Insurance is another arena where compliance management is of vital significance. To understand the impact, one out of every three auto-insurance claims involves fraud. From a financial standpoint, this has the effect of adding $6 billion to the auto premiums each year. There is a strong need for efficient technologies that augment the productivity of insurance claim auditing. | 
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Audits (or claim-reviews) are the primary means of detecting and deterring insurance fraud. For example, in personal injury claims, often expensive independent medical examinations (IME) are used to validate suspicious claims. The challenge is to reduce the number of unproductive IME’s. Data mining methods, and in particular, predictive models can enable insurance agencies to understand the relationships between the attributes of a claim available prior to an investigative action is pursued and the decision made on whether or not to request an IME. Scoring models can be used to help make decisions on which claims to pursue with an IME and ultimately to predict the likely outcome of an IME. Overall, non-compliance and fraud within the various insurance programs leads to significant revenue loss to the insurance companies that manifest itself in higher premiums for legitimate customers. Compliance management has a strong role to play in minimizing this revenue loss, and maintaining the health of the insurance sector. |
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