Big data, machine learning, and artificial intelligence solutions are being used by banks, credit agencies, and other financial organizations to improve operations, save costs, and expedite debt collection. In this study, we developed and tested data-driven machine learning algorithms along with operation research to maximize debt collection recovery in banks and credit institutions. Out of all the aforementioned groupings, we concentrate on the recovery fee sector because it is the one that can potentially save these firms the greatest amount of money and expenses. Additionally, we put our plan into practice at a credit union and showed that it outperformed a few other tried-and-true techniques. Other debt categories, such as early and late collections, can also benefit from our approach.