According to the demand of bank credit business, a credit decision system is established. The system mainly uses principal component analysis and eXtreme Gradient Boosting algorithm to establish a credit risk assessment model. When calculating the index weight, it proposes a more accurate method: combination weight method, which combines the advantages of entropy weight method and expert scoring method to calculate the relatively accurate weight. Then, the credit risk of each enterprise is analyzed quantitatively. Through the results, we give the corresponding credit strategies of banks in different situations.
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Credit decision system based on combination weight and eXtreme Gradient Boosting algorithm
Semantic Scholar · Physics · 2021
Abstract
According to the demand of bank credit business, a credit decision system is established. The system mainly uses principal component analysis and eXtreme Gradient Boosting algorithm to establish a credit risk assessment model. When calculating the index weight, it proposes a more accurate method: combination weight method, which combines the advantages of entropy weight method and expert scoring method to calculate the relatively accurate weight. Then, the credit risk of each enterprise is analyzed quantitatively. Through the results, we give the corresponding credit strategies of banks in different situations.