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Challenge

Build a Transaction Narrative Drafter with Evidence Gap Detection

Synthesize chronological transaction narratives from bank transaction logs while explicitly highlighting missing documentary evidence. Compile investigative case briefs flagging gaps in counterparties, contracts, and shipping notes.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Synthesize chronological transaction narratives from bank transaction logs while explicitly highlighting missing documentary evidence. Compile investigative case briefs flagging gaps in counterparties, contracts, and shipping notes.

Financial crime intelligence investigator preparing defensible case summaries

Ingest chronological synthetic account transaction ledgers paired with attached documentary metadata.

Cross-examine each transaction row against expected document types including invoices, bills of lading, and contracts.

Identify documentary gaps such as missing proof of delivery or unexplained value discrepancies.

Generate a structured narrative brief articulating the fund flow while explicitly itemizing each unverified lead.

Command-line CLI and Markdown previewer displaying narrative paragraphs alongside a tabular evidence gap audit matrix.

A local synthetic fixture containing 15 multi-currency transaction records and associated simulated document manifests. Starter examples below are synthetic. They are not downloaded records.

Frictionless data validation Applies Frictionless Data tabular validation concepts from Source 3 to verify transaction table structure and missing fields.

dspy, frictionless, pydantic. DSPy allows compiling structured prompt signatures that strictly separate established facts from explicit evidence gaps. Requires local or remote LLM with strong zero-shot reasoning capabilities to isolate verifiable facts from gaps.

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 maps every transaction leg to corresponding proof documents in the narrative summary.

Generates an explicit list of evidentiary gaps with transaction references and missing document categories.

Outputs narrative artifacts formatted in structured JSON and Markdown without inventing unsupported transactional facts.

```json [ { "input": { "case_id": "CASE-8801", "transactions": [ { "tx_id": "TX-101", "date": "2024-03-01", "amount": 250000, "currency": "USD", "origin": "Apex Minerals LLC", "destination": "Vanguard Shipping Inc", "document_refs": [ "INV-101", "BOL-902" ] }, { "tx_id": "TX-102", "date": "2024-03-04", "amount": 248500, "currency": "USD", "origin": "Vanguard Shipping Inc", "destination": "Zenith Consulting Group", "document_refs": [] } ], "documents": [ { "doc_id": "INV-101", "doc_type": "commercial_invoice", "amount": 250000 }, { "doc_id": "BOL-902", "doc_type": "bill_of_lading", "carrier": "Atlantic Sea" } ] }, "expected_output": { "case_id": "CASE-8801", "narrative_summary": "On 2024-03-01, Apex Minerals LLC transferred 250,000.00 USD to Vanguard Shipping Inc, supported by commercial invoice INV-101 and bill of lading BOL-902. On 2024-03-04, Vanguard Shipping Inc transferred 248,500.00 USD to Zenith Consulting Group without attached documentary support.", "evidence_gaps": [ { "tx_id": "TX-102", "missing_document_types": [ "commercial_invoice", "service_agreement" ], "severity": "HIGH", "justification": "Rapid outbound fund movement of 248,500.00 USD lacks supporting commercial basis." } ], "verified_legs": 1, "unverified_legs": 1 } }, { "input": { "case_id": "CASE-8802", "transactions": [ { "tx_id": "TX-201", "date": "2024-03-10", "amount": 50000, "currency": "EUR", "origin": "Nordic Timber AB", "destination": "Baltic Logistics SIA", "document_refs": [ "INV-550" ] } ], "documents": [ { "doc_id": "INV-550", "doc_type": "commercial_invoice", "amount": 75000 } ] }, "expected_output": { "case_id": "CASE-8802", "narrative_summary": "On 2024-03-10, Nordic Timber AB sent 50,000.00 EUR to Baltic Logistics SIA referencing invoice INV-550.", "evidence_gaps": [ { "tx_id": "TX-201", "missing_document_types": [ "partial_payment_authorization", "bill_of_lading" ], "severity": "MEDIUM", "justification": "Transaction amount 50,000.00 EUR differs from invoice face value 75,000.00 EUR; delivery verification missing." } ], "verified_legs": 0, "unverified_legs": 1 } } ] ```

Strictly formats synthetic transaction logs. Does not submit SAR/STR filings to regulatory bodies or accuse individuals. Use mock external writes. Require human review before any real deployment.

Rules

Participation guide

Strictly formats synthetic transaction logs. Does not submit SAR/STR filings to regulatory bodies or accuse individuals. Use mock external writes and human review.

Delivery guide

How work is evaluated

Evaluation

Accurately maps every transaction leg to corresponding proof documents in the narrative summary. Generates an explicit list of evidentiary gaps with transaction references and missing document categories. Outputs narrative artifacts formatted in structured JSON and Markdown without inventing unsupported transactional facts.

Submission format

Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
4 scoring checks
Binary
1 pass or fail dimensions
Ordinal
3 scaled dimensions
Dimension 1

Complete workflow

Ingest chronological synthetic account transaction ledgers paired with attached documentary metadata. Cross-examine each transaction row against expected document types including invoices, bills of lading, and contracts. Identify documentary gaps such as missing proof of delivery or unexplained value discrepancies. Generate a structured narrative brief articulating the fund flow while explicitly itemizing each unverified lead.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 2

Correctness and evidence

Accurately maps every transaction leg to corresponding proof documents in the narrative summary. Generates an explicit list of evidentiary gaps with transaction references and missing document categories. Outputs narrative artifacts formatted in structured JSON and Markdown without inventing unsupported transactional facts.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 3

Review interface

Command-line CLI and Markdown previewer displaying narrative paragraphs alongside a tabular evidence gap audit matrix.

Score scale
012
Score 0

Missing or incorrect.

Score 1

Partly complete, with documented gaps.

Score 2

Complete, with reproducible evidence.

Dimension 4

Safe execution

Strictly formats synthetic transaction logs. Does not submit SAR/STR filings to regulatory bodies or accuse individuals.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Ingest chronological synthetic account transaction ledgers paired with attached documentary metadata.

  • Cross-examine each transaction row against expected document types including invoices, bills of lading, and contracts.

  • Identify documentary gaps such as missing proof of delivery or unexplained value discrepancies.

  • Generate a structured narrative brief articulating the fund flow while explicitly itemizing each unverified lead.

Resources and assets

Reference links and supporting material

Dataset notes

A local synthetic fixture containing 15 multi-currency transaction records and associated simulated document manifests. Supplied starter examples are synthetic, not source extracts.

Challenge setup

Configuration summary for this challenge.

Challenge input

Input details are not configured.

DSPy

Prompt and LM program optimization framework.

Evaluated output

No output checks are configured.

Evaluation checks
  • Ingest chronological synthetic account transaction ledgers paired with attached documentary metadata. Cross...
  • Accurately maps every transaction leg to corresponding proof documents in the narrative summary. Generates...
  • Command-line CLI and Markdown previewer displaying narrative paragraphs alongside a tabular evidence gap au...
Configured evaluation evidence
  • 2 public reference cases
Configured runtime
  • 3 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

Action Space
  • DSPy · Optional
Training Infra
  • DSPy · Optional
Orchestration
  • DSPy · 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.

Frequently Asked Questions about Build a Transaction Narrative Drafter with Evidence Gap Detection