The Application Of Data Mining Technology To Banking

Data mining (DM) technique came into being in the middle 1990s, with the aim of drawing implied and useful information/knowledge from massive incomplete, noisy, blurry, and stochastic real data.This thesis expatiates on the state-of-the-art of DM technique, with emphasis on data mining algorithms such as clustering analysis, classification analysis, dependence analysis and statistical analysis. A comparative study of three popular DM tools (IBM Intelligent Miner, SPSS Clementine and SAS Enterprise Miner) is carried out. The future trends of DM technology are also revealed.The operation of bank, stockjobber and insurance agent must product large numbers of data, use the actual database system can effective to input, query, count the data, but can't findout the relationship and rule between data, can't forecast the develop trend in future by actual data. Use DM technique not only can findout the impersonality rule from great capacity for liquor data, but also reduce the risk of finance organization. There are significant to finace organization by applicate DM technique.The application of DM technique to banking consists of four components: customer relationship management, risk management, credit grade evaluation, and service analysis and forecasting. Up to date, DM technique has been successfully applied to some internationally distinguished banks such as American Firstar Bank, Bank One Bank, and AIB. This thesis addresses the application of DM technique to banking. In contrast, DM technique has not yet been widely used in domestic banks.The thesis addresses the application of DM technology in banking with the help of the development of the IC card trade system of a certain bank in Jiang Men. This paper did many study works, such as get data, data transform, conformity data and straighten out data, ensure the correctness, consistency, integrality and dependability of the data. Specifically, i) statistical and clustering analysis in terms of the IC card customers'gender and age are conducted, ii) the IC card customers'consuming behaviors are analyzed according to their age distribution, such as IC card use times, expenditure, and the customers distributing of the stores, and iii) the history trade data of the IC card trade system is mined to acquire information that benefits the customer management and the development of new services, benefits the develop of bank trade, offer the scientific gist to decision-making by the leader of bank .