An interpretable credit risk assessment model with boundary sample identification

Experimental results on four public datasets demonstrate that the IAIBS model significantly outperforms 11 baseline models, as confirmed by the Nemenyi test. The model achieved area under the curve (AUC) scores of 89.17, 79.86, 97.48, and 66.03 on the PCL, FICO, CCF, and VL datasets, respectively. With appropriate parameter tuning, the IAIBS model maintains strong generalization ability, and each module contributes positively to overall performance. Additionally, the IAIBS model effectively interprets key predictors and prediction outcomes.