Validity of Fraud Detection Models on Fraudulent US-listed Chinese Companies

Wuyou Shu (), Tianxi He (), Xinghan Li () and Yuhao Gong ()
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Wuyou Shu: New York University, Steinhardt School of Culture, Education, and Human Development
Tianxi He: University of California Irvine, School of Social Sciences
Xinghan Li: Beijing Foreign Studies University, School of Asia
Yuhao Gong: Woosong University, Solbridge International School of Business

A chapter in Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022), 2023, pp 1759-1781 from Springer

Abstract: Abstract This paper examines the effectiveness of Beneish M-Score and Dechow F-Score models in detecting financial frauds of US-listed Chinese companies. In conclusion, based on the data we collected, the validity for M-Score on US-listed Chinese companies is 85.71%, way higher than what Aghghaleh measured for American companies of 73.17%. The calculation and analysis of these models reveals that (1) Beneish M-Score indicates high validity among Chinese companies, while (2) Dechow F-Score fails to identify financial fraud correctly in our selected pool of Chinese companies. This paper evaluates the potential ways of preventing frauds in the light of the samples we collected.

Keywords: Chinese Companies; Fraud Detection Models; Beneish M-Score; Dechow F-Score (search for similar items in EconPapers)
Date: 2023
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DOI: 10.2991/978-94-6463-098-5_199

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