The implementation of predictive analytics is simple and valuable, and it is key to the transformation of claims and legal expenses into valuable assets for insurance companies.

Executive Summary

Talk of insurance innovation can be overwhelming for insurance company executives. If you break down this innovation into three opportunities, however, you'll find that the goal of innovation is much more attainable, according to CaseGlide Founder Wesley Todd. In the third part of a three-part series, Todd describes four types of analytics and outlines a six-step process for using one of them—predictive analytics—to transform claims and expenses into valuable assets. The full article, "The Three Ways Technology Can Transform Claims and Legal Expenses Into Valuable Assets," will be published in the next edition of Carrier Management magazine.

Once you implement predictive analytics in your claims and legal departments, you will experience financial and operational benefits, such as improved underwriting, expense mitigation and indemnity reductions.

There are four types of analytics: descriptive, diagnostic, prescriptive and predictive. Predictive analytics is superior for your insurance company, and here is why.

Predictive analytics answer the question “what might happen?”—for example, predictive analytics could provide a range of the number of lawsuits your company might receive next year based on data trends from last year.

Predictive analytics can provide your company with opportunities for revenue growth and expense reduction. The following list demonstrates just some of the ways that insurance companies benefit from using predictive analytics:

Allocating resources. Reserving. Producing effective and efficient settlement values. Recognizing potentially fraudulent claims. Promptly identifying potentially high-value losses. Managing expenses. Analyzing emerging issue trends to help underwriting write more profitable business and quickly stop writing increasingly risky business.

Descriptive and diagnostic analytics have limited upside potential. They focus on the past. Descriptive answers “what happened?” Diagnostic answers “why did that happen?”

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