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Financial fraud detection for Chinese listed firms: Does managers' abnormal tone matter?

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  • Li, Jingyu
  • Guo, Ce
  • Lv, Sijia
  • Xie, Qiwei
  • Zheng, Xiaolong

Abstract

This study introduces a novel perspective on financial fraud detection by exploring the utility of managers' abnormal tone. To mitigate bias in indicator selection, we implement a feature selection process involving a comprehensive set of 301 indicators, including financial, non-financial, and textual, and various machine learning algorithms. The dataset contains 6077 pairs of fraudulent and non-fraudulent samples in China. Our findings underscore the significance of abnormal tone in fraud detection, establishing it as a prominent factor in the feature selection process. The accuracy outcomes from eight machine learning models further confirm that incorporating abnormal tone can enhance fraud detection performance.

Suggested Citation

  • Li, Jingyu & Guo, Ce & Lv, Sijia & Xie, Qiwei & Zheng, Xiaolong, 2024. "Financial fraud detection for Chinese listed firms: Does managers' abnormal tone matter?," Emerging Markets Review, Elsevier, vol. 62(C).
    • Handle: RePEc:eee:ememar:v:62:y:2024:i:c:s1566014124000657
    DOI: 10.1016/j.ememar.2024.101170
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