Strategies to reduce credit risk and liquidity risk to increase bank profitability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this study is to examine the effect of credit risk and liquidity risk on profitability with loan restructuring and income diversification as moderating variables. The research population is all general banking companies, which were listed on the Indonesia Stock Exchange (IDX) during the period 2018-2021. The research sample was created using the purposive sampling technique and 160 observations were obtained. This study conducts panel data regression analysis using EViews 12 software. The results of this study indicate that an increase in credit risk reduces profitability, liquidity risk does not affect profitability, a loan-restructuring strategy can reduce the effect of credit risk on profitability, and an income-diversification strategy can reduce the effect of liquidity risk on bank profitability. The research findings provide an understanding of banking strategy, namely loan restructuring and income diversification can increase banking profitability under urgent conditions. This study provides support for contingency theory and stakeholder theory. The limitation of this research is that it does not discuss Islamic banking because the policies of those companies are different in terms of rules and there are limited data.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it