Health Insurance Claims Fraud Detection Systems: 2015 IT Vendor Spectrum

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Celent have reviewed this profile and believe it to be accurate.
9 March 2015
Nicolas Michellod and Mohammed Mahfuz

Abstract

Mitigating claims fraud is a critical process for insurers if they want to generate profitable business, and health insurance is an area where claims fraud detection requires particular attention.

In the report Health Insurance Claims Fraud Detection Systems: 2015 IT Vendor Spectrum, Celent reviews IT vendors and their offerings in the claims fraud detection area with specific focus on health and medical insurance.

“Medical insurance claims handling is a complex process where multiple parties are involved including various medical providers,” says Nicolas Michellod, a senior analyst with the Celent’s Insurance practice and coauthor of the report.

“Specific functions and features are required if health insurers want to do a good job at mitigating claims fraud,” adds Mohammed Mahfuz, an analyst with the Celent Insurance practice and coauthor of the report.

This report provides a detailed description of IT vendors and their offerings in medical claims fraud detection. It profiles 13 IT vendors and is not restricted to a specific geography. Each vendor is profiled using the same structure, starting with a synoptic table presenting the company and its solution. Celent describes the system’s functionality, the customer base, technology as well as implementation, pricing and support.

The vendors profiled in this report are:

  • BAE Systems Applied Intelligence
  • Fair Isaac Corporation (FICO)
  • FRISS
  • Hugin Expert A/S
  • IBM
  • iGATE Corporation
  • INFORM GmbH
  • LexisNexis Risk Solutions
  • Lorica Health
  • Optilab
  • Performant
  • SAS
  • Verisk Health

Although this list is not exhaustive, we think it provides a valuable sample of vendors, which already have experience of implementations in the health insurance industry.

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Insight details

Content Type
Reports
Focus
Risk Management & Compliance, Vendor landscape