The Use and Characteristics of Foreign Component Auditors in U.S. Multinational Audits: Insights from Form <scp>AP</scp> Disclosures*
Bibliographic record
Abstract
ABSTRACT This paper investigates the common, yet previously opaque, practice of using foreign audit firms (component auditors) to conduct portions of audit work for U.S. public companies. U.S. regulators have expressed concern for the transparency and quality of audits using component auditors. Employing data disclosed in the newly mandated PCAOB Form AP, we find that component auditor use is largely structural, determined by the size and complexity of clients' multinational operations. We do not find that the mere use of component auditors is detrimental to audit outcomes, but rather the amount of work conducted by component auditors is associated with lower audit quality (i.e., higher likelihood of misstatement), higher likelihood of nontimely reporting, and higher audit fees, which collectively suggest that component auditor engagements are associated with adverse outcomes. Furthermore, we find that only the work performed by less competent component auditors and those facing geographic and cultural/language barriers, including significant geographic and cultural distance, weak rule of law, and low English language proficiency, is associated with adverse audit outcomes. Overall, these findings provide initial archival evidence that the use of certain component auditors on U.S. multinational audits is associated with audit coordination issues, which suggests that PCAOB Form AP disclosures provide relevant information.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".