Toward an Appropriate Model for Corporate Governance in Banking Industry- Case Study of Iran
Bibliographic record
Abstract
Given the vital role of banks and other financial institutions in financial and economic stability, and also their great vulnerability to the potential imperfections of corporate governance and the need to maintain the depositors' funds and the stakeholders’ interests, the issue of corporate governance and eliminating its weaknesses and failures are extremely important in banking industry. In recent financial scandals and economic crises which banks and other financial institutions have had a leading role because of malfunctioning of their corporate governance mechanisms. Furthermore, in 2011, the occurrence of a massive financial embezzlement and existence of enormous deferred bank accounts in Iran banking system implies that there is a serious failure in banks' corporate governance for the experts in this field.Therefore this study attempts to prepare information about the current state of corporate governance in Iran banks and compares it with that of prosperous big banks in other parts of the world. Additionally, it is going to investigate the weak points of corporate governance in Iran banks in order to present an appropriate model for them. It also should be noted that we review all available related documents in Iran banks and interview the managers and experts to obtain valid feedbacks in this regard. Then, we review successful and unsuccessful experiences of famous international banks such as Bank of America, Toronto-Dominion Bank, J. P. Morgan, and HSBC, and their corporate governance structures to extract and model them. By comparing this model with those belonging to Iran banks we can realize almost any weakness existing in Iran banks. Finally we suggest an appropriate model for Iran banks to improve the efficiency and effectiveness of the mechanism of their corporate governance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".