Impact of Credit Risk, Liquidity Risk, and Operational Risk on Commercial Bank's Profitability
Bibliographic record
Abstract
The major objective of the study is to examine the impact of bank specific risk factors such as credit risk, liquidity risk, and operational risk on commercial bank's profitability operated in Nepali money market. The study consists of descriptive and causal comparative research design. All the data are collected from the annual reports of nine sample banks for 15 years from mid-July 2009 to mid-July 2023 with 135 observations. The explained variables are return on assets and the return on equity whereas the explanatory variables are capital adequacy ratio, non-performance loan, leverage, cost to income ratio, loan loss provision, and loan to deposit ratio. The research methods used for the study consists of descriptive statistics, correlation analysis, and regression analysis. The results confirmed that capital adequacy ratio, non-performing loan, cost to income ratio, and loan loss provision have the significant negative impact on commercial bank's profitability. In contrast, leverage ratio has the significant positive impact on return on equity only. Loan to deposit ratio do not has any significant impact on profitability. More clearly, credit risk and operational risk both have the significant negative impact whereas liquidity risk has the significant positive impact on commercial banks operated in Nepali money market. The policy makers involving in the money market and the executives taking decisions can be beneficiated from the findings if they consider these findings for their day-to-day practices.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".