Standby Letters of Credit in International Trade
Bibliographic record
Abstract
The question of what constitutes ‘fraud in the transaction’ with respect to international letters of credit varies considerably among jurisdictions. In proving allegations of fraud, it is crucial for the practitioner to know the relevant jurisdiction’s case law, especially if wider defences such as inducement, unconscionable conduct or bad faith must be invoked. In this book, the author argues that, whereas ‘fraud in the documents’ is generally sufficient in cases involving commercial letters of credit, standby letters of credit demand a wider fraud exception. The central issue – how wide that fraud exception should be – is what this book explores in depth.This author compares and critically examines the application of the fraud exception in four major trade jurisdictions – the United States, England, Canada, and Australia. With an overall focus on how each jurisdiction’s fraud tests treat the autonomy of standby letters of credit, she builds her arguments on such relevant sources and concepts as the following: •when it can be shown that the beneficiary has ‘no bona fide belief’ in the validity of its claim •demand guarantees; •international initiatives (ICC Rules and the UN Convention on Independent Guarantee and Standby Letters of Credit); •the Sztejn Rule; •parameters of the ‘fraud in the transaction’ defence •‘materiality’ standard; •prerequisites for injunctive relief; •arguing ‘fraud in the formation of the contract’; •performance bond cases; •applying the ‘breach of good faith’ defence; •‘negative stipulation’ in the underlying contract; and •equitable versus statutory/broader notion of unconscionability. The presentation includes detailed summaries and analyses of leading cases in all four jurisdictions. Lawyers and corporate counsel responsible for arguing claims or defences in letter of credit transactions will welcome the way the author's research and insight define the range of options in each case they handle. Academics also will appreciate the systematic way the book frames a complex area of international trade law.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.019 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".