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Application of Artificial Intelligence in Anti-Money Laundering of Internet Finance--Taking the Construction of Intelligent Monitoring System as an Example

Yu Lu 1, *
1 Jiangsu University (JSU), Zhenjiang, Jiangsu, China * Correspondence: Yu Lu, Jiangsu University (JSU), Zhenjiang, Jiangsu, China

Vol. 22 (2026): 2026 3rd International Conference on the Frontiers of Social Sciences, Education, and the Development of Humanities Arts (EDHA 2026)

Received: 2026-06-13

Accepted: 2026-06-13

Published: 2026-06-13

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Downloads: 188

Abstract

With the rapid development of internet finance services, money laundering risks have exhibited new characteristics including strong concealment, diversified methods, and cross-regional activities. Traditional anti-money laundering monitoring methods have gradually revealed issues such as low efficiency and insufficient identification accuracy in addressing these challenges. This paper focuses on the construction of intelligent monitoring systems. First, it analyzes the main challenges currently faced in internet finance anti-money laundering, including difficulties in customer identity verification, transaction monitoring, and regulatory compliance. Then, it elaborates on the application advantages of artificial intelligence in the field of anti-money laundering, such as efficient data processing, precise pattern recognition, and real-time dynamic monitoring. Based on this, the paper emphasizes the architectural design of AI-based intelligent monitoring systems, key technology applications (including machine learning algorithms and deep learning techniques), as well as data sources and management strategies. Through case studies, the practical effectiveness of the system is validated. Finally, it proposes corresponding countermeasures and suggestions for challenges in AI application to anti-money laundering, such as data security and privacy protection, algorithmic explainability, technological updates, and talent shortages. The aim is to provide theoretical references and practical guidance for enhancing the intelligent level of anti-money laundering efforts in internet finance.

Keywords

artificial intelligence machine learning deep learning internet finance anti-money laundering intelligent monitoring system

References

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Copyright and License

Published in2026-06-13 17:26:59

DOI doi.org/10.70088/bvht4365

Creative Commons
Copyright: © 2026 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/license s/by/4.0/).

Copyright
Copyright © The Author(s), 2026. Published by EDHA 2026

Journal Information

  • Vol. 22 (2026): 2026 3rd International Conference on the Frontiers of Social Sciences, Education, and the Development of Humanities Arts (EDHA 2026)
  • 2026-06-13
  • ISSN: (Print) 3078-770X/ (Online) 3078-7718
  • Journal Homepage

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