No abstract

It is important for an insurance company to predict the future claims in order to evaluate premiums, to determine the reserve necessary to meet its obligation and probabilities of ruin, etc. as the claim data is highly positively skewed and has heavy tail, no standard parametric model seems to provide an acceptable fit to both small and large losses. Composite models that use one standard distribution up to a threshold and other standard distribution thereafter are developed and it is seen that these composite models provide better fit than the standard models when claim data involve small and high claims. The aim of this study is to investigate the use of the composite models namely Exponential-Pareto, Weibull-Pareto and Lognormal-Pareto to model the Turkish Motor Insurance claim data. From the results obtained, it is concluded that the composite Weibull-Pareto model provides better fit to Turkish Motor Insurance claim data than the all other models considered.

No abstract

In this study, the demand for comprehensive insurance is analysed using utility theory and system simulation. A simulation study is performed to assess the behaviour of individuals with different income levels for the demand of comprehensive insurance. Simulation assumptions and input-output variables are determined using the real data set from a Turkish insurance company and the report about the insurance activities in Turkey for year 2014. The effects of income level, expected claim severity and premium level on the demand for insurance are investigated. It is concluded that while an increase in income level and expected claim severity causes an increase in the demand, an increase in premium level causes a decrease in demand.