Hato Schmeiser

When determining the optimal deductible level for an insurance policy, a policyholder faces two sources of uncertainty. First, uncertainty arises from the randomness of future losses. Second, the opacity of the functional forms of the policyholder’s loss distribution and utility function also contributes to uncertainty. While the academic literature focuses on the former, we additionally include limited information on these functional forms in our model setting to reflect real-world decision making. That is, we draw on an expected utility framework and analyze the relationship between optimal deductible levels under limited and full information. We also derive several decision rules under limited information in order to approximate the optimal deductible level under full information. To support real-world decision making, these rules could be easily implemented in an online decision aid.

This paper examines the relationship between customer satisfaction and profitability at the level of the individual customer. In many industries, investigations detect a positive, decreasing relationship between customer satisfaction and firm profitability. The insurance industry has rarely been the object of such investigations. Pooser and Browne (2018) started this discussion in 2018 by examining U.S. insurers at the firm level. We provide reasons why the positive satisfaction-profitability relationship might be reversed, particularly in the case of the insurance industry. We conduct an array of OLS regressions with customer level data. Our results reveal a strong positive relationship between customer satisfaction and profitability. The effect is considerably large and also robust when investigating the effect of several customer characteristics on this relationship. We recommend that the increase in profitability is induced by a strong positive correlation between customer satisfaction and premium income, while satisfaction is not associated with the combined ratio.