Analysis of Financial Intermediation and Profitability: “A Case Study of the Ghanaian Banking Industry”
Bibliographic record
Abstract
The study examines the extent to which banks in Ghana have performed their financial intermediation function and its implication for profitability. Secondary data which was solicited from the Headquarters of the eight largest banks in Ghana was obtained from their financial reports from 2004 to 2010. Using descriptive examination technique, it is observed that all the banks performed creditably well within the period under study though the private banks performed better than the state-owned banks. Additionally, on the average, banks that mobilized the most deposits were also the ones that recorded most loans and advances. Interestingly, the study finds however that banks that made the most loans and advances were not necessarily those that made most profits. It is recommended that to remain profitable in the banking business in Ghana, management must not only put strategies in place to mobilize deposits and make out loans and advances but also institute procedures to efficiently manage cost. Furthermore, government must also put policies in place to motivate banks mobilize more deposits and make out more loans to deepen the financial system.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".