The application of a corporate bond default risk-identification model to digital economic security
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- A CatBoost-based risk identification model is developed for corporate bond default prediction.
- Financial performance and corporate governance indicators were jointly incorporated to improve risk recognition.
- The proposed model achieved 0.88 accuracy, 0.91 F1 score, and 0.99 precision at a training set size of 1000.
- CatBoost reduced recognition time to 0.9 s at 40 iterations, outperforming Random Forest, Back-Propagation, and Logistic Regression models.
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