This case study aims to give you an idea of applying EDA in a real business scenario. The loan providing companies find it hard to give loans to people due to their insufficient or nonexistent credit history. Because of that, some consumers use it to their advantage by becoming defaulters.
Predict loan approval by using different variable selection methods
Assessing multiple model iterations to find the best predictor to whether or not a person will default on their bank loan. The data comes from the Machine Learning Repository - https://archive.ics.uci.edu/ml/datasets/default+of+credit+card+clients
Perform Exploratory Data Analysis(EDA) on loan applications to understand how various client attributes (like marital status, education, occupation, etc.) influence the tendency of default.
Decision Tree algorithm used to predict defaulters of bank loan customers.
Project on Bank Loan Default Prediction
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