The Moderating Role of Corporate Governance on the Associations of Internal Audit and Its Quality with the Financial Reporting Quality: The Case of Yemeni Banks
Bibliographic record
Abstract
This study investigates the moderating effect of corporate governance on the associations of the internal audit and quality of the internal audit with the quality of financial reporting among commercial banks in the Republic of Yemen. The final sample includes 210 internal auditors, heads of internal auditors, chairpersons, and members of audit committees. Using a survey-based methodology, the results of the Smart-PL4 analysis showed a positive association between the internal audit and quality of the internal audit and quality of financial reporting. Interestingly, the results showed an insignificant association between the internal audit, quality of the internal audit, and quality of financial reporting when considering the moderating effect of corporate governance. It is worth noting that the results confirm the existence of a positive relationship between the internal audit, quality of the internal audit, and quality of financial reporting. This confirms the importance of the internal audit and quality of the internal audit in enhancing the quality of financial reports and instilling confidence in improving internal control processes and the financial reporting framework. Among the study’s many contributions are that it enhances current research on the interrelationship between internal auditing, quality of internal audits, and quality of financial reporting. It highlights the pivotal role of the internal audit, its effectiveness, and its ability to improve the quality of financial reports. This study calls for more stringent internal controls and posits that strengthening the internal audit and quality of the internal audit, along with improving corporate governance, can enable managers to raise financial reporting standards in banks. It also provides a mechanism for audit committees to monitor internal audit processes and evaluate internal performance.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".