AI-Enabled Transnational Fraud: Risk Evolution, Governance Dilemmas, and Regulatory Pathways_Vol. 3 No. 3 (JMSD 2026)_Journal of Management and Social Development (ISSN: 3005-5741)

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AI-Enabled Transnational Fraud: Risk Evolution, Governance Dilemmas, and Regulatory Pathways

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DOI: https://doi.org/10.62517/jmsd.202612302

Author(s)

Jingjing Zheng

Affiliation(s)

School of Finance and Accounting, Fuzhou University of International Studies and Trade, Fuzhou, Fujian, China

Abstract

Generative artificial intelligence has rapidly changed the technical conditions under which cross-border fraud is produced, distributed, and concealed. Unlike traditional fraud, which relies heavily on manual scripts, fake identities, phone calls, and fraudulent websites, generative AI enables criminals to create realistic text, cloned voices, synthetic images, deepfake videos, and personalized deception strategies at low cost and large scale. This article examines the emerging risks of generative AI-enabled cross-border fraud and analyzes why such fraud is difficult to govern under existing regulatory frameworks. The study argues that generative AI increases the credibility, precision, scalability, and concealment of cross-border fraud by combining identity impersonation, data misuse, automated content generation, platform-based dissemination, and complex financial transfer channels. It further proposes a governance framework based on risk classification, platform accountability, financial monitoring, enterprise internal control, personal data protection, public awareness, and international cooperation. The article concludes that the governance of generative AI-enabled cross-border fraud should not rely only on post-event punishment. Instead, it requires a preventive, coordinated, and technologically adaptive regulatory system that balances AI innovation with digital security.

Keywords

Generative AI; Cross-Border Fraud; Deepfake; Data Security; Financial Crime; Digital Governance

References

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