Applying Predictive Analytics to Claims

With claims representing more than 80% of P&C insurers’ costs today, the business case for investing in the claims process is sound.

A new report from Boston-based Aite Group examines how the use of predictive analytics can significantly improve the claims process by affording greater consistency in claims processing, improved accuracy in loss reserving, and a shared, single view of the customer. “Claims management is the best suited operational area of insurance for the many and varied benefits of predictive analytics,” the report states. “Claims is truly the “moment of truth” for carriers to deliver on their obligations and promises to their customers; based on the historically low post-claim retention rate, it is also an area with lots of room for improvement.”

According to Stephen Applebaum, senior analyst with Aite Group and author of this report, predictive analytics solutions are potentially transformational for insurers wishing to improve their operating results while differentiating their policyholders’ claims experience. “The most successful P&C insurance carriers will be those that can best leverage new claims technologies and implement continuous claims process innovations that drive down costs and lower claim severities while improving claim service, customer satisfaction, and retention,” he says.

Another area where analytics can make an immediate impact is claims fraud. The report notes that by some estimates claims fraud ranges as high as $120 billion annually, a sizeable portion of the industry’s $500 billion in annual premium income. “While most claims are relatively straightforward and legitimate, many are complex and some are fraudulent, but historically all claims have been processed in a linear, uniform manner due to the inability to effectively differentiate them at the outset,” the report states. “Through the use of predictive analytics, carriers are finally catching up with the rest of the financial services industry in using technology to reduce fraud.”

 

 

 

 

 

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Core systems Data and information management Policy adminstration Claims Customer experience Analytics
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