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3 Types Of Claims Metrics Every Department Should Be Looking At

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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.

Metrics to Manage the Operations

At the core, information coming out of the claims system should be used to manage the people handling files. Daily, weekly, monthly quarterly and yearly metrics around performance issues should be used to ensure claims professionals and support staff are performing at their best, responding to claims promptly and managing workloads and staffing levels.  Typical metrics to manage the operation would center on matters coming and going out (i.e., open, closed, closing ratios); aging reports (i.e., throughput, time from receipt to setup, open to close); workloads (i.e., caseloads and closing ratios by adjuster); or financial in nature (i.e. reserve changes from one period over another, average reserves, total paid).

Metrics to Reveal Trends

There are trends in your data if you know where to look. Trends in loss frequency and severity, which may be caused by external factors, such as legislative, environmental and economic forces, are all developed from claims data. Trending claims data will help underwriters ensure pricing and terms are appropriate and allow problems to be addressed before they become disasters. There are numerous examples of companies that succeeded because they were able to review claims trends and adjust their business before it was too late. There are conversely many companies that failed because they did not have or use their claims data to spot deteriorating books of business in enough time to address it. Information from claims is the lifeblood of the organization and should be identified and regularly shared to help the organization make better decisions about loss reserves, risks, investments, and resources.

Captives and self-insured can benefit even more on using data to trend losses and lower costs to the bottom line. In an article in Business Insurance about how Captive Insurers Provide Owners With Key Risk Management Tools, the authors discuss how Direct TV used claims data to trend key issues that allowed them to significantly improve results in their Workers’ Comp program:

DirecTV Inc. used claims data from the past several years …to help it manage claims more aggressively for its installation crews…DirecTV used the claims data identified to implement changes to its safety programs, its training programs and its return-to-work strategy…. The claims data also showed opportunities to improve fleet risks. Over a three-year period, the safety changes resulted in a 43% reduction in calls on the Driver Alert phone line. The data also found delays in reporting claims and lengthy lost time due to worker injuries. As a result, the company implemented a formal return-to-work program, which resulted in a significant decrease in lost time, and used additional training on claims reporting to reach the point where 91% of claims now are reported within three days of an incident.

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.

 How are you using data and analytics?

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