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In recent decades, China’s insurance industry has been developing in high speed and playing an irreplaceable role in social security and financial system.But compared with some developed countries,there are many drawbacks in insurance industry of our country.There is a large gap on the regional development of insurance industry in our country.Insurance data analysis is an important application field of statistics. We can use it ratifying the premium, estimating risk and loss ratio,predicting premium income and the amount of report or settlement.With the expansion of the scale of insurance, the data also tends to be diversified, which make us analyze the correlative more difficultly. Reasonable use of the statistical theory and method of statistical analysis of the relevant data of the insurance industry, explore the law of development of the insurance industry is of great significance to guide the healthy development of insurance industry in our country.Based some statistical theories and methods, this article has explored the two specific issues of the insurance industry in China. Specifically, on the one hand, we find the development degree of the insurance industry is different in different places. This article uses the premium income, insurance density, insurance depth of three indicators, using clustering method analyzes the31provinces (cities) of the development of insurance market, it is concluded that in the east, west and central regions, the insurance market, insurance demand gap is quite big, development is very uneven. On the other hand, we start from microcosmic problems to China’s ping an branch in recent years, the actual data of automobile insurance in henan province as an example, using time series method, studied the case report amount, the amount of insurance company, the relationship between the indexes of premium income and the corresponding modeling and prediction problems.Because the data has a seasonal trends, this paper through the season index method, the various indicators to eliminate seasonal trends, to make the fitting and prediction.In addition, considering the case reports and may have a certain amount of correlation, this paper again by co-integration analysis, impulse response functions to analyze data, further prove the issue of the final amount of the current report of measuring tool.
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