Blogs - Insurance Services Outsourcing
| Demand modeling can help customer retention |
| By Rajesh Desingu on 11/9/2009 9:06:00 AM |
Insurance companies face many challenges because of the economic slowdown in the US. Primary amongst them is customers’ willingness to buy additional policies / products and features. In fact, as job losses continue and the unemployment rate remains high, many customers have defaulted on the payment of premiums. As a result, insurance companies not only have to target new business, but, as importantly, must hold on to existing customers.
Among the many factors that drive customer retention, the key one is premium cost / price. Price represents value to the customer, and that’s why the insurance company must be aware how much the customer is willing to pay for their products. That's not easy when you have tens of thousands of customers whose priorities and "buying behavior" have changed in the last few months because of the slowdown. Moreover, at a time like this, customers want increased value more than ever before.
How the company prices its product portfolio impacts the bottom line, and is reflected in revenues and ultimately, profitability.
Normally when an insurance company prices its products, the prices reflects the cost of the claims which is a function of severity of the claim as well as insurance company’s ability to “out-underwrite” what its competitors offer. Added to it are the profit margins and operational costs. The final price is what you and I pay for a policy. The premium does not take into account a customer’s willingness to pay.
A well-known P&C insurance company in the US, with whom I have worked with, wanted to know what influenced a customer’s buying behavior. The company wanted to identify drivers that helped customer retention and use them to predict the behavior of its policyholders.
The insurance company selected WNS to perform comprehensive analyses. WNS analyzed data on quotes offered as well as customer policies, driver data, and demographic data and devised models to identify demand drivers and help profile customers based on their willingness to pay.
The predictor variables helped the insurance company to identify the determinants of retention, mid-term cancellation and quote conversion, and devise a strategy that improved policy retention by one per cent. Profitability levels were retained by using these models in the pricing strategy. These models were then extended to the company’s other markets in the US as part of a country-wide strategy.
By outsourcing the data analysis, the insurance company has been able to retain business in the face of cost pressures. Outsourcing this work allowed the company to perform the analyses at a cost far less (one-third) than it would have had to pay had it done this in-house. Moreover, the sheer volume of data could have overwhelmed the organization. By outsourcing, the company obtained substantial benefits on both the customer retention / acquisition and profitability fronts.
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