Loan Default Prediction Using Machine Learning

Loan Default Prediction Using Machine Learning

1 DR. SAVITA CHANNAGOUDAR, 2 VENUGOPAL A, 3 GANESH RODDANAVAR, 4 NAGANAGOUDA S PATIL

1 Associate Professor & HOD, Department of Information Science and Engineering, STJ Institute of Technology,

Ranebennur

234 UG Students, Department of ISE, STJ Institute of Technology,  Ranebennur

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Abstract By anticipating loan defaulters, the bank is able to reduce its non-performing assets. Three primary predictive analytics techniques—I Data Collection, II Data Cleaning, and III Performance Assessment—are used to research the prediction of loan defaulters. Experimental investigations reveal that when it comes to loan forecasting, the KNN model performs better than the Decision tree model.

Key Words: Machine learning, Loan prediction, Banking, KNN.