Issues of Letter of Credit in Malaysian Islamic Banks
Bibliographic record
Abstract
This paper discussed the prevailing issues currently faced by Islamic banks on the offering of Letter of Credit (LC), originally brought forward by the International Chamber of Commerce, using Shariah contracts and puts forth recommendations on practical solutions to solve the issues. The study adopted a qualitative method where the information on the issues of Islamic LCs was gathered throughout interviews with different bankers closely involved in LC issuance from 12 Islamic banks in Malaysia. The results indicate that there are three vital issues related to LCs offered by Islamic banks which lead to Shariah non-compliance issues. The issues revolve around the conversion of LC Wakalah (agency) to LC Murabahah (cost-plus), the existence of a sale contract between the customer and exporter and lastly the title of goods stated in the bill of lading. The findings recommend several solutions in relation to LCs within the underlying Shariah contracts to ensure that their operation complies with the Shariah requirements and Malaysian laws, standards and regulations. This paper highlights the issues of Islamic LC yet to be discussed thoroughly based on the views of a panel of experts and Islamic bankers.
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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 | 0.012 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".