Independent Board, Audit Committee, Risk Committee, the Meeting Attendance level and Its Impact on the Performance: A Study of Listed Banks in Indonesia
Bibliographic record
Abstract
This study determines the effect of good corporate governance on the performance of banks in Indonesia. The variables used are independent board (IB), the annual board meeting (BM), the percentage of annual board of director meeting attendance, the annual board-executive meeting (BEM), the percentage of annual board-executive meeting attendance, audit committee (AC), audit committee meeting (ACM), the percentage of annual audit committee meeting attendance, risk committee (RC), risk committee meeting (RCM), and the percentage of annual risk committee meeting attendance. The analysis technique employed in this study is two-stage least square (2SLS) panel data regression using return on asset (ROA), net interest margin ratio (NIM), and Tobin’s Q as the proxies of bank performance. The data used are listed bank in Indonesia Capital Market between 2013 and 2015. The findings reveal that the independent board has a positive impact on net interest margin among the big scale bank. However, among the small scale bank the independent board of directors has the positive impact on the market value, but they will have the lack of information that could obstruct the accounting based profit of the bank. Moreover, the findings of this study also explain the important role of meeting attendance for the accounting based profitability of the bank. This study also found the critical role of the audit committee in the banking industry.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".