Insurance Fraud Signals Found in Crash Data

While building geospatial risk scores for vehicle crashes, Matrisk AI unexpectedly uncovered potential insurance fraud by analyzing Vehicle Identification Numbers (VINs) and crash timelines. Analyzing millions of crashes, they identified suspicious patterns: multiple crashes involving the same VIN in short timeframes, frequent insurer switching, and a high incidence of late-night, single-vehicle accidents. These patterns align with known insurance fraud tactics. While not definitive proof of fraud, the findings provide insurers with early indicators of high-risk vehicles and potential fraudulent activity, enabling better resource allocation to investigate suspicious claims and reduce losses from insurance fraud.