Application Of Data Mining In Medical Insurance Claims Analysis

Since China’s accession to the WTO, more and more insurance companies enter China. China’s insurance industry begins to flourish, so that the insurance industry than any other industry has more data that can be tapped. The large concentration of data is the trend of informationization of China’s insurance industry. Making correct analysis of and mining latent information in the data by means of data mining technology as well as processing the information can produce a better product or provide a better service to customers. On this basis, the customer claims risk can be effectively controlled. Therefore, study on data mining technology is of great significance and practical value for the further development of China’s insurance industry.In this paper, a systematic study is on the development of insurance industry, the application of data mining technology, data mining theory, and data warehouse theory. It analyzes the process of the business of medical insurance settlement of claims and makes it as the key point. It also defines the three factors which constrain the operating management of the life insurance corporation:the rules of the rate of the insurance products, the control of underwriting risk and the improvement of business performance. Then, the modeling of data warehouse and the overall design of the data mining system is done based on the basis. The data of the business of medical insurance settlement of claims from actual life insurance corporation is used for data mining analysis, firstly, the SISS data integration services software from Microsoft corporation is used to the extraction of data, transition and import the data to the data warehouse; secondly, the SSAS data analysis software together with clustering analysis algorithm, decision tree algorithm and neural network algorithm are also used in this paper. Empirical research from three aspects of identifying the customer characteristics which the claims are prone to occur, the judge of the customer risk level and the identifying of the case of the customer claims cheat are done. The useful advice is proposed for the improvement of the operating management of the life insurance corporation based on the research.