Abstract
Using a generalized linear model to determine the claim frequency of auto insurance is a key ingredient in non-life insurance research. Among auto insurance rate-making models, there are very few considering auto types. Therefore, in this paper we are proposing a model that takes auto types into account by making an innovative use of the auto burden index. Based on this model and data from a Chinese insurance company, we built a clustering model that classifies auto insurance rates into three risk levels. The claim frequency and the claim costs are fitted to select a better loss distribution. Then the Logistic Regression model is employed to fit the claim frequency, with the auto burden index considered. Three key findings can be concluded from our study. First, more than 80% of the autos with an auto burden index of 20 or higher belong to the highest risk level. Secondly, the claim frequency is better fitted using the Poisson distribution, however the claim cost is better fitted using the Gamma distribution. Lastly, based on the AIC criterion, the claim frequency is more adequately represented by models that consider the auto burden index than those do not. It is believed that insurance policy recommendations that are based on Generalized linear models (GLM) can benefit from our findings.
Highlights
As of 2016, the amount of total property insurance premiums continues to increase, which makes total property insurance the biggest part in the property insurance industry.At present, the international approaches of rate making are mainly chauvinism and humanitarianism
On 1 June 2015, as one of the six pilot areas for deepening the reform of the auto insurance rate management system in China, Chongqing officially started the commercial terms for the reform of the auto insurance rate management system
We introduce the auto burden index into the model to precisely quantify the auto types, transforming the auto types into specific values, which is described by the formula, Single commonly used accessories price × accessories loss rate ÷ auto sales price × 100
Summary
As of 2016, the amount of total property insurance premiums continues to increase, which makes total property insurance the biggest part in the property insurance industry. With the development of the insurance industry, the existing provisions begin to consider human factors, including driving record, driver’s age, family members, regional factors and so on. This is more conducive to the mobilization of the driver’s initiative, making the burden of insurance premium more reasonable. According to the regulations of the new reform, auto burden index will be introduced to quantify the model analysis. The insurance company may set different business car insurance rates, according to their own risk recognition, risk cost and risk pricing power, motor vehicles and drivers of different risk levels.
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