In the world of fraud detection, generative AI has unlocked remarkable new capabilities for analytics, and as a result, companies are racing to develop ways to explore data, summarize evidence, and build fraud-detection workflows. It has become clear that hybrid solutions – combining genAI and traditional machine learning –  are most effective when solid business use cases are paired with curated data, human oversight, and statistical rigor. 

Attendees will learn why fraud detection remains stubbornly difficult in retail and other verticals, how to design a genAI workflow with human-in-the-loop safeguards, and how ML models and genAI systems complement each other rather than compete to deliver real value for organizations.