Agentic Risk Analyst

What could go wrong with this AI use case, and what should we do about it?

Chirag Dani · ARA v3.2.1
LLM: huggingface · meta-llama/Llama-3.3-70B-Instruct · Secure-RAG: connected

Library / ARA-261031-04C8B0 / governance

Worked example: AI-assisted AML transaction monitoring

Versions of this assessment, reviewer sign-off, suggested framework mapping, and every linked deliverable.

Sign-off

Sign off version 1 (the latest run). 13 of 13 items are not yet reviewed; the sign-off will record this.

Versions (1)

VersionSaved (UTC)ModelSHA-256
12026-10-31 06:37:15Worked example: prepared in advance, not generated live2fbf5c14fd7140e1

Client

Item-by-item review

Confirm each AI-drafted risk, threat, regulatory finding and control. 0 of 13 reviewed (0 changed, 0 rejected). "Accepted with changes" needs a note describing the change. The counts are sealed into the sign-off.

TypeIDItemReviewNoteLast reviewed
riskR-01Suspicious matters missed after replacing rules (Critical)
riskR-02Analysts approve drafts without real review (High)
riskR-03Customer data processed offshore (High)
riskR-04Hallucinated facts in SMR narratives (High)
threatT-01Prompt injection through payment memos (High)
threatT-02Exposure of SMR content (High)
regulationREG-01Anti-Money Laundering and Counter-Terrorism Financing Act 2006 (suspicious matter reporting): applicable
regulationREG-02Privacy Act 1988 (APP 8 cross-border disclosure): applicable
regulationREG-03APRA CPS 230 Operational Risk Management: applicable
controlC-01Parallel run with the rules engine
controlC-02Evidence-linked SMR drafts
controlC-03Quality sampling of approvals
controlC-04Data minimisation and onshore option

Deliverables

Board pack (Word)Risk register (Excel) Printable report
Failure simulationsnone
Operating envelopesnone
ADM inventory entriesnone (add)
Vendor reviewsnone (start)

Framework mapping (suggested)

Suggested by keyword rules at heading level; verify each mapping against the licensed standard before using it in a statement of applicability or audit.

ControlISO/IEC 42001 Annex ANIST AI RMFISO/IEC 27001:2022OWASP LLM 2025
C-01 Parallel run with the rules engine----
C-02 Evidence-linked SMR drafts----
C-03 Quality sampling of approvalsA.9 Use of AI systems--LLM06 Excessive Agency
C-04 Data minimisation and onshore optionA.7 Data for AI systems---

Headings with no mapped control

ISO/IEC 42001 Annex A: A.2 Policies related to AI; A.3 Internal organization; A.4 Resources for AI systems; A.5 Assessing impacts of AI systems; A.6 AI system life cycle; A.8 Information for interested parties of AI systems; A.10 Third-party and customer relationships

NIST AI RMF: GOVERN; MAP; MEASURE; MANAGE

An uncovered heading is a prompt to check whether a control is needed, not proof of a gap.

Decision support only, not legal or regulatory advice. AI-generated ratings and citations must be reviewed by a qualified person before they are relied on.