Estimation of claim/no-claim automobile insurnace withmachine learning methods

The aim of this study is to estimate whether new insured who will join insurance company have claim by using machine learning methods. The increase in the number of vehicles in traffic each year brings with it an increase in the risk of accidents. Increasing number of accidents increases the costs of insurance companies and this increase is also reflected in the insurance premiums. However, due to price competition in insurance companies, sales below the optimal premium cause companies to fall behind their profitability targets. In order for insurance companies to maintain their profitability, it is very important to include the profitable insured profile in the portfolio. In order to include the profitable insured in the portfolio, models that simulate individual behaviors are needed. Therefore, by using machine learning algorithms used in many sectors recently, the model that makes the best estimate of claimed policies in the portfolio is determined and compared with the logistic regression model commonly used in the insurance sector.