With advances in data collection and new technologies, predictive analytics have become more and more prevalent among the risk management community. At the 2014 RIMS Conference, Steven Laudermilch, SVP of Claims ACE Claims Group, provided an overview of recent developments in predictive analytics, and offered some advice for risk managers.

Mr. Laudermilch says one of the biggest misconceptions about predictive modeling is that building the mode is the more difficult than putting it into place. He acknowledges the expertise and investment required to build models, “putting it to work is the greatest operational challenge that companies face.” He warns companies not to dismiss the output, but accept it as insight to claims.

According to Mr. Laudermilch, “about three-quarters of claims represent about 75% of loss costs to an organization.” He says companies “need to find the loss driving segment of claims…intervene on those claims…and you have to drive better outcomes.” Predictive analytics “put a spotlight on claims…to drive business value.”

Structured data has a lot of limitations. “Text mining is the ability to access and analyze unstructured data (like claim notes)”, something ACE has invested heavily in. Text mining allows risk managers to sift through claims notes to look for risks that might be emerging…providing “a line of sight into loss trends and experience.”

Mr. Laudermilch believes risk managers without predictive analytics should “get onboard quickly.” He suggests they be thoughtful in their adoption. He likens predictive analytics without an organized operational response to an “unused gym membership.” He believes risk managers must embed predictive analytics into the claims process, change the way you intervene on claims, attack severity claims and drive better outcomes.” Companies that do not dot it will be at a competitive disadvantage.

For more World Risk and Insurance News from the 2015 RIMS Conference in New Orleans, visit the dedicated RIMS 2015 Channel in the On Demand Library.

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