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AI-Powered Fraud Detection in Auditing: Evidence from China and Implications for Audit Education

  • Poshan Yu,
  • Yunchen Zhang,
  • Kiran Mehta,
  • Renuka Sharma,
  • Yansong Wang,
  • Lanbei Yin,
  • Zuozhang Chen

摘要

The ever-evolving artificial intelligence technology is continuously transforming the operational framework of the auditing industry. It not only enhances the efficiency of auditing but also contributes to fraud detection, significantly improving the accuracy of auditing. Against this backdrop, the auditing education system must actively adapt to the trend of technological change and focus on cultivating compound talents with ai skills and interdisciplinary thinking to meet the growing professional needs of the auditing industry. This article, by means of the visualization analysis of citespace and the study of typical cases, explores the diverse applications of ai in auditing, especially in fraud detection. In combination with the innovative practical experience of auditing education in China, it proposes a development path that integrates “technology + business + education” in one, aiming to provide theoretical support and practical guidance for the transformation and upgrading of the auditing industry in the field of fraud detection.