The Role of the Auditor in Planning and Reduce the Risk of IT Environment in Commercial Jordanian Banks
Bibliographic record
Abstract
This study aimed to identify the role of the auditor’s judgment in dealing with the risks of the IT environment, so I studied the process of IT risk planning , and study how the auditor to reduce the risk of information technology. The study on designing a questionnaire covering the variables and hypotheses of the study , the questionnaire consists of 14 paragraphs, were used methods of statistics such as averages and standard deviations, and percentages and frequencies , and the study sample consisted of auditors (52) (external Auditors )for commercial banks in Jordan , most results are: Auditor determine the output of the likelihood of recurrence of the threat event (incidence of threat), and is expressed in a year ,Auditor Identify risks that cause weakness and imbalance core activities of the company, and monetary loss resulting from it , and Auditor prepare Prioritize risks according to their importance. Study recommendations are: its important to care that the members of the team in charge of identifying risks with a statement of clarification and details in favor of it, based on the knowledge that they own about those risks. And Auditor evaluate on an ongoing basis and on a periodic basis, and this determines the important information should be focused information security on them.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".