Data Mining Based Commercial Bank Customer Segmentation Management System Design And Lmplementation

Customer segmentation management system is based on the bank’s internal customer resourcedata mining analysis, from the customer information to find out the law and conclusion, as the bankdecision-makers to provide decision making reference to a set of management system.The bank customer segmentation management system to Hangzhou branch of industrial bankcustomer data as data source, used three kinds of data mining algorithms, respectively, the neuralnetwork algorithm, decision tree algorithm, genetic algorithm, the user can select a data miningalgorithm to analyze. The system test results is the use of Industrial Bank CRM system customerdata mining analysis, testing results are available by chart, histogram, curves and other way of seeing.This system uses the user classification management, low user also is ordinary bank staff only hasdata entry rights, while advanced users is also the bank executives with data mining analysis andstructure view and user management functions. According to the actual needs of the development,practical, open design allows the data sharing capability is very strong, and convenient dataexchange. Data entry in a variety of ways, in addition to the direct manual input, also includes bulkdata import capabilities, to provide data collection efficiency.In this paper, using a variety of data mining model, the banking system to do a systematicanalysis, according to the customer price rule, identify potential customer groups. This systemmainly includes the following several aspects of the work, the simple introduction of data miningand other related concepts and technical knowledge, to the commercial bank subdivisionmanagement has made the detailed design, including needs analysis, outline design, detailed design,database design as well as the final application analysis.