ClaimGUARD

Angoss ClaimGUARD™

Angoss ClaimGUARD is an industry-leading predictive claims fraud and abuse detection solution providing a suite of proven analytics capabilities and domain expertise to reduce and prevent the costs of fraudulent or abusive transactions for providers of public and private health care and benefits insurance.

Angoss ClaimGUARD helps health care insurers apply advanced data mining and predictive analytics capabilities quickly and easily to their claims data to:

  • Reduce Costs with Improved Detection of Claim Fraud and Abuse - quickly detect, document and expedite investigation of suspect providers, claimants, and claim-level behavior with keen models capable of detecting subtle patterns of unusual activity. Angoss’ sophisticated and adaptive pattern detection system is extremely difficult to outmaneuver and can discover new schemes before they become prevalent.
  • Actively Deter Fraud and Hasten Recovery – with a rapid Claims Fraud Scoring engine and list generation capabilities, providers can quickly and easily distribute greater numbers of better targeted verification letters that are fully detailed with relevant claim history and data.
  • Analyze Claims Portfolios to Support Client Satisfaction and Account Management Objectives - provide account and claims managers with detailed insight to key drivers of claims costs and loss ratios. Insurers using ClaimGUARD can quickly and proactively identify clients with high levels of exception claimants and providers before concerns are realized by the clients themselves.

Comprehensive Feature Set

  • Proactive claims fraud detection system for Health, Dental, and Prescription Drug claims that identifies new kinds of fraud, often before the organization is aware that it has occurred.
  • Prioritized claims lists and targeting tools that help in effective fraud and abuse strategies focusing on providers, claimants, and claims most likely abusing systems and programs.
  • Post-payment and pre-payment detection capabilities enable analysis of past incidents and automated detection of new claims.
  • Batch and real-time scoring