Built an end-to-end credit risk model: XGBoost(Default prediction) + SHAP + Streamlit dashboard.
Key Results:
0.73 ROC AUC, 76% recall for catching defaults Business-optimized threshold: 50% approval rate, 9.7% bad rate SHAP explanations for every loan decision Production-ready: modular .py scripts + interactive dashboard
GitHub: https://github.com/shashi-hue/loan-default-risk-system
submitted by /u/lambilund to r/learnmachinelearning
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