Isolation-based conditional anomaly detection on mixed-attribute data to uncover workers' compensation fraud

Moreover, we present a case study in which we demonstrate the usefulness of our proposed approach on real-world workers' compensation claims received from a large European insurance organization. As a result, the iForestCAD approach is greatly accepted by domain experts for its effective detection of fraudulent claims.