Abstract:Background: The personal credit default discriminant measures the size of the credit default risk, which provides an essential decision-making basis for banks. Methods: This article constructs a three-stage default discriminant model based on the DF21. In the first stage, this article selects the feature combination. This article obtains the default prediction results by traversing the decision tree from 20 to 500 and the learning rate from 0.08 to 0.12 in XGBoost. Taking the lowest Type II error, the highest … Show more
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