Machine Learning Algorithms for Predicting the Loan Status

Abstract

Nowadays, more people in India are asking for loans. Whether a consumer or client pays back a loan determines how many loans a bank makes or loses. In the banking industry, improvement is essential. As the process is manual, many mistakes could be made in identifying the real candidate who is applying for a loan for the first time. Each problem has a fix with us. To make our lives easier and to give us a sense of completion, we have machines. By combining different categorization algorithms with historical candidate data, a machine learning model was created. If the application is allowed or not depends on how the system evaluates the candidate's prior performance data. The loan length, loan size, age, and income (if the client would have a job) are the most crucial variables for deciding there. Bankers can better comprehend the client's behavior by looking at the graphs that show the results. On the basis of the data supplied, it is utilised to establish loan eligibility. When the project's results were uploaded to score the predictions, they came back at 0.7986, which is a decent result.