Auditor Reporting and Regulatory Sanctions in the Broker‐Dealer Industry: From Self‐Regulation to PCAOB Oversight
Bibliographic record
Abstract
ABSTRACT The financial security of the investing public relies on high‐quality service by broker‐dealers (BDs), investors' gateway to the financial markets. The SEC has long required auditors to attest to BDs' internal controls and compliance with regulations (including those privately owned). Following the unraveling of the Madoff Ponzi scheme in 2008, the SEC required auditors of all BDs to register with the PCAOB, and Congressional initiatives signaled imminent transition from private (AICPA) to public (PCAOB) oversight. We investigate whether audit quality increased following this transition by measuring whether auditors report material internal control and compliance problems for BD clients where a deficiency presumably existed (i.e., BDs sanctioned by the Financial Industry Regulatory Authority for transgressions against stakeholders). Overall, we do not find increased reporting quality following the regulatory shift but do observe variation by auditor group and BD ownership. While reporting quality for global network firms (GNFs) increases slightly, lower reporting quality observed prior to the regulatory shift for specialist audit firms (having large BD portfolios but small overall size) is exacerbated afterward. This finding complements results of PCAOB inspections and other research identifying audit quality problems among small, industry‐specialized firms in non‐public client settings. Focusing on deficiencies likely more difficult to detect, we find lower reporting quality for private relative to publicly affiliated BDs prior to PCAOB oversight, and lower reporting quality for very small audit firms relative to GNFs following the regulatory shift.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".