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Dr. V. Deepa is an Assistant Professor in the Department of Information Technology at Sri Ramakrishna College of Arts & Science, Coimbatore, India. Her academic interests include Artificial Intelligence, Information Technology, cybersecurity, and intelligent computing applications.
The swift embrace of cloud computing, Internet of Things (IoT), and e-commerce innovations has transformed financial services and digital transactions. Nonetheless, the growing interconnectivity of digital ecosystems has simultaneously generated various opportunities for cybercriminals to exploit weaknesses and perpetrate financial fraud. Conventional rule-based fraud detection systems frequently fail to recognise intricate and developing fraud schemes instantaneously. Artificial Intelligence (AI) has surfaced as a formidable remedy for tackling these issues via astute data analysis, anomaly identification, predictive modelling, and automated decision-making. AI-powered fraud detection solutions utilise Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and behavioural analytics to successfully recognise dubious actions and thwart financial crimes. This section presents the essential principles, structure, uses, obstacles, and prospective developments of AI-based fraud detection systems within cloud-supported IoT and e-commerce settings. The chapter offers an extensive examination of the role of AI technology in developing secure, scalable, and robust financial systems.