Predictive Modeling – An Overview of Analytics in Claims Management
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A 2012 Towers Watson survey of Property and Casualty claim officers found that 63% of respondents have started to explore the use of predictive modeling in their claim operations. The survey further stated that 7% have already been using claim analytics for more than three years.2Reported uses of predictive modeling in conjunction with claims management include:
- Allocation of Resources
- Reserving/Settlement Values
- Recognition of Potentially Fraudulent Claims
- Identification of Potentially High Value Losses
- Expense Management
- Trend Analysis
The use of predictive modeling tools in claims is not meant to supplant the claim handler’s own thought process. Its purpose is to provide decision support for his or her individual analysis. As with other forecasting tools, predictive models indicate probabilities, not certainties.
The utilization of predictive modeling with claims management has been embraced by some carriers, explored by others, but remains unknown to many. Analytics can be an effective tool for certain claim departments, if used appropriately. It is up to the individual insurer to determine whether its claim department would benefit from utilizing predictive modeling in some manner and to assess implementation requirements of time, money and manpower.
Common Claim Uses of Predictive Modeling
- Fraud Detection
- Outlier Claims
- Reserve and Settlement Values
- Defense Strategy
- Litigation Expense Management
- Subrogation Potential
It remains to be seen whether the use of analytics in claims management will eventually become standard operating procedure as some experts believe. Perhaps future technological advances will bring this belief closer to reality. However, if there is technology available today that is said to enhance efficiencies with the potential for improved loss costs, it may be worth a closer look.
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