AI-Powered Fintech Solutions for Travel: Combating Identity and Payment Fraud

Abstract

The tourism industry has witnessed a huge rise in online payments, which, in turn, has left it vulnerable to payment fraud and identity theft. Despite the widespread application of traditional fraud detection systems, including rule-based systems, these systems are likely to struggle to keep up with the ever-evolving fraudsters' tactics. Financial technology-based fraud prevention mechanisms using Artificial Intelligence (AI) have been an effective means of overcoming such limitations. AI techniques, including machine learning, deep learning, behavioral analytics, and biometric authentication, offer improved fraud detection functionality through real-time analysis of large volumes of transactional data. However, the research gap still prevails with the integration of such AI models with other emerging technologies, including blockchain and cloud computing, for the purposes of global fraud prevention. Moreover, despite the fact that the application of AI has been studied along numerous dimensions of fraud detection, a research gap prevails in the literature with respect to its responsiveness to the dynamic nature of fraud patterns and its scalability during peak travel periods. Another notable research gap area is the investigation of ethical and privacy concerns that emerge with the use of biometric data in AI-based fraud prevention mechanisms. Furthermore, the incorporation of predictive analytics to forecast fraud risk, as well as the development of more interpretable AI models to detect fraud, are issues that require investigation.