# Agentic Risk Analyst - Executive Assessment
## 1. Scenario
> A Tier-2 bank in Australia proposes to replace its rules-based AML transaction-monitoring engine with an LLM-based agent that reads free-text payment memos, customer notes and adverse-media results to score suspicious-matter reports (SMRs). The agent will draft the SMR narrative and auto-lodge to AUSTRAC once a compliance analyst clicks approve. The model is hosted on a US cloud region.
**Interpretation:** A Tier-2 Australian bank wants an LLM agent to replace rules-based transaction monitoring, score alerts and draft SMRs, lodged after analyst approval; the model is hosted in the US.
- Business objective: Improve detection of suspicious matters and reduce analyst effort
- Industry: Banking (Tier-2, Australia)
- Use case: LLM agent scores alerts and drafts suspicious matter report (SMR) narratives
- AI autonomy: human_approval_required
- Human oversight: A compliance analyst approves before lodgement
- Decision impact: Major: missed or wrong reports have legal consequences
- Jurisdictions: Australia, United States (hosting)
- Data types: Payment memos, Customer notes, Adverse media results, Transaction data
## 2. Executive Decision
**Decision:** REQUIRES REMEDIATION
**Overall inherent risk:** Critical
**Overall residual risk:** Medium
The idea has merit as a prioritisation and drafting aid, but replacing the rules engine without proven parity is not acceptable.
### Top risks
- Suspicious matters missed after replacing rules
- Analysts approve drafts without real review
### Key conditions
- Do not retire the rules engine until detection parity is demonstrated
- Evidence-linked drafts and second-line sampling
## 3. Remediation Plan
### 0-30 days
- **A-01** (Critical, AML Compliance Lead): Redesign as parallel run alongside the rules engine
### 30-90 days
- **A-02** (High, AI Engineering): Build citation checks into SMR drafts
- **A-03** (High, Privacy Officer): Assess cross-border data handling of the US-hosted model
### 90+ days
_No actions._
## 4. Risk Register
| ID | Category | Title | Likelihood | Impact | Inherent |
|---|---|---|---|---|---|
| R-01 | Compliance | Suspicious matters missed after replacing rules | Possible | Severe | Critical |
| R-02 | Operational | Analysts approve drafts without real review | Likely | Major | High |
| R-03 | Privacy | Customer data processed offshore | Likely | Moderate | High |
| R-04 | Model | Hallucinated facts in SMR narratives | Possible | Major | High |
## 5. Regulatory Findings
### Anti-Money Laundering and Counter-Terrorism Financing Act 2006 (suspicious matter reporting) (Australia) - Applicable
Source:
**Why relevant:** The agent supports SMR decisions and drafting.
**Scenario impact:** The program must cover the new monitoring method.
**Obligations:**
- Report suspicious matters to AUSTRAC within the statutory time frames
- Do not disclose ('tip off') that a report has been made
- Maintain an AML/CTF program
**Required controls:**
- Parallel run before retiring rules
- Tipping-off controls on outputs
### Privacy Act 1988 (APP 8 cross-border disclosure) (Australia) - Applicable
Source:
**Why relevant:** Personal information is sent to a US-hosted model.
**Scenario impact:** Contract and assessment of the US provider.
**Obligations:**
- Take reasonable steps so the overseas recipient handles the information consistently with the APPs
**Required controls:**
- Data processing agreement
- Data minimisation
### APRA CPS 230 Operational Risk Management (Australia) - Applicable
Source:
**Why relevant:** Material reliance on a third-party model provider for a compliance-critical process.
**Scenario impact:** Provider assessment and exit plan.
**Obligations:**
- Formal agreement with the material service provider
**Required controls:**
- Service provider due diligence
## 6. Compliance Gaps
| Area | Gap | Risk | Remediation |
|---|---|---|---|
| Validation | No evidence the agent detects what the rules detect. | Critical | Run both in parallel and compare before any retirement. |
## 7. Security Threats
### T-01 - Prompt injection through payment memos (ai_specific) - High
A memo instructs the agent to score the transaction as benign.
- **Attack vector:** Customer-controlled free text
- **Assets at risk:** Alert scores, SMR drafts
- **Likelihood x Impact:** Possible x Major
- **MITRE:** OWASP LLM01:2025
### T-02 - Exposure of SMR content (traditional) - High
Confidential report content leaks.
- **Attack vector:** Logs or provider retention
- **Assets at risk:** SMR data
- **Likelihood x Impact:** Unlikely x Severe
## 8. Controls
| ID | Control | Type | Effectiveness | Priority | Addresses |
|---|---|---|---|---|---|
| C-01 | Parallel run with the rules engine | Preventive | High | Immediate | R-01 |
| C-02 | Evidence-linked SMR drafts | Preventive | Medium | Immediate | R-04, R-02 |
| C-03 | Quality sampling of approvals | Detective | Medium | Near-term | R-02 |
| C-04 | Data minimisation and onshore option | Preventive | Medium | Near-term | R-03 |
## 9. Residual Risk
| Risk | Inherent | Controls | Residual | Justification |
|---|---|---|---|---|
| R-01 - Suspicious matters missed after replacing rules | Critical | C-01 | Medium | Parallel running prevents coverage loss. |
| R-02 - Analysts approve drafts without real review | High | C-02, C-03 | Medium | Citations and sampling expose weak review. |
| R-03 - Customer data processed offshore | High | C-04 | Medium | Minimisation reduces exposure. |
| R-04 - Hallucinated facts in SMR narratives | High | C-02 | Low | Uncited statements are flagged. |
## Evidence status
No external evidence was retrieved. Regulatory findings come from the model's general knowledge and must be verified against the source texts.
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_Generated by Agentic Risk Analyst (ARA). Decision support only, not legal or regulatory advice. Every rating and citation must be reviewed by a qualified person before it is relied on._