Research On Personal Client Value Of The Bank Based On Fuzzy Data Mining

With the rapid development of economic globalization, informationmanagement has become an important way for banks to enhance theircompetitiveness. Therefore, customer value, as an important part of the bank, hasinevitably become the focus of competition. As the current customer informationsoftware development is characterized by fierce competition and analysis in needof diversification, digging for information has become a great challenge.Especially in customer service management, customer value requires a highstandard in prediction and frequent changes in demand. It also has many limitingfactors. These objective conditions make the mining of customer informationmore and more difficult. A new method based on customer value index systemand data mining has brought new ideas to address the growing number ofinformation resources. Fuzzy data mining methods, a more accurate way to diginformation, gets a great deal of attention for its high degree of flexibility. Thispaper gives and evaluation of bank customer value analysis based on theflexibility of fuzzy data mining.First, it studies the existing problems and characteristics of bank customers,also analyzing the factors affecting bank customers and the importance ofcustomer value. It gives us a customer value index system that is relative to thetraditionally required method for obtaining the advantage. It introduces the ideaof customer segmentation, and explores customer value.Second, in accordance with the criteria and principles of evaluation, theintroduction of an expert scoring method, and component design for the overallframework of customer value indicators, it analyzes the steps of s ystem designand designs a customer value index system.Lastly, it analyzes the principles and purposes of the fuzzy data mining model, gives an overall framework for designing the data mining model, givesfuzzy data analysis of customer value data, and obtains actually-divided resultsand forecasts. It is aimed at the needs of the modular design, and the combinationof the bank customer empirical research.