Banks Use AI Agents to Catch Compliance Drift Earlier

Financial institutions have spent years stalking the risks and opportunities that artificial intelligence brings to their security-critical space. Then came AI agents.

These agents could give banks something their existing financial crime operations struggle to produce: investigations conducted consistently, documented exhaustively and audited continuously rather than months later through a small sample of cases.

“The AI doesn’t get bored. It doesn’t get fatigued. It doesn’t forget to include that link for the one search it did,” Christopher Phillips, director of financial crime industry engagement at Flagright, told PYMNTS. The result, he said, can be “a robust output that is easy to audit.”

That turns the conventional risk equation around. More automation does not necessarily mean less control. Properly designed, more autonomy could create more visibility into how financial crime decisions are made. Traditional financial crime quality assurance operates largely through sampling. Compliance or audit teams might examine a relevant percentage of cases and extrapolate findings across the broader program.

Agentic AI, however, makes another model possible.

“With AI, you can do all of them,” Phillips said. “You could literally do a QA or an audit of every single case.”