Risk Management and the Financial Performance of Banks in Nigeria
Bibliographic record
Abstract
The study examined “risk management and financial performance of banks in Nigeria” with focus on commercial banks. The broad objective of the study was to ascertain the effect of risk asset management on the optimal financial performance of commercial banks in Nigeria. The study is a longitudinal survey, so the ex-post facto research design was applied. Research data were analysed using generalized method of moments (GMM) and vector Error Correction Model, after testing and adjusting the data for stationarity and Cointegration.The research findings were: Banks’ profitability is significantly influenced in the short run by liquidity risk and in the long-run by credit risk, capital adequacy risk, leverage risk and liquidity risk. Furthermore, profitability measured by ROaA was found to be positively related to liquidity risk but negatively related credit risk. Arising from the findings, there is the need for effective risk management, especially credit, capital adequacy, leverage and liquidity risks, to enhance the profitability of banks. By helping to enhance the going concern of banks, risk management will help to reduce retrenchment and unemployment and hence help to forestall the attendant social vices.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".