits as funding for loans and other assets. Stablecoin issuers may earn income on reserve assets, but whether that income is passed to holders depends on product design and regulation. If stablecoin holders receive little or no yield while banks offer attractive deposit rates, the case for holding large idle stablecoin balances weakens. (BIS Bulletin 125, 2026)
This could increase competition for deposits. Banks may need to pay more attention to the yield, liquidity and digital usability of their deposit products. The strategic question becomes not only whether customers trust their bank, but whether keeping money in that bank remains the most convenient and economically attractive option in a market where alternatives are increasingly machine-comparable. (BIS, 2025) Why Stablecoins May Win in Payments Before They Win in Savings Stablecoins have a particularly strong case in payment and settlement use cases where 24/7 availability and programmability matter. That does not automatically make them the preferred longterm savings product. Most stablecoins do not inherently provide the same combination of yield, credit creation, relationship services and legal protections associated with regulated banking products. (BIS, 2026) This distinction is critical. The threat to deposits may emerge first in operational balances: money held temporarily for payments, trading, cross-border settlement or digital commerce. Savings balances could prove more resistant, particularly where banks offer competitive returns and strong protection. The future may therefore be less about stablecoins replacing deposits wholesale and more about them taking over specific functions deposits previously monopolised.
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If, however, regulated digital-money products evolve in ways that allow users to receive returns indirectly through linked platforms or tokenised financial assets, the competitive gap can narrow. The boundary between a payment token and a savings product may become less clear, especially as digital wallets integrate money-market instruments and other yield-bearing assets. Tokenised Deposits Are Banks’ Most Direct Response Banks do not have to defend the deposit model by preserving its current technological form. Tokenised deposits offer a different strategy: keep the legal claim on the commercial bank while making the deposit usable in more programmable and continuously available digital infrastructure. (BIS, 2025) This approach attempts to combine familiar banking protections and balance-sheet integration with some of the operational advantages associated with blockchain-based tokens. A tokenised deposit can remain a bank liability while moving through a distributed or shared ledger environment. For institutional customers, that could support programmable settlement, treasury and digital-asset transactions without requiring a migration into non-bank money. (BIS, 2025) Stablecoins and Tokenised Deposits Solve Different Problems The market is unlikely to converge immediately on one universal digitalmoney form. Stablecoins can offer portability across platforms and public blockchain ecosystems. Tokenised deposits can preserve direct connection
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to a regulated bank and its balance sheet. Central bank digital currencies, where developed, would introduce a third model based on a direct claim on central-bank money. (BIS, 2025) Each form optimises for different priorities: openness, programmability, settlement finality, regulatory certainty, privacy, interoperability and credit creation. The most likely near-term outcome is coexistence, with different instruments serving different segments rather than a single winner replacing every other form of money. The Real Competitive Threat Is the Loss of the Customer Interface Banks should be careful not to define the stablecoin challenge only as a funding problem. The deeper threat may be distribution. If customers increasingly hold and move money through wallets, fintech applications and AI-enabled financial agents, the bank can remain important as a regulated balance sheet while becoming less visible to the end user. The institution that owns the interface can influence where balances are stored, which payment rail is selected and which financial products are offered. A stablecoin ecosystem can therefore weaken a bank’s customer relationship even if some of the underlying reserve assets eventually return to the banking system. Payments Networks Are Preparing for a Multi-Rail World The evolving payments market already points toward coexistence rather than a single replacement technology. Card networks remain globally important, real-time bank payment systems are expanding, stablecoin settlement is being integrated into institutional workflows, and banks are experimenting with tokenised forms of commercial-bank money. (BIS Project Agorá, 2026)
The competitive advantage may increasingly belong to providers capable of orchestrating among several rails while hiding complexity from the customer. In that environment, the winning asset is not necessarily the one that replaces all others. It is the one that can be used safely, cheaply and conveniently inside the broadest set of financial workflows. Regulation Will Determine How Close Stablecoins Can Move to Deposits The regulatory treatment of stablecoins will shape the competitive outcome. Requirements governing reserves, redemption, custody, disclosure, operational resilience and issuer authorisation affect how closely a stablecoin can resemble safe money. Stronger rules can increase confidence and adoption, but they can also reduce some of the regulatory arbitrage that historically separated stablecoin issuers from banks. (FSB, 2023) If stablecoin regulation increasingly demands high-quality reserves, robust redemption and strong operational safeguards, the sector could become safer while also more bank-like. That creates an unusual convergence: stablecoins become more credible competitors precisely by adopting controls long associated with regulated financial institutions. (FSB, 2023) The Financial-Stability Question At sufficient scale, stablecoins can also affect liquidity transmission. Rapid conversion from deposits into stablecoins could make bank funding more sensitive during periods of stress. Conversely, a run on a stablecoin could force rapid liquidation or movement of reserve assets. These dynamics matter because digital assets move quickly and operate continuously. (BIS, 2026) (BIS, 2024/25) The concern is not that every stablecoin creates a systemic risk. It is that a sufficiently large stablecoin can become part of the monetary plumbing. At that point, its reserve structure, redemption process and interactions with banks and government-securities markets become relevant to financial stability rather than simply crypto-market policy. (BIS, 2026)
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Emerging Markets Face a Different Stablecoin Equation In economies with volatile currencies, capital controls, limited access to dollars or expensive cross-border payments, dollarlinked stablecoins can provide a function that users may value more strongly than consumers in advanced banking systems. In these markets, the competition may not be between a wellyielding insured bank deposit and a stablecoin. It may be between constrained access to foreign currency and a digital token that can be acquired and transferred globally. (BIS, 2026) That raises the possibility of digital dollarisation. Stablecoin adoption can improve access to international money while weakening local monetary sovereignty and potentially moving savings away from domestic banks. The policy trade-off is therefore particularly sharp in emerging markets. (BIS, 2026) Banks Still Possess Powerful Advantages The stablecoin challenge should not be mistaken for an inevitable victory over banks. Commercial banks combine payments, credit, deposit protection, liquidity transformation, customer relationships and regulatory infrastructure in a way stablecoin issuers generally do not. Banks can create credit from deposits, provide overdrafts and working-capital facilities, manage complex treasury relationships and offer legally established recourse structures. (BIS, 2025)
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They also possess one of the most valuable financial assets: trust built through regulation, supervision and long operating histories. Stablecoins can compete with individual functions of a bank deposit without replicating the entire banking relationship. The Banks Most at Risk Are Those That Treat Deposits as Passive Funding The strategic danger lies in complacency. For years, many banks could treat customer balances as relatively stable even when the user experience, rate or payment functionality was mediocre. Stablecoins, fintech wallets and open-finance tools increase the number of credible alternatives. Banks that respond by improving deposit pricing, real-time payments, programmable services and tokenised money can remain central. Banks that rely primarily on inertia may discover that the future of deposits depends less on regulation protecting the old model and more on whether customers still find the product useful. Implications for Banks, Fintechs, Regulators and Investors For banks, the priority is to understand which deposits are genuinely relationship-driven and which are merely inert. They should modernise payment capabilities, explore tokenised deposits where commercially justified, improve treasury functionality and treat 24/7 money movement as an operating requirement rather than a crypto niche. (BIS Project Agorá, 2026)
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For fintechs, the opportunity lies in interoperability: connecting stablecoins, bank accounts and existing payment networks rather than assuming one rail will replace every other. For regulators, the challenge is to allow useful competition while protecting redemption, reserve quality, consumer rights and financial stability. For investors, deposit beta, funding mix, payment-fee exposure and the quality of digital treasury infrastructure will become increasingly important indicators of which banks are positioned for a multi-money environment. (FSB, 2023)
The result is likely to be a competitive monetary ecosystem. Some transaction balances move to stablecoins. Some remain in deposits. Some bank deposits become tokenised. Some wallets abstract the distinction completely and simply choose the rail best suited to the transaction.
Conclusion: The Future Is Not Stablecoins or Deposits. It Is Competition Between Forms of Money
That is the real stablecoin challenge. It is not the disappearance of the bank deposit. It is the end of the era in which the bank deposit did not need to justify itself.
The central issue is not whether stablecoins will make bank deposits disappear. They are unlikely to do so. Bank deposits remain deeply embedded in credit creation, regulated finance and customer relationships. The more meaningful change is that deposits are losing their historical monopoly as the default private money used for digital financial activity.
For banks, that future is uncomfortable because it removes an old assumption: customer money will no longer remain in a deposit account simply because that is where money has always lived. Deposits will need to compete—for yield, convenience, programmability, safety and relevance.
Stablecoins offer something banks have struggled to provide universally: portable, programmable and continuously available digital value. Banks answer with stronger payment systems, better deposit economics and tokenised deposits of their own. Regulation narrows the gap between the two models while preserving important differences in legal claims and risk. (BIS, 2026)
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Why Human Judgment Is Becoming Private Banking’s Most Valuable Competitive Advantage The commercial paradox: AI lowers the cost of expertise — and raises the bar for premium service Private banking has traditionally bundled together research, product access, portfolio monitoring, administration, relationship management and reassurance. Artificial intelligence is now pulling that bundle apart. A market briefing that once required an analyst can be summarised in seconds. A portfolio can be scanned continuously. Meeting notes, follow-up actions and client prompts can be generated automatically. The commercial implication is bigger than a productivity gain: activities that looked scarce because they consumed professional time are becoming abundant because software can perform them at near-zero marginal cost. That change arrives at a moment when the wealth market is growing but client loyalty is weakening. Capgemini’s World Wealth Report 2026 estimates that global high-net-worth wealth rose 8.7% in 2025 to $98.3 trillion and the HNWI population reached 25.3 million. Yet Capgemini also reports that only 19% of HNWIs worked with a single wealth firm in 2025, down from 39% in 2019, while 88% used multiple firms specifically to obtain better access to alternative investments. The market is larger, but the assumption that assets will remain captive to one relationship is becoming less reliable. For business leaders, that creates a strategic paradox. AI can lower the cost to serve each client and allow advisers to handle larger books. But the same technology can also make competitors faster, make clients better informed and expose weak service more quickly. The opportunity is therefore not simply to automate the old private-banking model. It is to decide which parts of that model still deserve premium economics. The first AI advantage is operating leverage, not adviser replacement The clearest evidence so far is that leading wealth managers are using AI to remove friction around the adviser rather than remove the adviser altogether. UBS says its STAAT Insights platform provides more than 5,000 US financial advisers with AI-generated client intelligence. Nearly 90% of adviser teams actively use it, the bank estimates it saves about 1,200 hours of meeting preparation each week, and the system generated more than 20 million
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AI-identified client opportunities in 2025. In Hong Kong and Singapore, a related tool consolidates client, portfolio and activity data for more than 200 client advisers. Morgan Stanley has followed the same logic. Its AI @ Morgan Stanley Debrief automates meeting summaries and action items, while the firm has said its earlier adviser assistant reached 98% adoption across financialadviser teams. The immediate business case is straightforward: less time searching for information, preparing meetings and documenting conversations; more time spent on the work clients can see. Capgemini’s 2026 research reinforces why that matters. Advisers reported that 41% of their time is consumed by operational tasks, while 76% want AI-enabled systems to automate routine work so they can focus on relationships. If firms can reclaim a meaningful share of that capacity, the economics of advice change. Larger client books become possible, support layers can shrink, and specialist expertise can be deployed more selectively. But operating leverage is not the same as competitive advantage. Once similar AI tools spread across the sector, everyone can become faster. The durable question is what a firm does with the time and capacity it frees. A private bank that uses AI merely to make the same product-driven conversations cheaper may improve margins temporarily. A bank that redirects human capacity toward high-value decisions can redesign the proposition itself. When information becomes abundant, scarce judgment becomes more valuable Generative AI compresses one of private banking’s historic advantages: privileged access to analysis. A sophisticated client can increasingly ask an AI system to explain bond structures, compare funds, model portfolio scenarios or summarise market events without waiting for a relationship manager. Information still matters, but its scarcity value is falling. The harder decisions in private wealth rarely fail because the client lacks another chart. They involve objectives that conflict. An entrepreneur deciding whether to sell a business is weighing valuation against control, identity, employees and family ownership. A founder with most of her wealth in one company may understand diversification perfectly and still resist selling. An heir may inherit assets and obligations at the same moment as grief. These are not information problems. They are decision problems.
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The strategic inference is that human value migrates toward ambiguity. As software becomes better at producing technical answers, the premium shifts toward framing the decision, revealing hidden trade-offs, challenging inconsistent preferences and helping a client act when there is no mathematically perfect outcome. That is a different capability from being the person who knows the most facts. EY’s 2025 Swiss wealth research offers a useful clue. Forty-one percent of surveyed HNW clients said they had already spent more time discussing macroeconomic developments with their adviser. The same research found rising perceived complexity across investment products, pension planning, holistic wealth and family transfers. When uncertainty rises, clients may have access to more information than ever and still want a person to prioritise what matters.
can make that role more scalable by preparing context and coordinating information, but it does not automatically replace the need for someone to be accountable for the whole picture. Family governance exposes the limits of pure automation Private wealth is not only a portfolio. It is a social system. The more wealth crosses generations, jurisdictions and family branches, the more advice becomes a governance problem. AI can draft documents, model inheritance outcomes and summarise trust structures. It is less obvious that it can credibly mediate between a founder who wants control, children who want autonomy and beneficiaries who define fairness differently.
The most defensible service may be orchestration, not product access
EY’s Swiss survey found that only 36% of HNW clients considered themselves well prepared for wealth transfer, compared with 44% globally. EY’s European research also reported that only 73% of surveyed beneficiaries in Germany planned to continue with the donor’s wealth manager. Transparent fees, tailored strategies and open communication were among the factors shaping switching decisions.
Private banks have long defended premium fees through access: private equity, private credit, structured investments, bespoke lending and institutional research. Yet digital distribution is broadening access and making product discovery easier. Capgemini’s finding that 88% of HNWIs use multiple firms for alternative-investment access is a warning that the product shelf alone is not a loyalty strategy.
This is commercially important because inherited wealth does not guarantee inherited loyalty. A relationship manager who has built trust with a founder may have very little credibility with the next generation. Technology can help the firm remember family structures and prior conversations, but the institution still has to earn trust again. That makes succession capability, communication quality and family governance more than “soft” services; they are retention infrastructure.
The more durable value may lie in orchestration. A single decision can require an investment specialist, tax adviser, estate lawyer, lending banker, philanthropy expert and family-governance adviser. Capgemini’s 2026 report argues for broader tax, estate and retirement planning and for technology that helps relationship managers coordinate specialists; 61% of advisers in its research said they want access to an integrated specialist ecosystem.
Trust is becoming less about familiarity and more about accountable oversight
That points to a more useful business model for the AI era: the private banker as the chief financial officer of a household. The banker does not have to be the deepest expert on every subject. The banker has to understand the client’s context, assemble the right specialists, reconcile conflicting recommendations, navigate the institution and make sure somebody owns the next step. AI
The choice between a human adviser and an AI system is likely to prove false. Clients can want both. EY’s Swiss survey found that 58% expected AI to become part of the advisory process, yet only 28% said they trusted AI as much as their personal adviser. Respondents across age groups expected human supervision. That is not an argument against AI; it is an argument for a hybrid trust model in which technology does more work while a visible person and institution remain responsible.
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This is where accountability becomes a commercial asset. Regulators are not treating AI as an escape hatch from existing duties. In the United States, SEC standards-of-conduct guidance continues to attach duties of care and loyalty to regulated advisers. In the United Kingdom, the FCA’s AI approach has emphasised applying existing frameworks rather than creating a separate rulebook for AI, while the Consumer Duty requires firms to act to deliver good outcomes and avoid foreseeable harm. For a premium business, the implication is broader than compliance. If a recommendation goes wrong, a wealthy client does not want to discover that responsibility is dispersed across a model vendor, a data provider, an algorithm and an institution. The firm that can use automation aggressively while maintaining a clear line of human and corporate responsibility may strengthen trust rather than weaken it. The counterargument: the industry may be overestimating the “human premium” There is a serious case that human advisers are more replaceable than wealth managers assume. Humans are expensive, inconsistent and conflicted. They can anchor on house views, prefer familiar products, overlook details and spend large amounts of time on administration clients do not value. A well-governed AI system can be available continuously, scan a wider opportunity set, remember every disclosed preference and explain fees with a consistency no individual banker can match. Regulators themselves are exploring the upside. In a February 2026 speech, the SEC’s Director of the Division of Investment Management described the possibility of adviser- or fund-provided AI agents that could translate dense disclosures into plain-English answers about investments, fees, redemptions, short positions and conflicts. If systems become reliable enough to handle those interactions directly, some functions that once justified adviser time will become software. The economic conclusion is not that every wealthy client will continue to pay for a human at every touchpoint. Hybrid models are likely to expand first where client complexity is moderate and service costs are high. Ultra-high-net-worth families with operating businesses, cross-border structures, lending needs and family-governance problems may retain a much larger human component. The market is likely to segment by complexity and consequence, not wealth alone. Pricing power will depend on making human work rarer — and better AI creates an uncomfortable pricing question. If research, portfolio summaries, routine product comparisons and basic planning become dramatically cheaper to produce, continuing to wrap them in a premium percentage fee creates a visible value gap. Clients who already spread assets across multiple firms have more opportunities to compare that gap. The stronger strategy is not to defend every legacy service as “high touch.” It is to separate commodity work from premium work. Commodity work should be automated, standardised and delivered
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quickly. Human attention should be concentrated where it changes an outcome: difficult decisions, negotiations, family alignment, institutional navigation, relationship repair and moments where a client needs someone to take responsibility rather than merely provide information. This can support a different labour model. Fewer hours are spent preparing information and more on judgement-intensive work. Client books can become larger where complexity is low, while specialist resources become denser around complex families. Adviser performance can be measured less by activity and more by retention, decision quality, specialist coordination and the client’s ability to move from discussion to execution. The operating model matters more than the chatbot The biggest implementation risk is layering AI on top of a fragmented organisation. Capgemini reports that only 17% of HNWIs describe their advisory experience as seamless and personalised, 42% say they must restate goals and preferences multiple times to the same firm, and 60% of wealth-management executives acknowledge lacking a unified client view. An AI assistant placed on top of fragmented data can make fragmentation faster without making the experience coherent. A stronger model is “machine breadth, human depth.” Software monitors the whole client book, detects relevant events, prepares meetings, drafts follow-ups and navigates institutional knowledge. Human advisers focus on complex decisions, family alignment, discretion, negotiation and highstakes execution. The technology should make the adviser more present to the client, not simply make the institution cheaper to run. That requires organisational redesign. Data has to be unified. Roles have to be clarified. Specialist networks have to be easy to access. Incentives need to reward long-term client outcomes rather than product distribution. Training has to shift from memorising information toward questioning, communication, negotiation and judgement. AI therefore becomes a management challenge as much as a technology project. The broader business lesson: when expertise becomes software, companies must redefine what people are for Private banking is an unusually clear case of a much broader business problem. In professional services, insurance, law, consulting, medicine and enterprise software, AI is reducing the cost of activities that once justified large amounts of skilled labour. The first response is usually automation. The more important response is repositioning human work around the capabilities whose value rises when routine expertise becomes abundant. For private banks, those capabilities include judgment under uncertainty, emotional intelligence, discretion, complex problem-solving, accountability and the ability to coordinate multiple experts around a client’s real objective. None is permanently immune to automation. But they are harder to commoditise because their value depends on context, trust and consequence rather than information alone. The winners may therefore be neither AI-only wealth platforms nor traditional relationship-driven banks that protect old ways of working. They are more likely to be firms that use AI aggressively enough to lower the cost of routine expertise while redesigning the human adviser around scarce, defensible capabilities. In business terms, the goal is not to preserve the human role. It is to make the human role worth paying for.
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Conclusion: the human advantage survives only if the human work improves AI is unlikely to end private banking. It is more likely to strip away the parts of private banking that were expensive because institutions were inefficient rather than because the work was intrinsically valuable. Research, preparation, monitoring and documentation are already being compressed. That should be good news for clients and uncomfortable news for any business model that treated those activities as premium service. What remains is the harder layer: judgment under uncertainty, orchestration, family governance, emotional discipline, negotiation and responsibility. Private banks that simply add AI tools may become more efficient. Private banks that redesign their business around those scarce capabilities may become more valuable. The competitive question is therefore no longer whether a human adviser can know more than a machine. The question is whether the firm can combine machine-scale intelligence with human judgment in a way that improves decisions, strengthens loyalty and justifies a premium. In an AI-rich market, that is what the human advantage has to mean.
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