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The science of workers' comp analytics made easy

The predictive analytics functional process is complex. Claims, carriers, TPAs, and self-insureds of all sizes must follow a series of steps before they can accurately and reliably score claims.

First, they need to analyze and categorize a series of inputs. Then they must test, check, and validate data before they apply a range of multivariate models and machine learning algorithms in the analytics database and logic engine. At that point, they can connect obscure, hidden, and disparate relationships in the data to reflect an appropriate score for each claim.

Workers-Comp-Predictive-Analytics

Rewards of a predictive analytics model

But there’s an easier way to reap the rewards of a complex predictive analytics model. Our wcNavigator® tool tackles the complex analytics, and you simply get the results.

Workers' Comp Predictive Analytics Made Easy

We’ve made the science of predictive analytics easy and robust. wcNavigator® takes client claims data, enhances it with industrywide claims data, and does all the technical work. You get a reliable score upon which your claims department can take immediate action to get the best outcomes. 

Find out how to produce results with the easy, streamlined wcNavigator® system


Rob Lewis

Rob Lewis is president of Casualty Solutions at Verisk. You can contact Rob at rlewis@verisk.com


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