The Empirical Studies Of BMS In China

Bonus-malus system (BMS) is a mechanism that adjusts the premium paid by insurance applicants according to customer’s individual claim history during renewal of insurance. If no claim records the previous year, they will be rewarded, otherwise, be punished. As one of the primary competitive methods, more and more insurance companies focus on BMS. Nevertheless, compared with BMS used in foreign countries, there exist multitudinal shortcomings for our domestic BMS. This article makes researches on Third Party Liability using the method of empirical analysis, and gives a horizontal comparison between BMS’s abroad and domestic based on the latest international researches.This paper includes five chapters, in which we analysis relative theories and list relative evidences, at the end of this article, some conclusions are presented.The first part of this article introduces the dissertation’s background and its academic significance, relative researches at home and abroad, the contents, research ideas as well as research methods of this study.The following part of this paper includes two sections. Section one describes the risk factors that impact car insurance pricing, mainly including human, vehicle and environmental factors, in which various sub-factors are contained. In section two, we introduced BMS, and describe its three constitute elements. After that, we simply display the meaning for implementation of BMS in a insurance company and finally we depict the advantages and disadvantages of using BMS.In the third chapter two BMS models are constructed, in one of which claim numbers is the only factor to be considered. For the other model, we not only consider the number of claims but also the sum of claims. In the first section of this chapter, we describe the former model, including its construction process, model features as well as three styles, which are path-dependent BMS, endorsement-considered BMS and insurance Liability-related BMS. The second section of this chapter describes another model. Three conditions are considered: one for BMS that consider both claim number and sum of claim, another BMS that considers claim number, sum of claim and liability-related BMS. It should be noted that in this chapter no theoretical models are established, all the models we establish are for application.Chapter four introduces several evaluation factors of BMS, which are utilized in next chapter for empirical purpose. These factors are mainly as follows: Relatively Stable Average level (RSAL), this indicator is used to measure insurance policy concentration at the highest discount group when BMS reaches a steady state. The smaller RSAL is the higher concentration. Premium Variation Coefficient (ε), this indicator is the best measure of the severity index. The larger the indicator is, the more severe the BMS indicates and the stronger its ability to identify risks is. Elasticity, this indicator measures BMS’s response to changes of sum of claim. The larger elasticity is, the more severe BMS is. Other assessment indicators for BMS such as Optimal Retention, hidden penalties for new drivers as well as speed and premiums for a steady state will also be touched upon in this chapter.The last chapter is an empirical analysis that divided into three sections. Section one takes Third Party Liability insurance as an example to horizontally compare four BMS models’merits and weakness. These four BMS models are version 2007, PICC Edition 08, Scale version 08, and Danish version. The next section briefly introduces the characteristics of BMS abroad, aiming at offering some Assistance to improve our existing BMS. The third section describes some flaws of our BMS. The last section presents some suggestions for our BMS improvement, such as consider sum of claim and increase premium discount level.In aggregate, the empirical analysis in this paper is based on our current situation of BMS. As for the models constructed in chapter three, their merits and weakness detection should be continued later, as the models are still out of utilization in our country. Our BMS needs to be improved to avoid too less considering factors. We recommend that during the improvement, each insurance company should take actions that suit local circumstances. When drawing up their own BMS, they had better combine their improvement policies with other factors, for instance, local economic, cultural and geographical circumstances.