Artificial intelligence and corporate fraud: Evidence from China

Yun Xia, Linling Xie, Xiao Chen and Ziang Lin

Economic Analysis and Policy, 2025, vol. 86, issue C, 1391-1408

Abstract: Using panel data of Chinese A-share listed companies from 2010 to 2022, we find that AI technology significantly curbs corporate fraud. The results remain robust after conducting a series of robustness tests, including instrumental variables (IV) and 2SLS, dynamic effects tests, propensity score matching model (PSM), and difference-to-differences model (DID). Additionally, we find that AI technology reduces corporate fraud by improving firms’ internal control quality and reducing information asymmetry. This effect is more significant in high-tech and non-state-owned enterprises (non-SOEs). Additional analysis reveals that AI technology reduces firms’ incentives to commit fraud and increases the likelihood of being detected after committing fraud. Overall, our study extends the research on AI technology to non-financial domains and provides important insights for policymakers in the digital era.

Keywords: Artificial intelligence; Corporate fraud; Internal control; Information asymmetry (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecanpo:v:86:y:2025:i:c:p:1391-1408

DOI: 10.1016/j.eap.2025.04.030

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