Abstract
The purpose of this study is to find the key factors of the amount of outstanding balances among revolving credit card users in Chinese credit card market. A Heckman procedure is used to analyze a dataset of a bank in China. The small amount of revolver coursing imbalanced problem, and we try to use the rebalanced method in machine learning domain to deal with the problem. Results show there are differences in the determinants of being a revolver and the amount of the outstanding balance. Age, housing condition, industry, and average cash advance amount per time, etc. are significant related to the outstanding credit card balance.
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