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Detection of fraud statement based on word vector: Evidence from financial companies in China

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  • Zhang, Yi
  • Hu, Ailing
  • Wang, Jiahua
  • Zhang, Yaojie

Abstract

This paper aims to detect plausible frauds of financial companies via text analysis of annual and quarterly reports of China's listed companies. The Management Discussion and Analysis (MD&A) is digitized as vectors. The empirical results indicate that compared with various vector indexes, the bag-of-words (BoW) model and machine learning algorithm have a prediction effect and the ability to recognize frauds where the BoW model can correctly recognize 77% of the fraud reports. This would be helpful for audit authorities to identify fraud reports.

Suggested Citation

  • Zhang, Yi & Hu, Ailing & Wang, Jiahua & Zhang, Yaojie, 2022. "Detection of fraud statement based on word vector: Evidence from financial companies in China," Finance Research Letters, Elsevier, vol. 46(PB).
    • Handle: RePEc:eee:finlet:v:46:y:2022:i:pb:s1544612321004578
    DOI: 10.1016/j.frl.2021.102477
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    References listed on IDEAS

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    Cited by:

    1. Li, Jing & Li, Nan & Xia, Tongshui & Guo, Jinjin, 2023. "Textual analysis and detection of financial fraud: Evidence from Chinese manufacturing firms," Economic Modelling, Elsevier, vol. 126(C).

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