Article,
Credit card fraud detection and classification by deep learning and machine learning
Global Journal of Engineering and Technology Advances, 13 (3): 022-027 (December 2022)
DOI: 10.30574/gjeta.2022.13.3.0202
Abstract
One of the most important contributors to the expansion and progression of a nation's economy is its banking and financial industry. In particular, over the recent past, there has been a significant increase in the utilization of credit and debit cards, whereby all customers trade transactions either digitally over the internet or physically at the stores. Here, the customers, banking institutions, and financial organizations are all being put in a difficult position by fraudulent actors. Because more recent technology is now readily available, internet banking has become an important avenue for commercial transactions. Fake banking activities and fraudulent transactions are serious problem that affects both the users' sense of safety and their trust in the system. In addition, fraudulent activities result in enormous losses because of the proliferation of sophisticated frauds such as virus infections, scams, and fake websites. These frauds are all examples of advanced fraud. This study makes three contributions toward the prevention of fraudulent activity involving credit card transactions.
