The Challenge
A US-based casualty reinsurer was processing 15,000+ claims notifications annually with suspected fraud rates of 8-12%. Manual investigation was slow, inconsistent, and missed sophisticated fraud schemes. The company was paying $15M+ annually in fraudulent claims.
The Solution
Implemented Claims Intelligence Agent to analyze loss notifications, identify suspicious patterns, and flag high-risk claims for investigation. The system uses anomaly detection, network analysis, and historical pattern matching across 20 years of claims data.
Implementation
Trained Claims Agent on 20 years of claims data, including 500+ confirmed fraud cases. Built pattern recognition models for medical fraud, staged accidents, and inflated claims.
Deployed real-time fraud scoring system analyzing incoming loss notifications. Integrated with claims management platform and SIU workflows.
Added network graph analysis to identify fraud rings and connected claims patterns across multiple cedents and jurisdictions.
Results
Prevented $12M in fraudulent claims payments in first year
Identified 340% more suspicious claims than manual review processes
Reduced time to investigate flagged claims from 45 days to 18 days
Maintained low false positive rate of 12% vs. 35% industry average
"The fraud patterns we're catching now would have been impossible to detect manually. This is a game-changer for our bottom line."