Abstract
Artificial intelligence (AI) is reshaping the fraud landscape, serving as a tool for both controlling and organising frauds. This chapter examines AI's dual role, drawing on the distinction between predictive AI, widely used to detect and prevent fraud, and generative AI, which introduces new risks by enabling automated deception on a large scale. Predictive AI has long been integrated into fraud prevention in sectors such as finance, healthcare, and e-commerce, taking advantage of real-time monitoring, anomaly detection and predictive analytics. By contrast, generative AI, capable of creating hyper-realistic text, images, audio, and video, amplifies the risks of fraud by automating deception on an unprecedented scale and accessibility. The chapter discusses the key capabilities of generative AI that make it particularly attractive to fraudsters, as well as the conditions that shape the complexity of fraud, including the type of fraud and access to computational power and expertise. It also analyses existing countermeasures, arguing that traditional human-centred interventions, such as awareness training, are increasingly inadequate against AI-generated fraud. Instead, the study advocates AI-based detection tools, broader regulatory measures and cross-sector collaboration, emphasising the need for a proactive, technology-based approach to address the evolving challenges of AI-enabled fraud.
Original language | English |
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Title of host publication | The Research Handbook on Fraud and Society |
Publisher | Edward Elgar |
Publication status | Published - 1 Sept 2026 |
Keywords
- Fraud
- AI