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How Insurers’ Big Data “Moneyball” is a Game-Changer for Agents

As big data dilutes experience mods, agents must educate clients on the change.Computer hardware and software advancements now allow insurers to quickly process millions of calculations, analyze the data they produce and promptly validate their emerging predictive models.

There are significant inefficiencies in the rating system that data-savvy insurers can leverage to gain a competitive advantage. They can analyze their own data instead of relying on the rating bureau’s broader, aggregate view to create a competitive advantage.

Let’s assume the rating bureau’s data indicates that claim costs are rising for plumbers in a given state. The rating bureau will likely increase advisory rates and expected loss rates for plumbers in the entire state. However, an individual insurer analyzes its own book of business and sees a decrease in claims costs for that state’s plumbers. The carrier could set a lower premium for plumbers and capture greater market share from competitors that only use aggregated rating bureau data.

Enhanced data analytics can turn conventional rating and pricing upside down. The purpose of the rating bureau’s experience rating plans is to assist the insurers appropriately set a price for the risk. However, with advanced analytics and regulations mandating the use of the experience mod, employers may find themselves in the residual market because the insurer was unable to make an offer at their price.

Workers’ compensation experience rating and experience modification factors are not going away any time soon; they are enmeshed into each state’s regulatory and statutory framework. And not all insurers will create and utilize their own predictive models, so they will continue to rely on the rating bureaus. However, you’re probably beginning to see anomalies between the old world of “predictive indicators of future losses” and the new world of insurance-specific predictive analytics.

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