Build a Cross-Border Wire Counterparty LEI Drift and Remediation Tracker
Detect entity drift and mismatched registration jurisdictions between raw SWIFT MT103 counterparty strings and official LEI reference records. Synthesize structured data-cleansing queues and repair orders for banking back-office operators.
What you are building
The core problem, expected build, and operating context for this challenge.
Detect entity drift and mismatched registration jurisdictions between raw SWIFT MT103 counterparty strings and official LEI reference records. Synthesize structured data-cleansing queues and repair orders for banking back-office operators.
Payment Data Quality Engineer
Ingest batch normalized international payment transactions containing noisy legal names and country codes.
Query mock GLEIF API search endpoints utilizing full-text search and registration jurisdiction filters.
Compare counterparty postal codes, legal forms, and registered statuses against current LEI Golden Copy records.
Export an operational remediation file containing verified LEI codes and corrected SWIFT field 59 formatted lines.
A side-by-side reconciliation table with one-click approval for suggested SWIFT field replacements.
Fictional payment text files paired with simulated GLEIF API responses returning legal address components. Starter examples below are synthetic. They are not downloaded records.
GLEIF API Leverages GLEIF Golden Copy search schemas, legal name normalizations, and corporate jurisdiction code lists.
haystack, pydantic, requests. Haystack provides document search pipelines to evaluate fuzzy entity string similarity across large reference datasets. Embedder model for text similarity indexing coupled with an API-driven LLM for semantic discrepancy extraction.
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.
Normalizes noisy corporate suffixes to standard legal forms using GLEIF reference code lists.
Generates properly formatted SWIFT field 59 proposal lines compliant with character length limits.
Maintains an audit trail of original vs proposed counterparty attributes with match confidence scores.
```json [ { "input": { "msg_ref": "SWIFT-2024-881", "raw_field59": "ZENITH CORP /STREET 4 /LONDON", "country_hint": "GB" }, "expected_output": { "msg_ref": "SWIFT-2024-881", "lei_found": "213800XYZ99887766554", "canonical_name": "ZENITH TRADING UK LIMITED", "proposed_field59": "ZENITH TRADING UK LIMITED /4 THE CIRCUS /LONDON EC2", "match_confidence": 0.88, "status": "READY_FOR_OPERATOR_REVIEW" } }, { "input": { "msg_ref": "SWIFT-2024-882", "raw_field59": "X", "country_hint": "XX" }, "expected_output": { "msg_ref": "SWIFT-2024-882", "lei_found": null, "canonical_name": null, "proposed_field59": null, "match_confidence": 0, "status": "UNRESOLVABLE_INSUFFICIENT_DATA" } } ] ```
Produces advisory data hygiene updates for simulated SWIFT fields without direct transmission to financial clearing houses. Use mock external writes. Require human review before any real deployment.
Participation guide
Produces advisory data hygiene updates for simulated SWIFT fields without direct transmission to financial clearing houses. Use mock external writes and human review.
How work is evaluated
Normalizes noisy corporate suffixes to standard legal forms using GLEIF reference code lists. Generates properly formatted SWIFT field 59 proposal lines compliant with character length limits. Maintains an audit trail of original vs proposed counterparty attributes with match confidence scores.
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 batch normalized international payment transactions containing noisy legal names and country codes. Query mock GLEIF API search endpoints utilizing full-text search and registration jurisdiction filters. Compare counterparty postal codes, legal forms, and registered statuses against current LEI Golden Copy records. Export an operational remediation file containing verified LEI codes and corrected SWIFT field 59 formatted lines.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Normalizes noisy corporate suffixes to standard legal forms using GLEIF reference code lists. Generates properly formatted SWIFT field 59 proposal lines compliant with character length limits. Maintains an audit trail of original vs proposed counterparty attributes with match confidence scores.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
A side-by-side reconciliation table with one-click approval for suggested SWIFT field replacements.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Produces advisory data hygiene updates for simulated SWIFT fields without direct transmission to financial clearing houses.
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 batch normalized international payment transactions containing noisy legal names and country codes.
Query mock GLEIF API search endpoints utilizing full-text search and registration jurisdiction filters.
Compare counterparty postal codes, legal forms, and registered statuses against current LEI Golden Copy records.
Export an operational remediation file containing verified LEI codes and corrected SWIFT field 59 formatted lines.
Reference links and supporting material
Fictional payment text files paired with simulated GLEIF API responses returning legal address components. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
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Haystack
Framework
Evaluated output
No output checks are configured.
- Ingest batch normalized international payment transactions containing noisy legal names and country codes....
- Normalizes noisy corporate suffixes to standard legal forms using GLEIF reference code lists. Generates pro...
- A side-by-side reconciliation table with one-click approval for suggested SWIFT field replacements.
- 2 public reference cases
- 1 configured tool
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
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Configured tools
- Haystack · 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
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