Application Of Data Mining Techniques In Construction Bank Customers Management System

With the development of information processing technology and its popular application in all walks of life, how to produce and collect data is a matter of method, which has led to the explosive growth of data quantity. The traditional data processing method can’t satisfy people’s demands for higher data processing, how to find needed accurate data from large amounts of data and discover the inner relationship between data and transaction phenomena, is the problem facing us in the data processing, according to the higher demand for processing technology, the data mining technology was born, during the research of data mining technology, research of association rule is one of the most early, the researchers pay special attention to it.In the economic globalization tide, China’s financial industry is gradually opening up the financial industry to the outside world, the competitions between banks are intensified, especially bank operating income quality competition for customers is the focus of, banks use various methods in order to get good customer resources, as for quality customers, the business is a personalized service with appropriate incentives and so on, the discoveries and management of quality customers are dealt with the traditional methods, the management is identified with high labor costs, not timely treatment, data lacks of analysis; how to improve the service and management of the quality customers is one of the problems faced by the banks, the emergence of data mining technology provides a good support for solving this kind of problem.This paper first studies the related algorithms of data mining technology, based on the introduction and analysis of Appriori algorithm for association rules, SETM algorithm, DHP algorithm, Partition algorithm and other optimization algorithm, lots of work has been conducted in the analysis and summary on the Appriori algorithm, Appriori algorithm needs to scan database. Candidate item sets are generated in large quantities, improved Appriori algorithm for reference transaction data compression reduces the times of database scanning, this paper proposes an improved algorithm of Appriori algorithm, which is the use of triangular matrix processed and stored in the candidate set, so that the algorithm does not need to scan the database, by applying the two experimental algorithms in the instance, the original algorithm analysis and comparison results show that the improved algorithm can improve the efficiency of the algorithm.This paper introduces the general design, function design and database design of bank customer management system with the help of the improved algorithm, using the improved algorithm for customers of a bank loan business to mine the data. The risk of bank loan approval is analyzed for customers to provide accurate scientific basis for the business of bank lending and to avoid the risk of the bank loan business, consequently raising the capital efficiency and improving the operation and the competitiveness of the banks.