Abstract
A policyholder's degree of health risk could be classified as normal or better than normal or high or bad. We examine the relationship between the policyholder's degree of health risk and the effect of his demographic factors. A quantitative model is proposed to support decision-underwriting of the insurer by segmenting the health insurance underwriting portfolio to four risk groups, which are different and mutually exclusive (low risk, normal risk, high risk, bad risk) based on some demographic factors affecting the degree of risk. The likelihood of the insured to risk groups has been estimated using polynomial logistic regression analysis, and the degree of risk most likely has been determined to take appropriate underwriting decision. This study is based on experience of one of the insurance companies in Saudi Arabia, and the subjects were selected using a random sample for detailed data on individual health insurance during the period 2013-2015, based on the random numbers generated. We found a relationship between the degree of health risk and the policyholder's demographic factors. Using this result, we were able to calculate the probabilities of affiliation of the insured for various degrees of risk. This paper presents a model for the rationalization of underwriting decisions in the individual health insurance, by classifying the policyholder within the appropriate insurance risk group. In addition, this paper enables to determine the appropriate insurance premium for every policyholder according to his degree of risk and this leads to reduction of the possibility of adverse selection of insurer.