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Optimizing Policy Pricing: An Insurance Case Study

The Company

A leading North American insurance company.

The Challenge

The client realized that pricing was out of kilter with customer risk levels and believed that better aligning customer pricing with customer risk would create a more resilient product line. The company’s best customers would pay less and therefore be less exposed to potential competitive pricing pressures, whereas more risky customers would pay more to cover the cost of their potential losses. The company was concerned, however, that a wholesale change in its pricing structure might lead to unexpected reactions from the customer base.

The Solution

The insurer turned to APT to help test two pricing schemes: Option A, an aggressive pricing change, and Option B, a moderate pricing change. Once the test was in market, APT's Test & Learn software found that Option A created a sharp drop in revenue -- churn raised with high risk customers but the client was simply giving away money to low-risk customers. In Option B, the story was very different. Customers who were priced up less aggressively generally stayed with the company, and overall revenues increased significantly. Losses were unchanged, and, in aggregate, the program improved company profits.

The Results

APT’s predictive analytics helped the insurer decide to roll out Option B. The system-wide profit difference between the two pricing strategies for the insurer was more than $100 million per year. The less aggressive version was successfully rolled out.
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