Sharath Reddy Polu

AI-Driven Behavioral Analytics for Real-Time Fraud Prevention

Financial fraud detection is shifting from static rule-based systems to AI-driven behavioral analytics. By analyzing interaction signals such as navigation patterns, keystroke behavior, device fingerprints, and transaction sequences, modern systems create dynamic behavioral profiles that detect anomalies in real time. This session explores how contextual intelligence, behavioral biometrics, and self-learning models enable financial institutions to prevent fraud proactively while maintaining a seamless user experience.