A couple of years back, I prepared a report on behalf of Insurance Networking News that discussed the enormous cost-saving potential that comes out of applying predictive analytics to fraud detection. At that time, I noted, by integrating predictive analytic results into daily claims management activities, insurers can automate preventative measures as well as act immediately on fraudulent claims. Carriers only have a set amount of time in which they are mandated to cut a check, and applying predictive modeling technologies can help catch discrepancies within that short window. Such tools are not only run against the initial claim documents, but also against all transactions through the claim lifecycle—from initial filing to post-settlement.

Nowadays, the power of analytics—both predictive and historical—is sought for a range of business applications well-beyond fraud detection. And the benefits can add up to much more than cost savings. Analytics is now a way to find, engage and retain customers, understand new market opportunities, and understand product performance.

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