REAL-TIME FRAUD DETECTION USING IOT AND AI: SECURING THE DIGITAL WALLET

Abstract

The rapid proliferation of digital wallets, fueled by the integration of Internet of Things (IoT) devices and Artificial Intelligence (AI), has transformed financial transactions, offering unprecedented convenience. However, this evolution has also escalated the risk of sophisticated fraud, threatening the security of digital ecosystems. This paper proposes a novel framework for real-time fraud detection by leveraging IoT-enabled data streams and AI-driven predictive models. By integrating sensor data from connected devices with machine learning algorithms, the system identifies anomalous patterns and prevents fraudulent activities instantaneously. The study evaluates the framework’s efficacy through simulations, demonstrating enhanced accuracy and reduced response time compared to traditional methods. This research underscores the synergy of IoT and AI as a robust solution for securing digital wallets against emerging threats.