ML project to predict loan default risk based on customer data. Used Logistic Regression, Random Forest, and SVM to classify risk levels. Evaluated with ROC curves, confusion matrices, and classification reports. Helps banks/fintechs make smarter lending decisions with real data-driven insights.
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ML project to predict loan default risk based on customer data. Used Logistic Regression, Random Forest, and SVM to classify risk levels. Evaluated with ROC curves, confusion matrices, and classification reports. Helps banks make smarter lending decisions with real data-driven insights.
anvisgit/Credit-Risk-Analysis
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ML project to predict loan default risk based on customer data. Used Logistic Regression, Random Forest, and SVM to classify risk levels. Evaluated with ROC curves, confusion matrices, and classification reports. Helps banks make smarter lending decisions with real data-driven insights.
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