Published Paper Details:

With the enhancement in the banking sector lots of people are applying for bank loans but the bank has its limited assets which it has to grant to limited people only, so finding out to whom the loan can be granted which will be a safer option for the bank is a typical process. So in this project, try to reduce this risk factor behind selecting the safe person so as to save lots of bank efforts and assets. This is done by mining the Big Data of the previous records of the people to whom the loan was granted before and on the basis of these records/experiences the machine was trained using the machine learning model which gives the most accurate result. The main objective of this project is to predict whether assigning the loan to a particular person will be safe or not. Here Machine learning techniques are used to predict the person who is reliable for a loan, based on the previous record of the person to whom the loan amount is accredited before. The Four machine learning algorithms like Logistic Regression, Decision Tree, Random Forest and XGBoost are compared and the algorithm with highest accuracy is applied to predict the loan approval of customers.