Over the past decade, banks have transformed payments, moving from physical cash to digital payment channels such as cards, online banking and mobile payments. At the same time, digital assets like stablecoins and tokenized deposits are creating new payment rails, while round-the-clock systems like UPI in India, Pix in Brazil, FedNow in the US and SCT Inst in Europe settle payments instantaneously at near-zero cost.

According to our latest research report on World Payments¹, the global non-cash transaction volumes reached nearly 1.7 trillion in 2024 and are projected to hit 3.5 trillion by 2029. At the same time, more than 65 percent of payment executives recognize there is still a need to expand instant payment infrastructure.² The culmination of this innovation is a shift away from static transaction models toward dynamic, intelligent ecosystems that respond to customer behavior in real-time.

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The Future of Payments

 

Global non-cash transaction volumes are projected to hit 3.5 trillion by 2029.

FinTechs and neobanks have further changed the game. Digital asset payment rails powered by blockchain-based technologies move value globally without relying on traditional networks, delivering faster settlement, always-on operations and lower costs. Where certain types of digital assets have brought volatility and regulatory uncertainty alongside these benefits, stablecoins have emerged as a practical alternative, motivating businesses to harness them at scale by combining stability with innovation, showcased by 72 percent growth in stablecoin transaction value in 2025.³

The most significant impact of these innovations, however, isn’t speed or agility, but trust. Their adoption has proven that money can move across the globe instantly and reliably. This new paradigm is pushing Banks, FinTechs, Payment Service Providers and Digital Asset Firms, from crypto exchanges to Virtual Asset Service Providers (VASPs), to build faster, more cost-effective and accessible payment systems, with regulators under increased pressure to strengthen guidance, customer protection and advocate AI transparency.

It is also, however, creating the defining risk of the future. While global payments have moved to a real-time world, many financial crime controls have not followed suit, still siloed, reactive and built for a different, slower era. Closing this gap means re-thinking how financial crime is fought, how AI is deployed against fraud across the enterprise, how public and private institutions share intelligence, and how compliance meets regulations that measure outcomes rather than effort. This article explores how leading organizations are transforming themselves in response, building real-time resilience and securing the next generation of finance.

AI and the New Fraud Economy

Fraud in the digital asset space has exploded, driven by technological advancement and, above all, through AI. Firms are fighting synthetic identities, ID theft, deepfakes, cross-chain swaps and account takeover while managing classic Anti-Money Laundering (AML) battlegrounds like sanctions, tax evasion or cross-border movement of funds. With new typologies emerging daily, fraud has become the number one priority in the digital space.

AI itself presents both unprecedented opportunities and new risks, re-shaping financial crime programs from both ends. While AI enables sophisticated threats, it also powers some of the most advanced detection capabilities accessible to enterprises today. And the adoption is accelerating.

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The Future of Fraud Detection

 

76% of banks expect fraud detection to be an AI agent-led process within the next 18 to 36 months.

Our research shows that 64 percent of banks plan to deploy AI agents at scale in fraud detection, second only to customer service, with three in four (76 percent) banks expecting fraud detection to be an AI agent-led process within the next 3 years.⁴ The technologies involved span a spectrum, from predictive models that score risk and copilots that assist investigators to Generative AI that drafts and summarizes and, increasingly, autonomous agents. AI-agent-led refers to financial crime operations in which these agents execute multi-step tasks end-to-end, gathering information, assessing risk, documenting decisions and escalating when human judgment is needed. Our definition of an effective AI agent is one that teams and clients can trust: Understandable in how it reasons, verifiable in what it does and always under human control.

Deployment, however, is not the same as protection. The future of fraud prevention requires the right balance of human expertise and AI-powered intelligence, driving a fundamental shift from siloed investigations to real-time management of payments infrastructure itself. It means moving AI from pilot phase into governed, enterprise-wide production, with human expertise concentrated where it matters most: Judgment, escalation and emerging high-risk areas. Done well, AI doesn’t replace analysts; it replaces waiting.

This is also what we see in our work with financial institutions. The challenge is increasingly less about accessing AI capabilities and more about embedding them into live financial crime operations with the right controls, specialist oversight and governance. The organizations making progress are connecting AI with investigators, workflows and decision-making rather than deploying it as another standalone technology layer.

For several institutions, managed services are becoming one way to bring together the technology, specialist expertise and operational scale required for this shift. However, even the most advanced financial crime operations cannot fight fraud in isolation. Scams increasingly move across institutions, borders and asset classes by design, making industry-wide collaboration and intelligence sharing essential.

Public and Private Sector Collaboration

Collaboration among banks, financial institutions, FinTechs, RegTechs, neobanks and regulatory bodies is crucial, from design to implementation, to protect the overall ecosystem. The reason for this is structural: No single institution sees enough of all fraud typologies.

Promisingly, collaborative aspirations are now being realized through new guidance and infrastructure. Central banks and governing bodies sharing payments intelligence across networks, enabling effective transaction tracing and making customer behavior visible, is exactly the change underway. In recent months alone, regulators and standard-setting bodies like the Financial Crimes Enforcement Network (FinCEN) have moved to encourage fraud information sharing among institutions, with the Financial Transactions and Reports Analysis Center (FINTRAC) opening the door to private-to-private sharing in Canada and the Financial Action Task Force’s (FATF) strengthened payment transparency standard expected to apply globally by 2030.

What makes this collaboration vital is that each participant brings capabilities that the other cannot. Banks serve as trusted partners to governments and remain integral to the wider ecosystem’s liquidity. At the same time, the private sector offers the infrastructure, from trusted products, wallets and controls to governance and the security standards that protect customer data. With central banks and institutions such as the Basel Committee on Banking Supervision (BCBS) providing regulatory direction, collaboration can bring economies of scale to all participants while making the financial system more hostile to financial crime.

The Ever-evolving Regulatory Environment

This shared intelligence, however, is only truly valuable if it flows into ongoing monitoring, investigation, escalation and reporting that can act on it immediately. And this is increasingly how regulators are thinking too. Around the world, financial crime policy is undergoing a massive shift, from rule-based, check-the-box compliance procedures to risk-based, outcome-driven and effective approaches. Organizations are expected to meet their regulatory requirements with maturity, not just reporting volumes. Compliance, in short, is evolving from proving effort to proving effectiveness.

In practice, this can be achieved through the adoption of outcome-driven AML / Counter-Terrorism Financing (CTF) programs underpinned by a risk-based approach, with real-time monitoring and decision-making embedded across the control framework and human expertise and AI working in tandem. Robust AI governance sits alongside all of it. Regulators increasingly expect organizations to implement AI responsibly, with models validated before deployment, governed in production and reviewed continuously, supported by audits of performance, explainability and fairness to minimize bias and reduce false negatives. The bar, in other words, is no longer technical compliance but demonstrable effectiveness: Accountable ownership, explainable models and evidence that controls hold up under pressure.

The regulatory net is widening too. Regulations around digital assets are evolving across jurisdictions as regulators bring VASPs, crypto exchanges and stablecoin firms under supervision, with the travel rule, transaction tracing and verification of customer wallets among the areas of focus. Accountability is sharpening at the same time, with the message across jurisdictions consistent: Effectiveness will be measured, and accountability is increasingly reaching named individuals.

Operating in the Intelligent Era of Financial Crime Compliance

Securing the next generation of finance is not a technology problem, but an operational one. The institutions pulling ahead are making operating model decisions, converging fraud and AML programs into a unified intelligence function, scaling AI use cases across the enterprise and treating intelligence sharing as an operational capability. Taken together, it marks the shift from siloed, reactive investigation to real-time management of the financial crime infrastructure. This is a vital change for sustaining trust in a payments system that never stops moving.

 

THE BIGGER SHIFT

 

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Compliance itself is beginning to behave
like an intelligent operating system.

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Regulatory obligations, controls, evidence and decision-making are becoming digitally connected, enabling institutions to understand new requirements, assess risk, execute controls and generate supervisory evidence continuously.

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Getting there is no easy feat, and few institutions are attempting this journey alone. Our World Cloud Report – Financial Services 2026 finds that 67 percent of financial services firms partner with solution providers and system integrators to source AI agent capabilities. At the same time, only one-third attempt to build entirely in-house, with the operational complexity of financial crime lending itself to strategic partnerships that bring instant access to operational[RG6.1] scale, specialist investigators and governed, AI-enabled operating models.

Many organizations are already reaping the benefits of such partnership support. One leading global payment infrastructure provider, for instance, centralized its fragmented crypto financial crime investigations into a dedicated Center of Excellence (CoE), combining on-chain analysis with specialist investigators and achieving 100 percent SLA adherence from day one across Know Your Customer (KYC), transaction monitoring and SAR reporting.

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The Power of Partnership

 

67% of financial services firms partner with solution providers and system integrators to source AI agent capabilities.

In this AI-led era, financial crime will continue to evolve at the speed of the payments it exploits. The institutions set to thrive and secure the next generation of finance will be those equipped to operate just as fast, and just as intelligently. Capgemini’s Intelligent Business Operations (IBO) approach combines compliance, intelligent operations and AI-driven capabilities to help financial institutions adapt to evolving regulatory requirements, manage risk, strengthen controls and continuously generate supervisory evidence.

HOW CAPGEMINI CAN HELP

At Capgemini, we pair deep industry and advisory expertise with the power of AI to streamline operations, enhance controls, reduce costs and unlock new business models. Our extensive experience spans the design, transformation and operation of financial crime and compliance programs across banks, FinTech, RegTechs and emerging digital-first institutions, where we facilitate collaboration and knowledge sharing across the financial ecosystem.

Through these partnerships, we help accelerate innovation, promote industry best practices and contribute to a more resilient, secure and efficient financial services landscape.

Meet us at ACAMS: The AssemblyLas Vegas | September 29–October 1, 2026

Explore our Financial Crimes,
Fraud and Digital Asset capabilities

About the Author

Sandeep Chakravadhanula

Practice and Capability Lead – Financial Crimes,
Banking & Financial Services

Sandeep is a Senior Leader & Practice Manager with 20+ years of expertise in Financial Crime Compliance, Risk Management and Regulatory Operations. He leads capability development, global operations and advanced compliance transformation at WNS.

References

1. World Payments Report 2026 | Capgemini

2. World Report Series 2025: Payments | Capgemini

3. Stablecoin Transactions Soared 72% in 2025, Hit $33T with USDC in Lead | Yahoo Finance

4. World Cloud Report – Financial Services 2026 | Capgemini

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