Build a Watchlist Match Reviewer Disagreement and Audit Trail Synthesizer
Analyze screening adjudication variances across distributed compliance analyst teams reviewing FollowTheMoney entity hits. Reconcile contradictory False Positive and True Match verdicts to construct transparent supervisory audit trails.
What you are building
The core problem, expected build, and operating context for this challenge.
Analyze screening adjudication variances across distributed compliance analyst teams reviewing FollowTheMoney entity hits. Reconcile contradictory False Positive and True Match verdicts to construct transparent supervisory audit trails.
Compliance Quality Assurance Officer
Ingest completed screening review logs containing analyst notes, verdict choices, and applied risk thresholds.
Retrieve underlying FollowTheMoney entity properties and sanction listing history via a simulated yente service.
Identify systematic review discrepancies where analysts reached opposite conclusions on identical target entities.
Assemble an audit consensus report highlighting evidentiary gaps, policy drift, and retraining opportunities.
A review discrepancy workbench displaying analyst rationale side-by-side with underlying watchlist record diffs.
Fictional JSON compliance review decision tickets cross-referenced against synthetic yente match responses. Starter examples below are synthetic. They are not downloaded records.
OpenSanctions data toolkit Extracts FollowTheMoney schema entity attributes, match scoring metrics, and yente KYC appliance endpoint structures.
crewai, pydantic, fastapi. CrewAI facilitates multi-agent arbitration where one agent critiques evidence and another drafts policy compliance notes. Hosted reasoning model capable of identifying subtle discrepancies in natural language justification texts.
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.
Accurately pinpoints all cases with conflicting verdicts for identical FollowTheMoney target entities.
Categorizes discrepancy drivers into name similarity, PEP status interpretation, or secondary identifier mismatches.
Outputs a structured audit trail detailing analyst IDs, conflicting tags, and final supervisory consensus.
```json [ { "input": { "case_id": "CASE-6612", "target_id": "Q12345", "reviews": [ { "analyst": "usr_10", "verdict": "FALSE_POSITIVE", "reason": "Entity confirmed deceased in local register" }, { "analyst": "usr_22", "verdict": "TRUE_POSITIVE", "reason": "Matches active sanctions identifier" } ] }, "expected_output": { "case_id": "CASE-6612", "has_conflict": true, "discrepancy_category": "VITAL_STATUS_CONFIRMATION", "consensus_verdict": "ESCALATED_SUPERVISOR", "audit_summary": "Conflicting evidence regarding vital status; requires official death certificate verification." } }, { "input": { "case_id": "CASE-6613", "target_id": "Q99999", "reviews": [ { "analyst": "usr_10", "verdict": "TRUE_POSITIVE", "reason": "Exact passport match" }, { "analyst": "usr_22", "verdict": "TRUE_POSITIVE", "reason": "Passport and nationality match" } ] }, "expected_output": { "case_id": "CASE-6613", "has_conflict": false, "discrepancy_category": "CONSENSUS_REACHED", "consensus_verdict": "CONFIRMED_MATCH", "audit_summary": "Unanimous match on primary government identifier." } } ] ```
Facilitates internal quality control without executing regulatory freeze orders or sharing real personal data. Use mock external writes. Require human review before any real deployment.
Participation guide
Facilitates internal quality control without executing regulatory freeze orders or sharing real personal data. Use mock external writes and human review.
How work is evaluated
Accurately pinpoints all cases with conflicting verdicts for identical FollowTheMoney target entities. Categorizes discrepancy drivers into name similarity, PEP status interpretation, or secondary identifier mismatches. Outputs a structured audit trail detailing analyst IDs, conflicting tags, and final supervisory consensus.
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 completed screening review logs containing analyst notes, verdict choices, and applied risk thresholds. Retrieve underlying FollowTheMoney entity properties and sanction listing history via a simulated yente service. Identify systematic review discrepancies where analysts reached opposite conclusions on identical target entities. Assemble an audit consensus report highlighting evidentiary gaps, policy drift, and retraining opportunities.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Accurately pinpoints all cases with conflicting verdicts for identical FollowTheMoney target entities. Categorizes discrepancy drivers into name similarity, PEP status interpretation, or secondary identifier mismatches. Outputs a structured audit trail detailing analyst IDs, conflicting tags, and final supervisory consensus.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
A review discrepancy workbench displaying analyst rationale side-by-side with underlying watchlist record diffs.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Facilitates internal quality control without executing regulatory freeze orders or sharing real personal data.
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 completed screening review logs containing analyst notes, verdict choices, and applied risk thresholds.
Retrieve underlying FollowTheMoney entity properties and sanction listing history via a simulated yente service.
Identify systematic review discrepancies where analysts reached opposite conclusions on identical target entities.
Assemble an audit consensus report highlighting evidentiary gaps, policy drift, and retraining opportunities.
Reference links and supporting material
Fictional JSON compliance review decision tickets cross-referenced against synthetic yente match responses. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
crewAI
Multi-agent orchestration framework
Evaluated output
No output checks are configured.
- Ingest completed screening review logs containing analyst notes, verdict choices, and applied risk threshol...
- Accurately pinpoints all cases with conflicting verdicts for identical FollowTheMoney target entities. Cate...
- A review discrepancy workbench displaying analyst rationale side-by-side with underlying watchlist record d...
- 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.
View technical recipe
Configured tools
- crewAI · 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.