Case Study: CZ achieves real-time fraud detection and prevents improper payouts with SAS Detection and Investigation

Dutch health insurer CZ analyzes claims in real time, detecting fraud and preventing improper payouts

CZ, the third-largest health insurer in the Netherlands, needed to keep health costs affordable by detecting fraud, waste and abuse before payments were made. Previously CZ relied on manual, post‑payment reviews that missed complex patterns in large, coded claims datasets and recovered only modest amounts, making early detection and prevention the primary challenge.

CZ implemented SAS Detection and Investigation, a hybrid analytics solution combining rules, anomaly detection, predictive models and social‑network analysis to score and prioritize claims in real time. The system enables prepayment controls, captures complete case information, exposes linked entities and crime rings, speeds investigations and claims processing, and has allowed CZ to detect fraudulent claims earlier and curb larger losses across multiple care categories.

CZ

Marnix Suijkerbuijk

Director of Health Care and Statement Service