Everbright Bank Personal Quality Management Assistant Decision-making System Design And Implementation To Customers

Everbright Bank is an international large-scale commercial bank which is affiliated with the Ministry of Finance and many strategic institutions acts as its shareholders.Everbright Bank is the forerunner using the customer relationship management(CRM)systems in China.This CRM system has accumulated huge amount of data for bank's customers and transaction information.In recent years,in many cities,these local city commercial banks as the representative of the local commercial banks and Alipay,WeChat as the representative of the Internet banking to join the competition with the business banks.The purpose of this article is to help the staffs of in the branch bank use these valuable data resource to carry out the best customer service.This paper designs an auxiliary decision system which adopts the data mining technology to classify,clean up and standardize the historical data,and according to the desired output of the user,a data mining model is established,which gives the customer's subdivision pattern and type to guide the business work carried out.Data mining is a powerful way to extract important and useful information from massive data.It is an effective ways for knowledge discovery,forecast analysis and business model design in the large data age.Date mining of CRM system has many successful applications in the logistics,mobile communications,online shopping and especially,there are many exploration and experiments in the banking industry.In the paper,firstly,introduce the structure and operation mode of CRM system of Everbright Bank.Then,analyze the data mining technology from the perspective of development and application.And express the detail of mainstream technology and corresponding algorithm of data mining,especially for the C4.5 Decision tree algorithm calculation process,finally describe the excavation of the important data preprocessing methods.The fourth chapter starts from the demand analysis to analyze the purpose,principle and function requirement of the auxiliary decision system design.This part introduces the overall architecture of the auxiliary decision system and the function of each function module,and expounds the scheme and the way of the system realization.The fifth chapter introduces the hardware and software development environment and the hardware composition of the system,and combines the actual data to test the algorithm model.The fifth chapter gets the realization process of the data mining for the module of high quality customer classification and customer churn warning.In the fifth chapter,through the test of the sample data,the algorithm is verified and the rationality of the design scheme is proved.The implementation of the system is described in terms of hardware and software,especially focus on the high quality customer classification and customer loss warning analysis which all based on data mining technology.Based on the detailed description of mining database construction and mining model design,use a test database to prove the model validity and feasibility of the algorithm in the actual work condition.Although the design and implementation of the individual quality customer support decision-making system has been completed initially,it provides a useful reference for the staffs in the branch banks to carry out customer service work.However,as the first new CRM system in the Everbright Bank still has many imperfections,especially in the design of mining database,the supplement of effective data and the optimization of mining algorithm.Finally,briefly introduce the shortcomings of this system and the needed work on the next stage.