Research On Classification Of Banking Financial Customers Based On Data Mining

With the development of globalization,the deepening of the Internet,the improvement of people's living standards,so that the people have more surplus wealth,the competition between banks is becoming increasingly fierce.Personal finance business as the focus of inter-bank competition,how to provide customers with better financial services to become the key to the competitiveness of banks in the competition,banks in the context of globalization,information technology to maintain the original vitality,to obtain more profits,it is necessary to put customers in an important position in the development of banks.But banks have limited resources and bank managers are unable to accurately grasp the attributes of all financial clients,which could result in banks being biased against their own needs when providing financial services to their customers.Therefore,banks need to master the customer's past financial data on the basis of its effective classification,in order to better manage customers,to provide customers with matching financial services.On the basis of mastering a large number of customer information,the use of data mining technology,the scientific classification of customers,to find the internal relationship between bank customers and financial management business,for customers to match their own development of financial products,dynamic tracking of the basic situation of customers,the development of high-quality customers,mining potential customers,continuous innovation products,Provide financial products suitable for different customer groups.Data mining technology,as a technical means to extract hidden valuable information from massive data,plays an important role in the study of bank financial customer classification.Through data mining technology,the bank's customer information as the research object,the establishment of the Customer Center database,its in-depth analysis and accurate classification,understand the customer's consumption tendency,according to the different customer attributes to distinguish the appropriate bank personal finance product category,in order to provide domestic banks with±personal financial management business ideas and technical support,Reduce the financial risk caused by the mismatch between customers and financial products,so as to improve the quality of service of banks and bring value profits to them.Based on the research at home and abroad,this paper first summarizes the research status of bank financial customer classification at home and abroad,and in the study of some personal finance business problems existing in China's commercial banks,this paper makes an understanding of the current situation of bank personal finance business at home and abroad from the practical point of view,This paper studies the influence of economic globalization and the great development of Internet on the personal financial management business of banks,and finds out the problerms existing in the personal financial management business of Chinese banks and the significance of the classification of bank financial clients.Secondly,the method of customer classification and the basic theory of data mining are introduced,and the two classification methods used in this paper are discussed separately.Finally,using data mining technology to filter data,cluster analysis of customer data,and establish decision tree model,according to the similarity and difference between financial customers to divide customers into different categories,for banks to carry out financial management business to provide ideas,so that customers and banks at the same time to maximize the benefits.