Case Study: Government Employees Health Association (GEHA) achieves pre-payment fraud detection and twelve-fold improvement in case targeting with FICO Insurance Fraud Manager

GEHA catches fraud before payout while improving case targeting twelve-fold

Government Employees Health Association (GEHA), the third-largest health plan for federal employees and retirees (about 450,000 insured lives), faced a growing problem: its manual, rules-based system struggled to analyze more than 6 million claims a year, often detecting fraud only after payment. GEHA needed a way to increase electronic claims processing without missing fraud and to identify abuse and billing errors before dollars were paid out.

GEHA implemented FICO Insurance Fraud Manager — Health Care Edition, which uses neural networks and dynamic profiling to flag suspicious claims prospectively, accelerate routine payments, and provide detailed reason codes for investigation. Within a year GEHA saw hard-dollar savings from one in eight providers investigated and a twelve-fold improvement in case-targeting effectiveness, uncovering many billing errors and fraudulent or abusive claims earlier and more accurately.

Government Employees Health Association(GEHA)

Bob Greene

Manager of Data Analysis