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Most insurance companies find it hard and hectic to pay claims that had not being anticipated. In order for the companies to be able to make enough reserves to cater for the claims, the average survival time for a claim to occur and then settled in an automobile insurance companies need to be determined. Therefore, the project used survival analysis techniques to analyze this problem. The techniques that were employed include both the product limit estimator and the cox proportional hazard model. The variables that were analyzed in this study were primarily; type of vehicle ownership, type of policy issued, nature of the claim, size of the vehicle and place of residence for the respective customers. The objectives of the study was to compare statistically and graphically the Kaplan Meier survival graphs of different covariate groups and the time a certain vehicle takes for a loss to occur mostly after occurrence of the insured risk and also used a cox-regression to test for their significance. The study used on secondary data that was acquired from one of the insurance Company in Kenya. The review was motor vehicle claims data for 2018 where the information was coded and analyzed using descriptive statistics. The study showed that ownership and residence were significant risk factors that contribute to the occurrence of a loss but they are insignificant in claim settlement using Cox regression model and log rank test. The size of the vehicle and the type of policy given out were significant covariates that influence claim settlement time.

Modeling of Average Survival Time for a Loss to Be Handled in Insurance Company