• 80% of fraud and AML teams in mid-market US banks now collaborate
• 100% use AI to improve fraud and money laundering detection
• 67% of institutions dislike the term “FRAML” for these joint efforts
• Combined systems cut false positives and boost staff efficiency
• Most common challenge is analyst staffing and alert overload
• AI supports investigations, data cleansing, and SAR writing
• Over two-thirds saved at least $1 million annually through system consolidation
• Cultural silos remain a barrier to some collaboration efforts
• Survey urges banks to prioritise people and process before tech
• Joint efforts enable more proactive and predictive risk detection

A new era of collaboration between fraud and anti-money laundering (AML) teams is reshaping the financial crime defences of US banks, with results that are already saving institutions millions of dollars annually.

According to a joint survey by research firm Celent and AI-driven financial crime platform Hawk, 80% of mid-market US financial institutions now report active coordination between fraud and AML functions – something that was rare even a few years ago.

The 2025 Trends in AML & Fraud Convergence at U.S. Mid-Market Banks survey, which polled 30 compliance, IT, and risk leaders from institutions primarily in the $1–20 billion asset range, paints a picture of a sector finally recognizing the power of working together.

“Too many banks jump to technology before they fix their processes or engage the right people,” said Tobias Schweiger, CEO and co-founder of Hawk. “Real change begins with conversations, not code.”

That shift is already paying dividends. Sixty-seven percent of those surveyed who consolidated systems said they had saved over $1 million a year.

Roughly half reported annual cost reductions of more than $5 million. But the benefits extend beyond budgets.

By combining AML and fraud systems, banks are also seeing dramatic reductions in false positives – alerts that turn out to be benign – and improved efficiency across investigations, transaction monitoring, and onboarding.

Although some financial institutions have balked at the term ‘FRAML’ – with many saying it simplifies a deeply complex integration of functions – few dispute the results of closer operational alignment.

Among the top benefits: shared context between teams, unified case management, and easier information flow between systems.

AI plays a pivotal role in making this possible. Every institution surveyed uses artificial intelligence in some capacity, with applications ranging from behavioral biometrics and anomaly detection to automated SAR (Suspicious Activity Report) writing and ad-hoc data searches.

AI is also helping banks tackle one of their biggest challenges: staff shortages. “AI is simply more precise in handling the complexity of cases,” Schweiger noted, citing the increasing sophistication of tools that can model past behavior and identify subtle deviations in real-time.

Despite the momentum, barriers remain. Legacy systems, inadequate training, and siloed organizational cultures still prevent some banks from achieving the full benefits of convergence.

Schweiger advises institutions to begin with small pilot projects and use early insights to guide broader implementation. “If your teams don’t collaborate, you miss crimes,” he said. “Fraud doesn’t care where AML begins and ends.”

The survey's findings suggest that the pressure of rising regulatory expectations and increasingly sophisticated criminal tactics has forced a long-overdue rethink.

As digital services proliferate and customer expectations evolve, banks that fail to unify their defences may soon find themselves not only out of step but out of pocket.

For institutions ready to embrace a more integrated future, the message is clear: align your people, refine your processes, and then apply the right technology. Only then can financial firms hope to stay ahead of increasingly organized and tech-savvy financial criminals.