Conference
Sep 2026
Credit Default Prediction Using Logistic Regression and XGBoost: A Multi-Scenario Evaluation with SHAP-Based Interpretability Analysis
This study compares Logistic Regression (LR) and Extreme Gradient Boosting (XGB) for credit default prediction using 554,349 fintech loan records with a 7.95 percent default rate. Twelve scenarios covered 70-to-30 and 80-to-20 train-test splits, under both imbalance conditions, plus out-of-time validation from October...
Keiza Julita, J. Hefni, Helena Margaretha et al.
· 2026 3rd International Confe... · 0 citations