Roadmap and Information System to Implement Information Technology Risk Management
Bibliographic record
Abstract
In the pursuit of strategic and economic goals, risk management has become indispensable for organizations.Information technologies hold a central position in organizational operations, necessitating adaptable information systems that can effectively navigate associated risks.While numerous standards and frameworks are dedicated to Enterprise Risk Management (ERM), Information Technology Risk Management (ITRM) is addressed less frequently.Within this domain, COBIT 5 emerges as a notable guide, offering audit and governance principles tailored to ITRM.Nevertheless, COBIT 5, alongside other benchmarks, is observed to lack comprehensive, structured guidelines that support an integrated approach.This paper introduces a proposed roadmap and its supporting information system, drawing upon the foundations laid by ISO 31000, COSO ERM, and COBIT 5.The roadmap is designed to address the dearth of detailed frameworks in ITRM, presenting a holistic strategy that elucidates and simplifies the sequential steps and expected deliverables.The principal aim is to provide a structured methodology for the implementation of ITRM in organizations.Looking to the future, the potential application of Artificial Intelligence (AI) to further automate and refine this approach represents an intriguing avenue for research and development.The roadmap thus sets the stage for a transformative leap in ITRM, promising enhanced efficacy and strategic alignment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| 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".