Predictive analytics rapidly is emerging as a must-have tool in the insurance carrier’s arsenal. However, in most common applications, the power of advanced analytics is deployed from the bottom up:

Executive Summary

Risk models, the most common applications of predictive analytics in P/C insurance, can help carriers understand what's happening to risk quality and predicted loss at the policy level and across an entire underwriting portfolio, explains Bret Shroyer of Valen Analytics. Here he introduces the predictive measure "embedded profit" as the source of this information and reviews added benefits for reserving actuaries.
Individual account pricing. New business underwriting triage. Audit and inspection optimization. Claims management. Incident-level fraud detection.

The forward-looking statistics made possible through predictive analytics have another, equally powerful application: top-down, portfolio-level management using the new levels of information now available. Imagine, for example, being able to accurately predict an accident-year loss ratio for an entire portfolio of business just six months into the year.

Profit Uncertainty: Three Broad Sources

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