Operational auditing versus traditional method: A comparative investigation
Bibliographic record
Abstract
Operational auditing is one of the management consultancy services whose significance is on the rise day by day. This approach is, clearly, a systematic and methodical process used to evaluate economic savings of financial processes in organizations and the results of the evaluations are reported to interested people along with some comments to improve operational processes. Accordingly, it appears that the proper employment of the existing rationale in operational auditing can be a significant step towards the improvement of financial efficiency in Iranian public and private banking sector. This paper studies the effects of operational auditing on the improvement of economic saving of financial processes in Iranian private banks compared with traditional approaches where the operations are based on financial statements. The population of this survey includes 15 private and public Iranian banks and the proposed study selects 78 branches, randomly. The Cronbach alpha was used to test the reliability a questionnaire employed to collect the needed data in this study. The results obtained by SPSS Software indicated that the reliability of the instrumentsanged between 0.752 and 0.867, suggesting an acceptable level of the reliability for the questionnaire. Besides, content validity was used to confirm the validity of the instrument. The results of the study indicated that the operational auditing as a useful approach influencing the financial efficiency of public and private banks has significantly transformed the traditional thinking in the field of management auditing. The operational auditing has a number of significant advantages including a better method of controlling financial operations within Iranian banks, efficient planning in the future, facilitating efficient, appropriate, and accurate management decision making, and sound evaluation of managers’ financial operations.
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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 | 0.015 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".