Financial‑crime detection relies on machine‑learning algorithms to analyze large datasets, identify suspicious patterns and monitor transactions in real time. Feedzai explains that supervised and unsupervised learning detect known and unknown fraud types, while behavioural biometrics and continuous authentication enhance security. Human experts remain integral to review flagged alerts and improve models.

 

For risk management frameworks, see What does an AI governance framework look like for banks?