Research On The Adjustment Coefficient Of Auto Insurance Pricing Under The Background Of Commercial Auto Premium Rate Reform

This paper is based on the background of the third premium rates reform about commercial auto insurance,through analyzing the history of the three premium rate reform in China,we can see that after the third rate reform,with the the lower limit of the independent underwriting coefficient and the independent channel coefficient,insurance-companies profit margins is compressed.Therefore,in the context of this reform,by optimizing the pricing method of auto insurance to achieve accurate division of different insurance groups will be an important means of response for insurance companies.The main research contents of this paper are as follows:The first chapter is the introduction,which is mainly about the background,literature review and research content of the research topic.First of all,through the analysis of the current situation of the auto insurance market,combined with the current reform background of auto insurance rates,it is necessary to analyze a the more accurate pricing method of the auto insurance.Then,the introduction of related domestic and foreign literatures,as well as the main contents of the paper,the methods,deficiencies used,the possible innovations and shortcomings.The second chapter is the history of auto insurance premium rate reform.Through the review of the three reform process,introuducing the main reform content,the premium calculation formula and the market conditions of the previous two reforms.And for the content of the third auto insurance rate reform,the paper analyzes the importance of auto insurance pricing segmentation.The auto insurance rate is determined by ranking the customers by the number of claims.The third chapter is a summary of the theoretical overview of auto insurance rates and the methods of auto insurance pricing.The first part mainly introduces the basic concept of auto insurance premium rates,and the second part introduces the relevant methods for auto insurance pricing that have been used so far.The fourth chapter is an overview of the three methods needed to model this paper.It includes principal component analysis method for data dimensionality reduction,open mixed Poisson distribution for grading claims,and generalized linear model for fitting the number of claims.Through the introduction of these three methods,the empirical analysis used in the next chapter is paved.The fifth chapter is an empirical analysis of the model.Mainly through the principal component analysis method and the mixed Poisson distribution to process the data,complete thetasking of dimensionality reduction and grading of the data..The second part divides the customer into more precise levels according to the number of claims.The third part is to fit the data by establishing a generalized linear model to analyze the main influencing factors under different claim strengths.The sixth chapter is a summary of the full text,mainly for the summary of the empirical results,and put forward some suggestions for the development of China's auto insurance market under the commercial auto insurance premium reform.This paper mainly analyzes the risk of insurance groups based on the number of claims,and uses the generalized linear model to study the main factors affecting the strength of claims of different groups,so as to achieve the aim of more precise pricing for auto insurance.Firstly,the principal component analysis is used to reduce the dimension of the claim data of a group of automobile liability insurance.by doing this,the multiple factors of the original data are simplified.Secondly,using the OMP distribution to fit the claim number and divide the data into different claim strengths.In this paper,the classification of different risking insurance groups is mainly divided into three risk levels: zero claim,low claim,and high claim.Finally,through the generalized linear model we can see,for the insured group with zero claim strength,mainly affected by the car factor and the human factor,and the car factor is more significant.For the insured group with medium and low claim intensity,it is mainly affected by the vehicle factor,the driving environment and the human factor.The car factor has the greatest impact,but the driving environment factor has a greater impact on the increase of the claim strength.For the high claims strength group,the empirical results are not good due to the small amount of the data.Based on these conclusion,the paper finally puts forward some suggestions on the development of China's auto insurance market,such as adjusting the optimal distribution model of the number of claims,dividing the risk level to achieve pricing differentiation,expanding the market area,and strengthening product innovation.The main innovation of this paper is to use a loss distribution function that can simultaneously satisfy the zero expansion,thick tail and heterogeneity of auto insurance claim data—open mixed Poisson,according to the claim strength of different risk insurance groups,classifying and analyzing the main types of factors that affect the strength of different claims to help insurers to achieve pricing accuracy.For the shortcomings of this article,there are two points:First,due to the limited data collected,the analysis of the group with high claim intensity failed,and the empirical results are lack of perfection.This is also the place where subsequent research can use different data for in-depth research.Second,the policy interpretation of the reform of the commercial vehicle insurance premium may not be sufficient.Because the third premium reform for commercial auto insurance was implemented in March 2018,the changes in the entire market remain to be seen.