A Tale of Two Supervisors: Compliance with Risk Disclosure Regulation in the Banking Sector*
Bibliographic record
Abstract
ABSTRACT We examine how the presence of multiple supervisory agencies affects firm‐level compliance in form and substance with disclosure regulations. This analysis is important because coordination problems among regulators are frequently present in practice but often overlooked in academic research. We exploit that banks are subject to equivalent risk disclosure rules under securities laws (IFRS 7) and banking regulation (Pillar 3 of the Basel II Accord) but that different regulators start enforcing the rules at different points in time. We find that banks substantially increase their formal risk disclosures upon the adoption of Pillar 3 even if they already had to comply with the same requirements under IFRS 7. The effects are stronger if the central bank is responsible for bank supervision and bank regulators are equipped with more supervisory resources, but are less pronounced if the securities market regulator is an independent entity. In turn, banks facing more market pressures are more compliant with the rules. We further find persistent liquidity benefits of the increased risk disclosures but only after Pillar 3 became effective and its compliance was enforced by the banking regulator. Our results suggest that formal and material compliance with risk disclosure regulation are a function of both the resources of the supervisory agency and its incentive alignment with the regulated firms. In our setting, the banking regulator seems more effective in fulfilling this role.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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".