Can independent directors identify the company’s risk of financial fraud: Evidence from predicting financial fraud based on machine learning

Yunjing Liu, Bin Wu and Min Zhang

China Journal of Accounting Studies, 2023, vol. 11, issue 3, 465-492

Abstract: Combining the company’s risk of financial fraud predicted by the machine learning method and unique Chinese data of board voting, this study investigates whether independent directors can identify the company’s risk of financial fraud. We find that independent directors are more likely to express dissenting opinions on board’s financial-related proposals when the company has a higher risk of financial fraud; this impact is more pronounced when independent directors have more financial backgrounds or higher reputations. Further study shows that companies with independent directors’ dissension have a lower risk of financial fraud in the future after controlling the risk of financial fraud in the current year. Our findings indicate that independent directors can identify the company’s risk of financial fraud and play as a supervisor, thereby reducing the probability of the company’s future financial fraud. Our findings provide direct empirical evidence for the effectiveness of the independent director system and enhance our understanding of independent directors’ actual voting behaviour.

Date: 2023
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DOI: 10.1080/21697213.2023.2239670

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