What financial leaders should ask about their AI fraud strategy

Fraud has always been part of doing business. What has changed is the pace. Artificial intelligence has accelerated how quickly fraud schemes evolve, how convincing they look, and how widely they can spread. For finance leaders responsible for corporate payments, that shift raises an uncomfortable reality: the controls that worked even a couple of years ago may no longer be enough.

At the same time, businesses cannot afford to slow down. Payments still need to move quickly. Suppliers still expect on-time settlement. Internal teams still need efficient workflows, not more manual checks layered onto already strained processes. That tension between protection and performance is at the heart of today’s fraud challenge.

Rather than asking whether AI belongs in a fraud strategy, a better question is how it fits, where it truly helps, and where it can create blind spots if teams rely on it too heavily.

Fraud is moving faster than most controls

AI has changed the economics of fraud. What once took weeks of coordination can now happen in seconds. Bad actors are using AI-generated content, synthetic identities, and automated campaigns to probe payment systems at scale. Language barriers are gone. Poorly written phishing emails have been replaced by messages that look and sound legitimate.

That shift is showing up in the data. According to the 2025 AFP Payments Fraud and Control Survey Report, in 2024, 79% of businesses reported experiencing attempted or actual fraud, and business email compromise (BEC) was the most common form of attempted fraud, cited by 63% of organizations. Checks remain especially vulnerable, with nearly two-thirds of companies reporting check fraud last year.

What makes this especially risky for corporate payments teams is that many attacks target trusted processes. A supplier change request that looks routine. An invoice that matches historical patterns just closely enough to pass review. Fraud today is designed to blend in, not stand out.

The fraud conversation often leaves out B2B

Much of the public conversation around AI-driven fraud focuses on consumers. Stolen credit cards. Account takeovers. Identity theft. Those threats are real, but they can overshadow risks that live squarely inside B2B payment operations.

Corporate payments introduce different vulnerabilities: complex approval chains, high dollar values, long-standing supplier relationships, and multiple handoffs between systems and people. When fraud occurs here, it often exploits process gaps rather than technical weaknesses alone.

For example, supplier onboarding and change management remain high-risk moments. So does invoice intake, especially when teams rely on email or manual data entry. Even approval workflows can become weak points if urgency overrides verification.

A strong fraud strategy starts by asking where trust is assumed instead of verified across the payment lifecycle.

AI is both a weapon and a defense

Bad actors are using AI to make fraud harder to detect, but finance teams are also using AI to spot patterns humans can’t. Modern tools can analyze transaction behavior at scale, flag anomalies, and surface subtle signals such as duplicate payments to slightly altered vendor names or unusual timing that would be easy to miss in a manual review.

Where teams run into trouble is assuming AI is a set-it-and-forget-it solution. AI works best as one layer in a broader strategy. It can surface risk, but human judgment still matters, especially in gray areas where context is critical.

The most effective approaches combine AI-driven detection with strong process controls, clear audit trails, and payment methods that reduce exposure by design.

Strengthening controls without slowing payments

One of the hardest challenges for finance leaders is improving fraud prevention without adding friction. Overcorrecting after a fraud incident by piling on manual checks often slows the business without addressing the root cause.

Instead, many teams are rethinking where controls live in the payment process. For example, payment methods like virtual cards can reduce risk upfront by limiting transactions to specific amounts, vendors, and timeframes. Security is built into the payment itself, rather than added after the fact.

The goal isn’t to remove people from the process. It’s to use AI and automation to focus their attention where it matters most, while keeping legitimate payments moving.

Fraud prevention is a payment strategy issue

Too often, fraud is treated as a reactive problem or a narrow risk function. In reality, it is deeply connected to how payments are designed, executed, and managed.

The choices a company makes about payment methods, supplier enablement, approval structures, and data visibility all influence fraud exposure. After an incident, teams often rush to add controls. A more sustainable approach is to step back and ask how payments can be both safer and more efficient by design.

Looking ahead, finance leaders should be preparing for a world where AI is everywhere, not just in fraud tools but in everyday business operations. “Good” fraud prevention will not mean zero risk. It will mean resilience: the ability to detect issues quickly, respond decisively, and keep legitimate payments moving.

That starts with asking the right questions today.

For more insights and updates on corporate payments, check out:

• Your guide to virtual card rebates
• 2026 payment trends
• Is the secret to better cash flow management AI?

Learn more about how WEX payment solutions can be tailored to your business, so you can accelerate and streamline operations while creating lasting growth and success for your organization.

The information in this blog post is for educational purposes only. It is not legal, tax or investment advice. For legal, tax or investment advice, you should consult your own legal counsel, tax, and investment advisers.