How the detection of insurance fraud succeeds and fails

Abstract

Insurance fraud is a serious and growing problem, and there is widespread recognition that traditional approaches to tackling fraud are inadequate. Studies of insurance fraud have typically focused upon identifying characteristics of fraudulent claims and claimants, and this focus is apparent in the current wave of forensic and data-mining technologies for fraud detection. An alternative approach is to understand and then optimize existing practices in the detection of fraud. We report an ethnographic study that explored the nature of motor insurance fraud-detection practices in two leading insurance companies. The results of the study suggest that an occupational focus on the practices of fraud detection can complement and enhance forensic and data-mining approaches to the detection of potentially fraudulent claims.