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Repository Details
Loan default prediction is an important aspect in banking industry. In Finance and Banking sector the losses incurred by this Industry due to loan defaults or we can say customer not paying back their loan is increasing drastically. In this study we have built a loan default prediction model on the data collected for borrowers of multiple states in the Unites States of America. The research focuses on constructing a model that would predict whether the borrower would repay the loan or would end up being a defaulter. The research uses Random Forest classifier, Adaboost classifier and Artificial neural network model to compare the performance of these classifiers. It also works on understating and obtaining the important features that are to be monitored carefully before sanctioning any such credits. Keywords: Credit risk analysis, Loan Default, Machine Learning, Random Forest classifier, Adaboost Classifier, Artificial Neural network.