Financial Statement Management, Liability Reduction and Asset Accumulation: An Application of Goal Programming Model to a Nigerian Bank
Why this work is in the frame
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Bibliographic record
Abstract
This paper examines the management of the financial statement of UBA using goal programming (GP) technique. The data are collected from the annual financial statement of the bank to cover a period of 2007 to 2011. Six goals are identified in the bank: goal (1) (asset accumulation); goal 2 (liability reduction); goal 3 (shareholders’ wealth); goal 4 (earning); goal 5 (profitability); and goal 6 (optimum management of the items in the financial statement). Applying POM-QM Version 3 software, the solution generated reveals that besides goal 2, all other goals are attainable by the bank. It is not therefore possible for the bank to reduce its liabilities, for the sake of reducing or increasing the other items of its financial statement. Based on this, it is concluded that the bank should convert its liabilities to earning assets quickly or as much as possible.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it