Loan Approval Prediction Based on Tabu Search Optimization Technique

The banks and their customers know loan approval methods. Although traditional methods like taking all the relevant information are time-consuming, there is a need for technology, which can result in machine learning algorithms being applied to the data sets that contain the past data of customers to help in predicting whether the loan is being approved or not. Now the question is how much these algorithms predict accurate results, our research paper tells how the optimization we applied will maximize the number of loan approvals and minimize the risk analysis. We applied the Tabu search optimization along with a few machine-learning algorithms on the loan data set, and our accuracy is about ${9 8 \%}$.