Build a Trade Finance Letter of Credit Inconsistency Inspector
Inspect trade finance documents including bills of lading, commercial invoices, and letters of credit for counterparty discrepancies. Collate address mismatches and missing ports into an investigation dossier.
What you are building
The core problem, expected build, and operating context for this challenge.
Inspect trade finance documents including bills of lading, commercial invoices, and letters of credit for counterparty discrepancies. Collate address mismatches and missing ports into an investigation dossier.
Trade finance operations auditor
Ingest simplified normalized trade finance packets containing LC rules, commercial invoices, and shipping bills.
Extract counterparties, cargo descriptions, declared weights, and loading/unloading port codes.
Reconcile shipping party names against GLEIF legal entity names to verify counterparty authority.
Flag cross-document discrepancies such as destination port drift or altered cargo descriptions in an audit log.
Side-by-side document comparison split-screen highlighting discrepancies between LC stipulations and shipping manifests.
Construct 35 synthetic trade finance dossier JSON objects featuring consistent transactions and intentional discrepancies. Starter examples below are synthetic. They are not downloaded records.
GLEIF API Verifies legal names and jurisdiction registration of trade counterparties against simulated GLEIF reference records.
pydantic-ai, pydantic, fastapi. Pydantic AI structures multi-document validation logic and generates structured discrepancy reports. Local or hosted LLM API capable of document reasoning with structured output validation.
Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.
Detects discrepancies between letter of credit stated destination and invoice destination.
Verifies freight forwarder entity status against simulated GLEIF legal entity records.
Compiles an exportable JSON trade reconciliation summary for trade compliance analysts.
```json [ { "input": { "lc_id": "LC-100", "lc_applicant": "Oceanic Traders", "invoice_buyer": "Oceanic Traders", "port_of_loading": "SGSIN", "port_of_discharge": "NLRTM" }, "expected_output": { "discrepancies": [], "status": "COMPLIANT" } }, { "input": { "lc_id": "LC-101", "lc_applicant": "Oceanic Traders", "invoice_buyer": "Oceanic Logistics Sub", "port_of_loading": "SGSIN", "port_of_discharge": "USNYC" }, "expected_output": { "discrepancies": [ "Port of discharge mismatch: NLRTM expected vs USNYC provided", "Counterparty name discrepancy between LC applicant and invoice buyer" ], "status": "DISCREPANT" } } ] ```
Demonstration tool for document reconciliation; does not delay port shipments or halt financial letters of credit. Use mock external writes. Require human review before any real deployment.
Participation guide
Demonstration tool for document reconciliation; does not delay port shipments or halt financial letters of credit. Use mock external writes and human review.
How work is evaluated
Detects discrepancies between letter of credit stated destination and invoice destination. Verifies freight forwarder entity status against simulated GLEIF legal entity records. Compiles an exportable JSON trade reconciliation summary for trade compliance analysts.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Complete workflow
Ingest simplified normalized trade finance packets containing LC rules, commercial invoices, and shipping bills. Extract counterparties, cargo descriptions, declared weights, and loading/unloading port codes. Reconcile shipping party names against GLEIF legal entity names to verify counterparty authority. Flag cross-document discrepancies such as destination port drift or altered cargo descriptions in an audit log.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Detects discrepancies between letter of credit stated destination and invoice destination. Verifies freight forwarder entity status against simulated GLEIF legal entity records. Compiles an exportable JSON trade reconciliation summary for trade compliance analysts.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Side-by-side document comparison split-screen highlighting discrepancies between LC stipulations and shipping manifests.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Demonstration tool for document reconciliation; does not delay port shipments or halt financial letters of credit.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Ingest simplified normalized trade finance packets containing LC rules, commercial invoices, and shipping bills.
Extract counterparties, cargo descriptions, declared weights, and loading/unloading port codes.
Reconcile shipping party names against GLEIF legal entity names to verify counterparty authority.
Flag cross-document discrepancies such as destination port drift or altered cargo descriptions in an audit log.
Reference links and supporting material
Construct 35 synthetic trade finance dossier JSON objects featuring consistent transactions and intentional discrepancies. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
Pydantic AI
Typed Python agent framework.
Evaluated output
No output checks are configured.
- Ingest simplified normalized trade finance packets containing LC rules, commercial invoices, and shipping b...
- Detects discrepancies between letter of credit stated destination and invoice destination. Verifies freight...
- Side-by-side document comparison split-screen highlighting discrepancies between LC stipulations and shippi...
- 2 public reference cases
- 2 configured tools
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- Pydantic AI · Optional
- Pydantic AI · Optional
Evaluation contract
- Complete workflow · Weight 40
- Correctness and evidence · Weight 30
- Review interface · Weight 20
- Safe execution · Weight 10
Reference cases
- 2 public reference cases
Workflow tasks
No workflow tasks are configured.
Recipe freeze marker
No recipe freeze time is recorded.