Predictive Analysis of Loan Data using Machine Learning

For banks and other financial institutions, loans are the primary source of income. As a result, a variety of loan types are offered depending on certain limitations. Banks face difficulties in determining whether or not to approve the applicant's loan. To evaluate whether a loan application may be approved, loan data must be analyzed. Giving a loan without first analyzing the applicant's data is risky from the bank's perspective. In this study, loan data is evaluated utilizing a combination of feature selection and appropriate machine learning algorithms, including clustering, association, and classification methods. We can determine whether a loan can be approved or not by employing a number of algorithms. In order to choose the best strategy, these algorithms are also contrasted.