DISCOVER AI
Financial Crime Intelligence
NLP LabLifecycle: Build · InvestigatePRIVATE_PREVIEW

Narrative Analytics & NLP Lab

Narrative Analytics and Model Evaluation

Evaluate narrative intelligence with evidence, leakage controls, and human oversight.

Dedicated Sandbox Target:https://nlplab.discoveraisolution.com
The Operational Challenge

Why Financial Crime Teams Require NLP Lab

Over 80% of critical investigative context is buried in free-text transaction memos, counterparty notes, and prior investigative narratives. NLP Lab applies governed NLP, entity extraction, and controlled LLM assistance to accelerate SAR drafting, detect evidence gaps, and ensure narrative consistency.

Quantitative focus: Evidence Citation Accuracy & Zero Hallucinated Typologies
Regulatory alignment: OCC 2011-12 & Federal Reserve SR 11-7
Primary User Roles:
Senior InvestigatorsQuality Assurance LeadsFinancial Crime NLP Engineers
Governed Risk Domains:
Narrative AnalyticsSAR/STR Drafting SupportTypology Extraction
Repository Verified

Verified Technical Capabilities

Every capability below is backed by working code, verified algorithms, and evidence sources in the engineering repository.

Evidence-Grounded SAR Narrative Assistance

VERIFIED

Generate structured investigative narrative sections where every sentence is tied to specific cited transaction IDs and account evidence.

Evidence: Working/HRS/DataLab/nlplab / server.py

Typology & Predicate Crime Extraction

VERIFIED

Classify unstructured transaction remarks into standardized FinCEN and FATF typologies (e.g., structuring, funnel accounts, trade-based laundering).

Evidence: Working/predictive_qc_v1_merged/generator / narratives.py

Unsupported Claim & Hallucination Guardrails

VERIFIED

Audit generated narrative drafts against raw case data to flag any claim lacking primary document backing.

Evidence: Working/predictive_qc_v1_merged/contracts / narrative_contract.py

Sensitive PII Redaction & Prompt Governance

VERIFIED

Sanitize narratives according to bank privacy policies and preserve prompt versioning for audit traceability.

Evidence: Working/HRS/DataLab/nlplab / src/sanitizer.py
Operational Execution

Standard Operating Workflow

How NLP Lab executes within regulated banking environments, with explicit human oversight roles at every phase.

01

Case Material Ingestion & Masking

Ingest raw investigator notes, transaction records, customer statements, and prior SAR history.

Inputs / Outputs:
In: Unstructured text from CMS and core records
Out: PII-masked, tokenized document corpus
Human Decision Role:
Investigator selects evidence files for case synthesis
02

Typology & Entity Relation Extraction

Extract entities, dates, jurisdictions, amounts, and suspected typologies with confidence scoring.

Inputs / Outputs:
In: Masked case corpus
Out: Structured fact graph and chronology table
Human Decision Role:
Investigator confirms key factual chronologies
03

Assisted Draft Generation with Citations

Compile the 5-part SAR narrative structure (Who, What, When, Where, Why) with hyperlinked evidence citations.

Inputs / Outputs:
In: Verified fact graph and bank narrative template
Out: Editable narrative draft with inline source citations
Human Decision Role:
Investigator edits, rewrites, and reviews all drafted copy
04

Evidence Consistency & Completeness Audit

Verify that every stated conclusion matches source numbers and that no mandatory fields are missing.

Inputs / Outputs:
In: Completed narrative draft and source ledger
Out: Consistency scorecard and clearance check
Human Decision Role:
QA reviewer or compliance manager performs final review
Interactive Preview

NLP Lab Operational Exhibit

Synthetic demonstration illustrating data representation, factor decomposition, and audit trail generation.

CAS-2026-09418Apex Logistics & Freight LLC(CUST-883019)
SYNTHETIC DATA ILLUSTRATIONPending L2 Supervisor Disposition
Primary Typology
Rapid Movement of Funds
Total Trigger Volume
$482,500.00
Review Window
Trailing 14 Days
Risk Rating
HIGH RISK
Txn ID
Timestamp
Type
Counterparty & Corridor
Amount
TXN-9011
2026-09-02 09:14:22
Incoming Wire
Mariner Shipping Corp (Cyprus) CY
$240,000.00
TXN-9012
2026-09-02 11:32:05
Outgoing ACH
Vanguard Holdings Ltd US
$78,500.00
TXN-9013
2026-09-02 13:05:40
Outgoing Wire
Kestrel Trading International PA
$161,500.00
TXN-9024
2026-09-05 14:20:11
Incoming Wire
Mariner Shipping Corp (Cyprus) CY
$242,500.00
Discover AI Synthetic Demonstration EnvironmentSchema Source: DataLab / Synthetic Fixtures v2

Governance & Defensibility

  • Strictly prohibits autonomous filing: drafts require human review, editing, and final attestation
  • Enforces citation grounding: every claim must cite verified transaction or KYC records
  • All prompt templates, underlying models, and temperature parameters are versioned and audited
  • Preserves complete edit diffs between AI assistance and final investigator submission

Appropriate Use & Boundaries

Per Charter Section 11, Discover AI transparently discloses operational limitations:

  • •Requires human investigator adjudication for intent and regulatory filing determinations
  • •Performance relies on the quality and completeness of incoming investigator notes and source records
Frequently Asked Questions

Technical & Compliance Inquiries

Absolutely not. NLP Lab provides decision support and drafting assistance. The human investigator remains the sole author, editor, and authorized signatory on all regulatory filings.

Interoperable Suite Modules

CMSCase Management SystemQMSQuality Management SystemData LabGoverned Data Engineering

Evaluate NLP Lab in a Dedicated Synthetic Sandbox

Schedule an institutional technical review. We demonstrate Narrative Analytics & NLP Lab using synthetic data formatted to your exact core schemas.