| Data mining is a potentially valuable knowledge (model rules) extracted from thelarge amounts of data. Data mining techniques after several decades of development，has been widely used in finance， insurance， telecommunications， electricity andother fields. Data mining technology in the banking industry is the technologicaldevelopment of hot spots， is also an urgent need for the development of competitionof the banking industry itself. Currently， some foreign banks are trying to use datamining technique to solve the various problems in the management of bank credit andlooking for new opportunities， and provide strong support for decision making， andproduced a number of successful use and management models. Rural creditcooperatives facing due to the special nature of the domestic financial sector， thereare many problems in the credit management and are difficult to control the risk， isalso an urgent need to use data mining techniques to control credit risk and improvecredit management.Hunan rural credit cooperatives, that the status of the rural credit cooperatives,credit management and the challenges in the management of rural credit cooperatives,data mining, data mining process, the key technologies and mininganalytical methodsin the analysis. Discusses several steps of data mining techniques applied to thebanking credit management, and several steps involved in the technology and methods,as well as the popular data mining tools are described. Then use the C4.5decision treealgorithm on small loans in rural credit cooperatives, customer credit evaluation andloan risk management carried out an empirical analysis. Then proceed from thecharacteristics of the rural credit cooperatives, credit business using data miningtechnology to enhance the knowledge of the relevant data, including credit analysis ofcustomers, credit risk analysis, credit decision support for rural credit cooperatives,credit management system model system design and data mining framework. Creditmanagement system for rural credit cooperatives to build data mining provides areference to the role to improve the efficiency of the analysis before the loan of theHunan Province Rural Credit Cooperative, the quality of decision-making in loan andcredit management has a very significant effect.Finally， the rural credit cooperatives to establish the credit management data mining system， the difficulties and implementation of recommendations. And in thisarticle the work summary list of the limitations of this study， research work andfurther outlook. |
