AI is changing how financial crime is conducted, increasing the pressure on fraud, anti-money laundering (AML), and risk leaders at financial institutions. Criminals can now produce thousands of identities and applications within days, adjust tactics, and create deepfakes that pass document and liveness checks. In Datos Insights research, most institutions expect fraudster use of AI to increase over the next five years and disputes to rise. Institutions must act now. Only a small segment institutions report making excellent use of AI and machine learning themselves, and many still rely on controls designed for slower, human-scale threats.
Datos Insights’ ninth annual Financial Crime and Cybersecurity Forum brought together financial crime leaders, solution providers, and industry experts to examine how smarter risk intelligence, AI-driven operations, and stronger collaboration can reshape institutional defenses into orchestrated, resilient ecosystems built for the speed of modern threats. The report captures how leading institutions are rebuilding their control frameworks by connecting fraud, AML, and authentication signals, shortening the time from a fraud event to a deployed countermeasure, and treating customer losses as a measure of program success. Several institutions are also moving from detection to interdiction, stopping suspicious payments before funds leave.
The report sets out four imperatives: measure human and nonhuman activity, fund interdiction alongside detection, quantify customer losses, and accelerate information sharing. Together, these can reduce loss, cut unnecessary friction for good customers, and build the case for modernization.
Clients of Datos Insights’ Fraud & AML practice can download this report.
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