Events

Dr. Sean S. Cao
Associate Professor of FinTech, AI and Capital Markets
Robert H. Smith School of Business
University of Maryland

In the age of Artificial Intelligence, the analysis of corporate financial statements is predominantly conducted by machines. This study investigates the impact of this rising machine readership on the quality of firms’ financial reporting. Our results shows that overall, machine readership has a disciplinary effect, prompting firms to improve their financial reporting quality. Specifically, we observe a reduction in financial misreporting patterns that can be detected by machines in response to the increased use of machine readership. Interestingly, our analysis reveals no significant association between machine readership and misreporting patterns detectable through traditional methods. This disciplinary effect is stronger in situations where machine readership holds clear advantages (in the presence of complex financial statements and alternative datasets). Additionally, the effect is strengthened when firms face heightened costs associated with earnings management.