Research And Application Of Data Mining In In-Surance Customer Data

With the rapid development of the modern information technology in China, the enterprise has gradually accumulated a lot of data, how to use and analyze these data becomes a difficult problem setted in front of the enterprise. The application of data mining arises at the historic moment. Nowadays, data mining affects the management and decision-making of the enterprise in all aspects. The application of data mining tools and plat-form,which are based on the data analysis, in the enterprise also gradually become popular.In recent years, along with the domestic insurance companies con-tinuously introducing new products and the entry of foreign insurance companies, insurance companies in our country are faced with increasingly fierce market competition.In order to decrease the cost and improve the customer response rate, solve the problems of the traditional net-type marketing, using the data mining technology to analyze the huge amounts of data that the insurance company accumulated for many years, excavating its internal information and business opportunities, so as to timely and accu-rately understand and grasp the market and improve the product’s market share, are of great significance for the insurance enterprise’s development.This study, using data mining algorithms and data mining analysis tools, combined with an insurance company’s customer data, tries to clas-sify the data and excavate associate insurances, so as to find the charac-teristics of the data, understand the client’s buying behavior as well as the relationship between different insurances. Also, the study analyzes the customers’consumption behavior, to get support for customer groups ori-entation and combined insurances promotion, so that to develop targeted marketing solutions and make it possible to take different marketing strat- egy according to different levels of customers.This paper expounds the application of data mining technology in in-surance customer data analysis, the main work includes:1. Analyzing and introducing the background and current research status of this topic as well as the application of data mining in insurance.2. The relevant theories of data mining technology is introduced, and the related technologies and tools of data mining are compared and summarized.3. In this article,the data mining algorithms are introduced in detail, and K-Means algorithm are put forward.4. Using the related theory of data mining technology, combined with the insurance customer data demand analysis and data pretreatment process analysis, putting forward the insurance customer data mining analysis model as well as the cross-selling analysis model and classification of customer segmentation model, and elaborated on them.5. Combining clustering analysis of classic K-Means algorithm with the improved algo-rithm to analyze insurance customers’training set data, and giving the re-sults’accuracy comparison of the two algorithms’classification.6. Corre-lation analysis results of Insurance customer data is given.7. Tables and rules of Insurance customer data processing and classification are given.8. With the training set, using the C4.5decision tree to export the classifica-tion rules, and classifying the training set data, analyzing the classification results. Analyzing the correlation according to the associated Apriori algo-rithm and samples of data.9.The main work is summarized, the existing problems are probed, the direction of the future work and research is pointed out.