In this paper fraudulent crediting of amounts is the primary challenge that clients encounter in the finance sector. On the other side, frauds have accompanied credit card innovation since it began. Many rule-based techniques that were used in the past to identify fraud were ineffective at managing the large number of variables. However, in order to prevent customers from paying for more credit, it is imperative to detect fraud. Machine learning techniques in an effort to combat corruption, the government is also pushing digital currency in this day and age. Although many people use credit cards and ATM cards to complete their transactions, they are not aware of the potential for fraud. An attacker utilizes the information of others to perform a fraudulent transaction, which results in billions of dollars' worth of losses annually. To lower the losses, effective fraud detection algorithms can be applied. The sophisticated machine learning methods these algorithms rely on can be useful to fraud investigators. © 2024 Elsevier B.V., All rights reserved.