Synchronization of AI and Deep Learning for Credit Card Fraud Detection
Keywords:
Deep Learning, AI, Fraud Detection, Credit CardAbstract
At current scenario, more and more businesses are moving toward accepting credit card payments online, there is a growing demand for an efficient fraud detection solution that is able to send alerts in real time that can be acted upon. The banking and financial sector of a country is one of the most significant contributors to the growth and development of the economy of that country. In recent years, consumers have become increasingly reliant on credit and debit cards for all of their purchasing needs, whether they prefer to do their shopping online or in-store. Because of this, the number of people using bank cards has skyrocketed. As a result, the number of monetary exchanges completed with plastic has increased significantly. Customers & other organisations are all being put in a precarious position as a result of fraudulent actors in this situation. Internet banking has emerged as a significant channel for conducting business deals as a result of the widespread availability of more recent technological advancements. There is a significant trust and safety issue caused by fake activities and fraudulent transactions. This is a problem because fake banking activities and fraudulent transactions can be committed by anyone. Additionally, the proliferation of sophisticated frauds like virus infections, scams, and fake websites cause enormous losses due to fraudulent activities. These frauds are just some of the ways that fraudulent activities can result in enormous losses. All of these cons are examples of more sophisticated forms of fraud. This research makes three important contributions to the fight against fraudulent activity involving the use of credit cards.
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