Study On Risk Control Of Vehicle Insurance Based On Data Mining

In recent years, car ownerships are rising in China. As an important means of transport,vehicle accidents such as rollover, collision, scratch and other accidents are increasing, andtherefore the business of insurance and claims increased. On the one hand, it led to thedevelopment of automobile insurance industry in china, but with the development of theinsurance business. There have been an increasing trend in insurance risk, how to get theinsurance company to avoid risk to ensure profits, is the problem for the insurance industrycontinues to research. For the insurance companies, getting control of risk factors in insuranceclaims has become necessary and urgent.With the rapid development of modern computer technology, the era of big data has beencome, which is analyzed by data mining technology and as a reference. Data mining technologyis from the huge, partial, irregular, uncertain databases to identify information hiding in the dataand associated in the process, which is also a decision support process. This paper will examinethe application of data mining technology in the automobile insurance and claims risks control.By vehicle insurance claims case data, data mining techniques was used for analyzing risks.Specific studies are as follows:The first chapter introduces the current development of automobile insurance industry andproblems in china, and the problems were simple analyzed; it also introduces the domestic andforeign automobile insurance claims research status regarding pricing, risk control, and otheraspects lie to lose.The second chapter describes the basic theory and method of data mining techniques,definitions and steps architecture and design construction of a data warehouse, and data miningtools and mining species are described.The third chapter through the automobile insurance claims process for the overall demandanalysis of the insurance company, providing the insurance rates, insurance risk and operatingperformance of the three specific needs.The fourth chapter combines actual work of Shandong zhonghua company insuranceclaims with data cleaning and classified, based on the relevant division and analysis data miningsystem for the overall design. The fifth Chapter is by digging for insurance product pricing, risk management andinsurance claims cheated pay characteristics of customers, and the results were verified.Finally the research was concluded and data mining techniques were forecasted in thedevelopment of the insurance claims industry.