When Are Audit Firms Sued for Financial Reporting Failures and What Are the Lawsuit Outcomes?
Bibliographic record
Abstract
ABSTRACT We examine how often audit firms are sued in a large sample of accounting lawsuits that allege financial reporting failures. We find an insignificant relation between the likelihood of auditor litigation and restatements, but the likelihood of auditor litigation is strongly related to the types of alleged accounting deficiencies. We also find that the auditor's type influences the probability of the auditor being sued and the size of the payouts from auditor and nonauditor defendants. In particular, the Big N firms are approximately 7 percent less likely than non–Big N firms to be named as co‐defendants, and the auditor's contribution to the plaintiff's payout is significantly larger when a Big N firm is sued. Overall, our findings suggest that auditors are rarely blamed when there are allegations of financial reporting failures, but the types of accounting deficiencies and the auditor's type significantly influence the probability of the audit firm being sued and the outcomes of the lawsuits.
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 | 0.009 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| 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".