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With the increasing number of accounting fraud cases today, this paper aims to explore the accounting fraud detection technology using the BP neural network method. Fraudulent activities significantly impact the accounting field, necessitating effective identification methods. The paper initially introduces the basic concepts of the BP neural network algorithm and tests its performance. Building upon a comprehensive review of domestic and international research, this study proposes a recognition model based on the BP neural network. The performance, effectiveness, and accuracy of this model in accounting fraud detection are verified through experiments. The results indicate that the proposed model significantly identifies accounting fraud, offering a new solution for addressing fraud issues in the accounting field.

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Accounting Fraud Detection Research Based on BP Neural Network Method

  • 会议论文

  • 发表日期：

    2025年

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  • Lin Liu,
  • Xin Meng,
  • Yucui Bai,
  • Ran Chen

摘要

With the increasing number of accounting fraud cases today, this paper aims to explore the accounting fraud detection technology using the BP neural network method. Fraudulent activities significantly impact the accounting field, necessitating effective identification methods. The paper initially introduces the basic concepts of the BP neural network algorithm and tests its performance. Building upon a comprehensive review of domestic and international research, this study proposes a recognition model based on the BP neural network. The performance, effectiveness, and accuracy of this model in accounting fraud detection are verified through experiments. The results indicate that the proposed model significantly identifies accounting fraud, offering a new solution for addressing fraud issues in the accounting field.