AI and Machine Learning in Fraud Detection for Finance and E-Commerce

Abstract

The fraud activities involving the finance and e-commerce industries have become very sophisticated, thus demanding new technologies to solve them. This paper aims to find how Artificial Intelligence (AI) and Machine Learning (ML) enable the prevention and detection of fraud, utilizing the provision of processing large numbers of inputs, recognizing irregularities, and assessing risks in real-time. The four areas include: It describes how generative AI can be used to uncover complex fraudulent schemes, how IoT-enabling chatbots can be integrated to improve the customer experience while detecting fraudulent activities, and the importance of 5G edge computing to facilitate immediate processing. The research also pays attention to the necessity of integrating these technologies into the frameworks of the 'zero-trust' protection concept and enhancing cybersecurity with the help of both. Showing a practical application of AI and ML in financial and e-commerce environments, this study provides evidence of the emerging trends in combating fraud, enhancing business processes, and enhancing consumers' confidence in the digital economy.