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Kelvin Lin

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Review Open access Sep 2026

Explainable Machine Learning for Home Equity Line of Credit Risk Assessment: A Multi-Model Comparison with SHAP Interpretability

The findings indicate that interpretable machine learning can give lenders a defensible account of every credit decision — a capability that serves both regulatory oversight and the individuals whose applications are under review.

Kelvin Lin · 0 citations

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