Machine Learning approach for the Evaluation of loan defaulters

Abstract: In today’s world, obtaining loans from financial institutions has become a very common phenomenon. Every day many people apply for loans, for a variety of purposes. But not all the applicants are reliable, and not everyone can be approved. Every year, there are cases where people do not repay the bulk of the loan amount to the bank which results in huge financial loss. The risk associated with making a decision on a loan approval is immense. Hence, the idea of this project is to gather loan data from the Lending Club website and use machine learning techniques on this data to extract important information and predict if a customer would be able to repay the loan or not. In other words, the goal is to predict if the customer would be a defaulter or not.

Keywords: Lending Club, peer-to-peer Lending, EDA, Machine Learning.