Blockchain and Machine Learning Approaches for Credit Card Fraud Detection

Abstract

A credit card is a convenient and widely recognized method of making cashless transactions both online and offline. One of the most significant benefits of using a credit card rather than a debit card is that it allows you to borrow money to pay for your transactions. As well as the majority of online fraud occurs during a card or online transaction when a user attempts to buy something or move money. Nowadays lots of technology introduced for secured money transactions, that's blockchain technology. The blockchain has the potential to evolve into a distributed ledger, offering a revolutionary new form of trustworthy third-party authentication. Because of the long history of credit card systems, it is easier to understand and security has always been triggered by a process of delegating risk to third parties. Blockchain technology has the potential to avoid these types of losses from occurring in the first place. This study examines how Blockchain technology may be applied, how it might br made safe, and how it might be used to reduce the danger of credit card data being compromised. Additionally, this article identifies and discusses a mechanism that may be created utilizing current technologies, such as multiple identification, SR4S randomized OTP (One Time Password), and biometric tools, to avoid the loss of credit cards.