Predict If a Customer Would Signing a Loan

Abstract

As the loan is one of the most important products of banking and financial companies who have interests in personal loans face a lot of competition from their competitors. Hence to increase profitability and maintain a healthy lending market the company requires predicting customer churn and all the banks are trying to figure out effective business strategies to persuade customers to apply for their loans. Machine learning algorithms have a pretty good performance on this purpose, which are widely used by banking. In this project, there are lots of people applying for bank loans but the banks have limited assets which they have to grant to limited people. This project is done by classifying the previous records of the people which contains various data such as employee id, age, pay schedule, income, years, and months employed, amount requested to predict whether a customer would sign for a loan or not based on their financial history.