Are External Auditors Concerned about Cyber Incidents? Evidence from Audit Fees
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
SUMMARY While the importance of addressing cybersecurity is widely acknowledged, there is no explicit requirement by regulators or standard setters for auditors to do so. This paper investigates (1) whether external auditors respond to cyber incidents by charging higher audit fees, (2) whether they anticipate and price material cybersecurity risk before cyber incidents occur, and (3) whether increases in audit fees for firms experiencing a cyber incident in the current period are associated with subsequent cyber incidents. We find that only cyber incidents are associated with increases in audit fees and that the association is driven by more severe incidents. We also find that increases in audit fees are smaller for firms with prior cybersecurity risk disclosure after 2011 when the SEC issued cybersecurity disclosure guidance. Finally, larger increases in audit fees for firms experiencing cyber incidents in the current period are associated with a lower likelihood of subsequent cyber incidents.
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.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.009 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it