Enterprise Risk Management in the US Banking Sector Following the Financial Crisis
Bibliographic record
Abstract
Purpose: The purpose of this paper is to investigate the effect of the financial crisis on the management of risk in the largest US banks. Design/Methodology/Approach: Levels of risk exposure, risk consequences and risk management were examined using a content analysis of the 10-K annual reports form of a sample of 59 largest U.S. banks. Paired-t-test, along with frequency analysis of the disclosures of 15 banking risks was used to test our research hypotheses. Findings: We found that the subprime financial crisis had significantly affected the levels of risk exposure and its consequences after the crisis (risks more probable and certain with major consequences). We also found minor but significant changes in the ERM strategies after the crisis for the three major categories of risk investigated in this study (financial, business, strategic). We found that the changes in ERM strategies were not significant for risks examined individually with the exception of credit risk. Finally, the number of banks disclosing their levels of ERM increased after the crisis especially for systemic risk. Practical implications: Our study is particularly relevant for standards setters and regulatory bodies for it sheds light on the vulnerability of banks to certain types of risks (such as systemic risk) and helps them orient their analysis and find comprehensive and innovative solutions for future reform. Originality/Value: This research enriches the literature on ERM disclosures and presents the first study examining the effect of the crisis on ERM levels in the US banking sector.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".