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Build a Trade Finance Letter of Credit Inconsistency Inspector — implementation
Linked challenge: Build a Trade Finance Letter of Credit Inconsistency Inspector
Prompt source
implementation64 lines11 sectionsNo variables1 code block
## Build
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.
## User
Trade finance operations auditor
## Workflow
1. Ingest simplified normalized trade finance packets containing LC rules, commercial invoices, and shipping bills.
2. Extract counterparties, cargo descriptions, declared weights, and loading/unloading port codes.
3. Reconcile shipping party names against GLEIF legal entity names to verify counterparty authority.
4. Flag cross-document discrepancies such as destination port drift or altered cargo descriptions in an audit log.
## Interface
Side-by-side document comparison split-screen highlighting discrepancies between LC stipulations and shipping manifests.
## Data
Construct 35 synthetic trade finance dossier JSON objects featuring consistent transactions and intentional discrepancies.
Starter examples below are synthetic. They are not downloaded records.
## Source
[GLEIF API](https://www.gleif.org/en/lei-data/gleif-api)
Verifies legal names and jurisdiction registration of trade counterparties against simulated GLEIF reference records.
## Tools
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.
## Deliverables
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.
## Acceptance
- 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.
## Starter Examples
```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"
}
}
]
```
## Safety
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.