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Analytics and Claim Fraud

Insurers that want to establish effective anti-fraud programs or enhance the effectiveness of existing programs must take a comprehensive approach to dealing with this pervasive problem.

By Michael A. Costonis | Updated on April 01, 2010
An estimated 10 percent of claims filed with the U.S. insurance industry are fraudulent. That number covers a multitude of sins, from relatively simple, low-dollar amount instances of opportunistic fraud, to highly sophisticated fraud rings, often linked to organized crime and often operating with insider knowledge and expertise in software rules and claim thresholds. We typically find, however, that only low single-digit percentages of total claim payouts are prevented or recovered as part of claim handling fraud investigation units.

Some insurers used to accept fraud as a cost of doing business, more expensive to combat than to ignore. That attitude, however, has largely disappeared, due in part to the evolution of powerful analytical tools that help insurers identify fraud, act on it quickly, and direct potentially fraudulent claims to special investigation units.

Tools, however, are only part of the equation. In a business environment as challenging as the one insurers have faced in the last few years, the potential to reduce fraud losses—as well as the costs associated with investigating fraudulent claims—has become a very significant profit-and-loss item, one with a relatively rapid and attractive return on internal investment.

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