Role of Authentication Factors in Fin-Tech Mobile Transaction Security

Abstract Fin-Tech is the merging of finance and technology to be considered a key term for technology-based financial operations and money transactions as far as Fin-Tech is concerned. In the massive field of business, mobile money transaction security is a great challenge for researchers. The user authentication schemes restrict the ability to enforce the authentication before the account can access and operate. Although authentication factors provide greater security than a simple static password, financial transactions have potential drawbacks because cybercrime expands the opportunities for fraudsters. The most common enterprise challenge is mobile-based user authentication during transactions, which addresses the security issues against fraudsters. The confirmation of a user legitimation before the money transaction is highlighted by mechanisms and technologies from previous studies that may be helpful in user authentication. Internet of Things (IoT) technologies may have potential vulnerabilities for hackers to hack the user credential information for illegal use. This study aims to identify the technologies for user authentication and the opportunity for their transformation to mobile money transaction security despite having all the legally required data for a transaction. This proposed review has identified the role of multifactor authentication techniques for authentication to mitigate the risk of fraudulent transactions. The analysis through 92 articles taken from famous publishers. The most relevant articles address authentication problems, of which 54 percent describe money transaction security, and the rest of the articles highlight the supporting technology for user authentication. The study platform described the technology-based approaches with the appreciation of new ideas for secure money transactions. Multifactor authentication might be a key term in advanced security to ensure the user is legitimate by using advanced technology and algorithms to predict and find transaction risks and discourage fraudsters from trying.