What if auditors could predict when errors are more likely to occur in financial reporting? Instead of simply improving techniques for detecting errors, they could focus on how to stop them from happening.
This is the focus of work by Chanyuan (Abigail) Zhang Parker, assistant professor of accounting in the UT San Antonio Carlos Alvarez College of Business. Parker’s paper, “Predicting Material Misstatements Using Machine Learning,” was recently accepted in The Accounting Review on this topic.
