How Predictive Analytics Can Improve Claims Outcomes

Predictive Analytics

If insurers could see the future they would be able to help their loss prevention departments reduce claim frequency and severity. Unfortunately, no one has that skill but as this month’s Claims Magazine explains we do have the tools to predict the future more accurately. More specifically, using predictive analytics to assist with Worker Compensation claims.

According to The National Council on Compensation Insurance 2015 Annual Issues Symposium, from 2009 to 2013 there has been an increase in annual Workers Compensation claims severity in 32 states. Predictive analytics can help adjusters be proactive and make informed decisions on the best way to handle these types of claims.

Predictive Analytics helps by combining all of the experience needed in resolving thousands, sometimes millions of claims, into a model to base future claims on. Instead of relying on a single person, insurers can use these models to determine which claims may possibly spiral out of control.

Errant Worker Compensation claims can cost insurers time and money. Even the best adjusters can find themselves dealing with unruly claims due to heavy caseloads, too many file transfers, lacking information, and inexperience spotting severity indicators. If a claim is flagged as possibly having high severity then insurers know that an adjuster with a high caseload or an inexperienced adjuster may not be the best person for the job.

In this regard, predictive analysis models can help determine the best person for the job. If you assign a severity score to claims based on the models created from the predictive analytics you can assign less severe claims to newer adjusters and more difficult claims to experienced adjusters. This allows employees to work at their level and get progressively harder cases as they gain experience. This type of triage creates better adjusters and saves the insurer money in regards to claims that spiral out of control.

Beyond assigning work, severity scores can be used in the claim handling process. For low severity claims, auto adjudication can be built in while increased managerial oversight can be requested for higher severity claims. With these types of processes in place, claim departments can better focus their time and energy where it’s needed.

Now, predictive analytics is great but it can never fully replace a person. Even though the best adjuster can make mistakes, a good predictive model can’t replace a human being. It helps in finding the best solution and minimizing the risks. To find out how Kompani Risk & Insurance Solutions, Inc. uses predictive models to help you, please contact our CEO R. Glenn Matsen directly on his personal extension at 916-306-5902. We work smart and hard to make sure your business is well protected.