Performance Analysis of GCC Banks: A Survey
Bibliographic record
Abstract
The banking sector plays an essential economic role in providing financial intermediation and economic acceleration by converting deposits into productive investments. A strong banking sector can deal with any crisis and contribute abundantly to the stabilization of the economy. GCC is home to one of the fastest increasing banking sectors in the world. The objective of this study is to identify the country that has the best-performing banking sector in the GCC and to rank the best-performing banks in the GCC based on different parameters like the total asset, net profit, return on asset (ROA), return on equity (ROE), capital adequacy ratio and cost-to-income ratio. The study includes all the 55 listed banks from the GCC countries. The study revealed that Emirates NBD from the UAE is at the top rank under Net Profit and ROE, the second rank in ROA, and the third rank in Total Assets. Qatar National Bank from Qatar has been ranked the best under the category Total Assets, rank two under net profit, rank four in ROE, and cost-to-income ratio. The National Commercial Bank from Saudi Arabia was ranked third in ROE and ROA and rank four under Total Asset and Net Profit.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".