Application Of Decision Tree Algorithm In User Loss In Insurance Industryy

With development and application of data mining technology,has achieved good results in the field of multiple industries.Through the efficient combination of mathematical statistical model and information technology,it can accurately process larger volume and more complex data information,quickly reflect statistical analysis results,and provide important support for enterprise management and operation decisions.As an important algorithm in data mining,decision tree algorithm as applied to the insurance industry,to many aspects of improving customer information analysis,customer fraud analysis,marketing analysis,user loss analysis and so on the accuracy of the results.Finding potential surrender users in time and formulating personalized insurance services according to user needs and behavior characteristics is conducive to the stable development of insurance companies.Based on this,the paper on the decision tree algorithm in the insurance industry users loss prediction of the practical application of research,to improve the traditional decision tree algorithm,and applied to the user loss prediction model,further enhance the inductive analysis of the various data accuracy,for the operation of the data mining technology provides a good space.At the same time,the model prediction results are applied to the customer relationship management of insurance companies,aiming to improve product design and service quality.Through the improvement of the traditional decision tree algorithm,the Clementine data mining platform can greatly reduce the workload,improve the efficiency of data mining,and has a highly flexible data interface.With Oracle,IBMDB2 and SQL information can establish a good interactive relationship,customer churn analysis for insurance enterprise users to provide technical support.First of all,the study to introduce the research background and research significance,elaborated the present stage domestic and foreign research situation,the paper USES the method and the main research content,the concept,development and application of decision tree method and process were analyzed.The study then expounds the theory of customer Relationship Management(CRM),and defines the application value of CRM theory in the insurance industry.Secondly,the paper designs the user loss prediction model of the insurance industry,analyzes the common causes of user loss in the insurance industry,subdivides the key indicators of the user loss prediction model based on the enterprise operation perspective,price factors and product quality issues,and improves the decision tree algorithm to make it more in line with the needs of the insurance industry user loss prediction.Finally,the research will be RS object of the insurance company as a case,the case enterprise users information generation into the model,analyzes the RS of the company’s business model,the RS projections on the user loss of insurance company,points out the influence factors of losing customers.According to the prediction results,this paper puts forward targeted management suggestions to help insurance companies avoid user loss,and hopes to provide some reference for relevant researchers.