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This project builds a model to predict if Lending Club loans will be fully paid or charged off. Using completed loan data, it includes credit history and loan grades but excludes FICO scores and rejected loans due to limited data. Methodologies and results are documented for accuracy and fairness.
Minimizing bad-risk loan approvals by accurately predicting the applicant's credit risk to reduce financial losses and improve the decision-making process.
Code for classifying whether someone can repay their loan to a banking institution using a supervised learning approach: Binning and Logistic Regression.
A study, analysis and visualization of factors and relationships between those factors which determine the rate of interest and also if a person is a potential loan defaulter by using ML.