| Data mining technology,as the trend of the times,and the gradual development of data processing technology,has been more widely used at home and abroad.The basic idea of data mining technology is to use the data that has been accumulated in the past to find out the hidden laws through the establishment of scientific models,in order to complete the guidance and reference of the operation.As an important part of the property and casualty insurance system,the business involves a large number of customers,complex decisions on insurance and claims,and all aspects of the process are dependent on data support,which invariably accumulates a large amount of data in the process.In this context,small and medium-sized property and casualty insurance companies should consider how to use data mining technology to cope with the ever-changing developments and to make use of the historical data accumulated during the production and operation process to contribute to the operating profit.In this context,it is important to optimise marketing channels for cross-selling,strengthen customer relationship management to enhance differentiated services and improve risk management.On the one hand,cross-selling,customer management and risk management can support the smooth development of business operations,while on the other hand,the application of data mining technology can enhance the scientific nature of operations and improve work efficiency.This paper firstly explains the concepts of cross-selling,customer relationship management and risk management and their importance to insurance companies.It then introduces the theory of data mining,the data mining process,and explains the implementation of data mining related models to lay the theoretical foundation for the rest of the paper.From the perspective of customer relationship management,the k-means model in cluster analysis is used to subdivide customers into five categories with different percentages according to the subject attributes,and to classify quality customers,potential customers and low-value customers.From the perspective of risk management,the logistic model is used to filter the variables with explanatory power from the data and build a claim prediction equation,which provides a reference for risk management.Finally,based on the above findings,the study provides suggestions and new ideas for Y Property and Casualty Insurance Guangdong Branch to further realise technology empowerment and promote refined management. |
