Fraud isn’t just changing; it’s picking up speed. And Artificial Intelligence (AI) is what’s driving it. As fraudsters use AI to launch precision-targeted payment scams, banks and regulators are racing to adapt. Here's what that shift looks like and why it matters.

AI Is Changing the Fraud Game Fast

Fraud tactics like authorized push payment (APP) fraud, Business Email Compromise (BEC), account takeovers (ATO), and social engineering aren’t new. What’s changed is the scale, precision, and believability AI brings to these schemes. Today, a single fraudster can use AI to generate thousands of hyper-targeted fake emails, spoofed websites, and even deepfake audio clips that mimic executives with chilling accuracy.

Commercial payments, once considered relatively safe due to stable vendor relationships and predictable transaction patterns, are now far more exposed. Fraudsters mine business data to impersonate vendors, hijack payment instructions, and mimic internal communication styles. All with alarming realism.

Fraud is evolving from sporadic and detectable to constant, integrated, and nearly invisible.

Regulators Are Paying Attention

In the U.S., bipartisan support is growing for the Task Force for Recognizing and Averting Payment Scams (TRAPS) Act, a payments fraud task force, and the Federal Reserve has proposed new measures to combat check, ACH, wire, and instant payment fraud. But this is just the beginning.

Historically, commercial entities have borne the brunt of B2B fraud losses, unlike the strong consumer protections in retail banking. But as AI-powered fraud increasingly targets high-value transactions, regulators are recognizing that this imbalance is no longer sustainable.

The Federal Reserve’s recent language around “payments fraud,” “data sharing,” and “AI-driven detection frameworks” signals a broader ambition: tougher standards and shared responsibility across the financial ecosystem. Because AI-driven fraud is now so sophisticated that no single player can fight it alone, collaboration has become essential.

This isn’t just about financial losses. It’s about preserving trust in the payment ecosystem. When a business suffers a major fraud event, it risks not only its bottom line but also its reputation and operational stability.

Lessons from Abroad: CoP and VoP

The U.K. and EU are already implementing preventive fraud measures that the U.S. could learn from.

  • Confirmation of Payee (CoP) in the U.K. verifies that the name on a payment matches the recipient’s account before funds are sent. Since its launch in 2020, CoP has been adopted in over 99% of Faster Payments and has significantly reduced APP fraud.
  • Verification of Payee (VoP) in the EU, effective October 2025, mandates similar safeguards across the SEPA region.

These systems prevent misdirected commercial payments before they happen, emphasize shared responsibility, and rely on real-time verification and standardized data-sharing.

Building a Multi-Layered Defense

AI is not a silver bullet. It’s just one part of a broader fraud prevention strategy. To stay ahead, both banks and businesses need a layered approach that mixes technology with good governance and collaboration:

  • Adaptive AI: Machine learning models that evolve with changing fraud patterns.
  • Explainability and Fairness: Algorithms must be auditable, secure, and non-discriminatory.
  • Integrated Intelligence: Correlating login behavior, payment activity, and third-party data.
  • Collaborative Networks: Sharing anonymized fraud data across banks, PSPs, and ISVs.

Open platforms and real interoperability are what make this possible. The more banks and businesses work together, the stronger the collective shield against AI-powered fraud.

The Role of Regulation and Industry Standards

As AI-driven fraud becomes more pervasive, regulators will move from encouraging better controls to mandating them. Expect to see:

  • Potential shifts in liability for commercial fraud losses
  • Clearer standards around AI transparency
  • Mandatory data-sharing protocols

The U.K.’s “Failure to Prevent Fraud” law is a prime example, requiring organizations to prove they’ve taken adequate steps to prevent fraud. A similar framework could emerge in the U.S.

Preparing for What’s Next

To thrive in this new landscape, banks and businesses alike must invest early in stronger controls, including:

  • Deploying explainable, adaptive AI systems
  • Integrating fraud signals across internal and external systems
  • Participating in data-sharing ecosystems
  • Updating governance frameworks for faster incident response

This is more than just commercial fraud prevention. It’s about earning and keeping customer trust in a fast-changing environment.

Act Now

The AI fraud race is real and it’s only accelerating. But so is the opportunity to lead through innovation and cooperation.

The threats are growing. So must our defenses.