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Any credit business has certain risks, and the credit card business has the characteristics of unsecured mortgage. Therefore, credit card is a high-risk financial product. Therefore, it identifies the influencing factors of credit card default behavior and accordingly defaults on credit card holders. Risk measurement and forecasting will help banks prevent and resolve credit card risks. However, the basic data of credit card, bank access and credit card behavior have a considerable degree of relationship with the occurrence of default. This study is based on the number of credit card circulation card customers of a bank as the parent sample, plus the number of sampled samples of the ratio of 1:1 and 1:3 between the defaulting household and the normal household. The total number of samples is divided into three types of samples; Three types of independent variables, "banking channel" and "swipe habits", there are seven different combinations of independent variables, and the combination of various types of Logis regression model analysis to explore its optimal Logistic regression analysis model, and Confirming those variables is an important factor affecting cardholder defaults.
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