shawn-y-sun/Credit_Risk_Model_LoanDefaults
Credit Risk Modeling to Compute Expected Loss of Loans (logistic regression, linear regression)
This project helps lenders and financial institutions calculate the expected loss on their loan portfolios. By analyzing historical loan data, it processes financial metrics, borrower characteristics, and loan statuses to predict the probability of default and potential financial loss. It is designed for credit risk analysts, loan officers, and compliance professionals who need to quantify and manage credit exposure.
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Use this if you need to assess the credit risk of a loan portfolio to inform lending decisions, optimize capital allocation, or ensure regulatory compliance.
Not ideal if you're looking for real-time fraud detection or a system to automate individual loan application approvals without human oversight.
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Last pushed
Feb 26, 2024
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