Deciphering the PCAOB Inspection Process: Evidence and Predictive Insights from Public Data

Little is known about how the Public Company Accounting Oversight Board (PCAOB) selects audits for inspections. We exploit public data that track PCAOB searches of issuer Securities and Exchange Commission (SEC) filings and the trial transcripts of United States of America v. David Middendorf to provide the first large-sample evidence on confidential PCAOB monitoring activities. We initially validate that PCAOB searches spike during actual inspections of triennially inspected auditors and for a list of KPMG audits inspected in 2016. Importantly, we find that PCAOB searches vary predictably with ongoing audit-flagged events, client corporate events, and client characteristics, and these screening and inspection activities extend beyond enforcement actions. Using KPMG data, we introduce a PCAOB inspection prediction model for Big 4 clients based solely on public data, with predicted incidence closely aligning with actual inspections. One implication of our study is that, perhaps to mitigate political costs, the PCAOB relies overly on conspicuous trigger events that already signal low audit quality (i.e., restatements, auditor changes, chief financial officer turnovers, bankruptcies, and SEC comment letters), raising the question of how its risk-based inspection program is designed to improve overall audit quality or minimize large audit failures. In addition, although model-inferred PCAOB inspections are not associated with future restatements, broader PCAOB monitoring activities, as proxied by search intensity, exhibit modest predictive power. Overall, our study provides a more nuanced understanding of the PCAOB inspection program and the factors driving its revealed preferences. This paper was accepted by Ranjani Krishnan, accounting. Funding: This work was supported by the Jones Graduate School of Business at Rice University, Baruch College, and the Penn State Smeal College of Business. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.08084 .