From Compliance to Strategic Partnerships: The Role of Internal Audit in Enterprise Risk Management and Opportunities for Future Research
Bibliographic record
Abstract
Implementing enterprise risk management (ERM) helps organizations identify, assess, and manage emerging risks. As global ecosystems face intensifying environmental, social and governance (ESG) pressures—including climate risks, regulatory demands for sustainability reporting and stakeholder expectations for ecosystem protection —the internal audit function (IAF) plays an increasingly critical role in helping organizations monitor and respond to these risks. Internal auditors’ expertise supports risk identification and assessment, though management maintains responsibility for risk management and control. Using the Committee of Sponsoring Organizations’ (COSO) ERM framework, we review 77 studies across 23 journals published between 2004 and 2024. Prior research primarily examines internal audit’s assurance and consulting roles, with considerably less attention given to activities that compromise independence. While evidence suggests that internal audit quality enhances risk management effectiveness, uncertainty remains about boundaries for consulting activities and technology-enabled assurance. Our synthesis highlights limited empirical insight into internal audit’s strategic partnership role in ERM and identifies future research opportunities for scholars, practitioners and standard setters.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".