Experience rating and bonus-malus system in automobile insurance

In a competitive market it has become compulsory for insurance companies to partition their portfolios into the risk categories with all policyholders belonging to the same category paying the same premium and to fairly distribute the burden of claims among policyholders. Existing motor vehicle insurance risk classification plans have been using to create risk classes according to the priori variables of the insureds such as age, gender, occupation, use of the vehicle etc. whose values can be determined during the process of issuance of the policy. But due to the many important factors such as the habit of obeying traffic rules or swiftness of reflexes of the driver which cannot be taken into account, the risk classes are not homogeneous enough. For this reason with the method of so called experience rating, with a correction applied to the base premiums determined by the risk classification of the insureds, it has been possible to obtain premiums closer to the risk level of the insured and to ensure fairness among the insureds. In this study firstly, insureds are partitioned into the risk classes by using Turkey MTPL (Motor Third Party Liability) insureds data and then adjustment coefficient tables are created with the methods of credibility and bonus-malus system.