A Systematic Literature Survey on Credit Card Fraud Detection using Machine Learning Techniques

Credit card fraud transactions are a major problem in the banking industry. This study explores the possible ways to detect fraud transactions using Deep Learning (DL) as well as Machine Learning (ML) models. This study tries to attempt to discuss multiple ways to detect the fraud transaction. A better understanding of all approaches to make a better decisionmaking model for detecting a fraud transaction. This paper reviews fraud transactions, challenges, and their solutions. This study highlights strategies for detecting both established and emerging fraud patterns. Academics and businesses looking to improve their fraud detection efforts might benefit greatly from its description of important data mining techniques and identification of the nations most vulnerable to financial fraud. Alongside summarizing significant contributions by various researchers in the financial fraud domain, this review expands the scope of analyzed articles beyond earlier studies. In order to improve financial security measures, the research also emphasis how important it is to continuously innovate and adapt.