Predictive Modeling for Workers Compensation Helps with Pricing and Claims
Predictive models for Workers Comp traditionally have been used to reduce claim costs and duration. But with technological advances, insurance carriers are also using the models to boost their comp underwriting results and help select profitable accounts. According to a study by Towers Watson, property/casualty insurers increasingly are reporting benefits from the use of predictive models in underwriting, pricing, rating, and market segmentation. More than 75% of the survey’s respondents in fact are reaping bottom-line benefits of rate accuracy, loss ratio improvement, and higher profitability. That’s good news in a market that has seen its shares of crises.
What Is Predictive Modeling?
Predictive modeling is the application of statistical techniques and algorithms to individual risk data to better understand the behavior of a target variable based upon how multiple variables interact. Rather than just relying on an understanding of individual risk elements, predictive modeling allows insurance companies to consider many (including new and unexplored) factors simultaneously. This analysis permits more accurate and objective risk selection and pricing decisions.
Benefits of Predictive Modeling
Property/Casualty carriers using predictive modeling for market segmentation, according to Towers Watson, are saving two to four points in their loss ratio and loss adjustment expenses (LAE) after the first year of implementation. What’s more, by improving efficiency, the process can also reduce underwriting expenses. Other benefits that carriers have experienced include the ability to detect fraudulent claims and improving the claims process. Further, carriers can detect potential misreporting by a business with predictive modeling. The Insurance Services Office (ISO) in 2010 launched a premium audit predictive modeling tool that reveals which policyholders are more likely to need an on-site audit and which are more likely to require a premium adjustment. Non-insurance data, such as wages and employment information in government databases, are part of the model to reveal discrepancies in payroll information.
Predictive modeling is also being used to help determine the right price for each risk in a workers compensation portfolio. Moreover, it is being used to reduce losses from medical-only claims to loss-time claims at the onset by helping to reveal potential claims problems, such as attorney involvement, unnecessary delays in maximum medical improvement and return to work, and fraud.
Predictive modeling for Workers Compensation is evolving as technology continues to advance and as carriers embrace its benefits and begin implementing it in their underwriting, pricing, and loss control.
Caitlin-Morgan, an MGU and wholesaler brokerage, specializes in Workers Compensation and can help you with placement of coverage for your clients. Our staff has many years experience in the areas of underwriting, claims management, and loss prevention. Whether your client is a minimum premium account or a tougher to place risk, Caitlin Morgan is here to help you meet your clients’ needs. Give us a call at 877.226.1027.