There is gold at the end of the rainbow!

Good news! – claims departments are now flooded with great data.

Seems like great news doesn’t it. It is great news, or can be, if you’re using the data to help improve the operations, lower cost or predict the future. However, many firms aren’t using the data they have to provide valuable information for the operation.

With the advent of more modern claim technology there has been a push to input more and more information about claims. Claims professionals are being asked to capture very specific fields of information presumably to be used by others within the organization. In addition, more sophisticated data models are combining claims data with underwriting and financial data that when used correctly can be a treasure trove of information.

With all that information available what is the best way to use the information?

At the very least data should be used to manage the operation, reveal trends, or be predictive.

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Metrics to Be Predictive

Using data is not just about spotting trends but predicating outcomes. Using predictive analytics is not about deciding claim outcomes without the involvement of skilled claims professional, but rather it is about providing a tool to assist in the process. Predictive analytics can correlate multiple aspects of data and draw conclusions in an instant that claims professionals would not be able to do without hours of analysis. Predictive analytics tools are being successfully implemented to combat fraud and streamline the claims intake process as Gen Re noted in Predictive Modeling – An Overview of Analytics in Claims Management, some other uses of  uses of predictive analytics include determining:

• Outlier Claims
• Reserve and Settlement Values
• Defense Strategy
• Litigation Expense Management
• Subrogation Potential

The benefits, if used correctly, are limitless when robust data sets now common in the claims world are used. More and more companies are using analytics to improve operations. In fact, according to a Towers Watson study in 2012, 63% of Chief Claims Officer’s surveyed stated they were starting to use predictive analytics in in their claim’s operations (see study).

Predictive modeling has been limited in the past because systems were not as robust and the amount of data available to run data models was limited. Times, however, have changed and most carriers should have more than their share of data that could prove invaluable. Of course data integrity must be as clean and accurate as possible for these new models to be effective. Regardless, the possibility for significantly improving claims outcomes is compelling.

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