Learn how AI — from predictive models to generative and NLP tools — is changing the fight against fraud, waste and abuse (FWA) in health plans. This session explores practical AI applications: automated document analysis, anomaly and network detection across claims and clinical data, and AI assisted investigator workflows that prioritize high risk cases. See real examples of how combining internal records with external datasets improves signal quality, speeds investigations and reduces false positives. Join us to understand how AI can strengthen plan integrity while meeting privacy and regulatory expectations.

What you’ll take away:
•    Key AI techniques for FWA detection: anomaly detection, NLP/document extraction, and graph analysis
•    How combining clinical, claims and third party data uncovers complex, high value schemes
•    Practical steps to improve investigator conversion and reduce false positives using AI
•    Governance, explainability and privacy best practices for safe AI deployment in health plans