Research On Credit Rating Of Consumer Client Of Credit Card Based On Data Mining

Since. the90’s, with the development of China’s economy and the expansion of domestic demand,Credit Card Industry developed rapidly. The key of Credit Card Industry is control of credit risks. Inorder to guard against credit risks efficiently, to promote the development of the consumer creditbusiness, card issuers must establish a set of effective scientific and reasonable individual credit system.The credit rating system divided customers into “good” customers and”bad” customers. Then accordingto the historical data of different attributes, set a mathematical model, forecast the default risk of creditcard users. Decision Trees is simple, easily understanding and has low error rate, so this paper take thealgorithm as the modeling method.Firstly, this Paper combines data mining, credit card industry, credit rating together, analyzed thecharacteristics of data mining and credit rating for credit card, lay a theoretical foundation for thefollowing discussion. Secondly, consider the different feature of means of data mining, choose thealgorithm C5.0of Decision Tree as the following data mining mean, then introduce the specificprocesses of modeling with C5.0. Finally, make use of the individual credit card data which comes fromcertain bank, go through business Understanding, data understanding, data preparation, modeling,modeling evaluation, set a model based on decision tree. Then according to the specified actual demandof card issuer, adjust the Cost-sensitive Tree and prune decision tree, form a advanced model.Credit rating of consumer client of credit card based on decision tree has higher accuracy andstronger controllable nature, which can be used widely, and attributable to the cost-sensitive tree, the costof card issuer is minimize. It has directive function in practice for distinguishing credit card applicant, Ithas strong theoretic and practical significance to provide support for credit decisions,...