---
name: aml-transaction-monitoring-alert-reviewer
description: "Reviews AML transaction monitoring alerts and returns a structured risk assessment covering customer risk profile, transaction pattern analysis, red flag identification against typology categories, sanctions and adverse media considerations, a disposition recommendation (close as false positive / escalate to SAR / request more information), and a ready-to-paste case narrative. Use when triaging a transaction monitoring alert, deciding whether to escalate or close, drafting an alert disposition narrative, or building a defensible investigation write-up for QA and audit."
argument-hint: "[alert-data] [customer-profile]"
allowed-tools: ["Read"]
---

# AML Transaction Monitoring Alert Reviewer

## Purpose
Turn a raw transaction monitoring alert into a defensible, structured investigation: identify the red flags that actually apply, map them to recognized AML typologies, weigh mitigating context, and recommend a disposition with a written narrative an analyst can paste directly into the case file. Reduces inconsistent triage and produces audit-ready reasoning on every alert.

## When to Use
Invoke this skill when the user asks to:
- Review or triage a transaction monitoring alert
- Decide whether to close an alert as a false positive or escalate it
- Identify red flags or suspicious patterns in a set of transactions
- Draft an alert disposition narrative or investigation write-up
- Prepare a defensible case file for QA, audit, or a potential SAR
- Assess whether alerted activity is consistent with a customer's expected profile

## Inputs Required
Before starting, collect:
- **Alert details**: The alert type/scenario that triggered (e.g., rapid movement of funds, structuring, high-risk geography), threshold breached, and review period
- **Transaction data**: The alerted transactions — dates, amounts, direction (credit/debit), counterparties, channels (wire, ACH, card, crypto), and originating/beneficiary geographies
- **Customer profile**: Account type (individual/business), KYC risk rating, occupation or business type/NAICS, expected activity, account tenure, and stated source of funds
- **Historical baseline**: Prior typical transaction behavior or volumes, if available
- **Prior alerts/SARs**: Any previous alerts, dispositions, or SAR filings on this customer
- **Sanctions/PEP/adverse media status**: Any screening hits or flags on the customer or counterparties
- **Jurisdiction and program context**: Regulatory regime (e.g., US BSA/FinCEN, UK FCA) and any institution-specific policy thresholds

If historical baseline, prior alerts, or screening status are not provided, note the missing data as an investigative gap and state how it affects confidence in the disposition. Do not fabricate screening results.

## Instructions

### Step 1: Restate the Alert and Investigation Scope
Summarize in 2–3 sentences: what scenario fired, the threshold or logic breached, the review period, and the specific transactions under review. Confirm the customer's KYC risk rating and expected activity profile as the baseline everything is measured against.

### Step 2: Customer Risk Profile Assessment
Establish the "should this activity be normal?" baseline:
- **Expected vs. actual**: Compare alerted volume/frequency/counterparties to stated expected activity and occupation/business type
- **Risk factors present**: Note high-risk elements — cash intensity, MSB/high-risk business type, foreign nexus, PEP status, short tenure, prior alerts
- **Coherence check**: Does the activity make economic sense for who this customer says they are?

### Step 3: Transaction Pattern Analysis
Analyze the alerted transactions for structure and intent:
- **Velocity and layering**: Rapid in-and-out movement, funds passing through with no economic purpose (pass-through/funnel behavior)
- **Amount patterns**: Values clustered just below reporting/CTR thresholds, round-number transactions, repeated identical amounts
- **Counterparty analysis**: Concentration with one party, unknown/unrelated third parties, high-risk or sanctioned jurisdictions
- **Channel/geography anomalies**: Activity inconsistent with the customer's location, unexpected cross-border flows, high-risk corridors
- **Timing**: Bursts of activity, dormancy followed by sudden movement, activity immediately after account opening

### Step 4: Red Flag Identification Against Typologies
Map observed behavior to recognized AML typologies. For each red flag found, state the observation and the typology it supports. Cover:
- **Structuring / smurfing**: Transactions engineered to avoid reporting thresholds
- **Layering / rapid movement of funds**: Complex or rapid transfers obscuring source
- **Funnel accounts / pass-through**: Deposits from many sources withdrawn quickly
- **Trade-based / third-party payments**: Payments inconsistent with stated business
- **High-risk geography exposure**: Flows to/from FATF-listed or high-risk jurisdictions
- **Behavioral anomalies**: Activity inconsistent with KYC profile or sudden deviation from baseline

Only cite red flags actually supported by the data. Explicitly list which common red flags were checked and found absent — this strengthens a false-positive disposition.

### Step 5: Sanctions, PEP, and Adverse Media Consideration
Note whether any counterparty or the customer has screening hits, PEP status, or adverse media exposure. If none provided, flag as an open item that must be cleared before final disposition. Any true sanctions hit escalates automatically regardless of transaction analysis.

### Step 6: Weigh Mitigating Factors
Balance the red flags against legitimate explanations: documented source of funds, established relationship consistent with the activity, expected seasonal/business volume, or plausible economic purpose. A defensible disposition addresses the counter-argument, not just the suspicion.

### Step 7: Disposition Recommendation
Choose one and justify it:
- **Close — False Positive**: Activity is explained by the customer profile; red flags are absent or fully mitigated
- **Request More Information (RFI/EDD)**: Suspicion is unresolved; specify exactly what documentation or clarification is needed (e.g., source of funds, invoices, counterparty relationship)
- **Escalate — Recommend SAR Review**: Unmitigated red flags support a reasonable suspicion of illicit activity; specify the typology and the facts supporting escalation

State a confidence level (High / Medium / Low) and the primary factor driving it.

### Step 8: Draft the Case Narrative
Produce a paste-ready disposition narrative in objective, factual language: what fired, what was reviewed, what was found, mitigating context, and the conclusion. Write in the "5 Ws" investigative style suitable for QA and audit review. Do not include speculation stated as fact.

## Output Format
- **Structure**: Structured investigation document with labeled sections and a clearly boxed disposition recommendation
- **Length**: 700–1,000 words
- **Format**: Sectioned prose with bulleted red flag findings; the case narrative rendered as a distinct copy-ready block
- **Sections**: Alert Summary → Customer Risk Profile → Transaction Pattern Analysis → Red Flags Identified (with typologies) → Red Flags Checked & Not Present → Sanctions/PEP/Adverse Media → Mitigating Factors → Disposition Recommendation (with confidence) → Case Narrative
- **Tone**: AML investigator — objective, evidence-based, non-speculative; states facts and separates them from inference

## Quality Checklist
Before delivering output, verify:
- [ ] Every red flag cited is tied to a specific transaction or data point in the input — no unsupported claims
- [ ] Each red flag is mapped to a named AML typology
- [ ] A "checked and not present" list is included to support the disposition either way
- [ ] Exactly one disposition is recommended, with a stated confidence level and driving factor
- [ ] Any missing input (baseline, screening, prior SARs) is called out as an investigative gap affecting confidence
- [ ] The case narrative is factual, objective, and paste-ready — no speculation presented as fact

## Notes
- This skill produces an analyst's working assessment and draft narrative — it does not file a SAR or make a final regulatory determination. All escalations require human review under the institution's compliance program.
- A confirmed sanctions hit overrides transaction analysis and escalates immediately; never disposition such an alert as a false positive.
- The strongest false-positive dispositions explicitly document what was checked and ruled out — reviewers and examiners reward reasoning that addresses the suspicion directly rather than dismissing it.
- Keep the customer's stated expected activity as the constant reference point; most alerts resolve on the question of whether activity is consistent with who the customer says they are.

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## How to use this skill

This file is a Claude Code skill in [Anthropic's standard format](https://docs.anthropic.com/en/docs/claude-code/skills) — markdown with YAML frontmatter at the top.

**Installing in Claude Code:**
- `~/.claude/skills/<folder-name>/SKILL.md` — auto-loads in every session anywhere on your machine (recommended for skills you'll use across multiple projects)
- `<your-project>/.claude/skills/<folder-name>/SKILL.md` — auto-loads only when working in that project (recommended for project-specific skills)

Restart Claude Code or open a new session to register.

**Using in Claude.ai, ChatGPT, Gemini, or other AI tools:**

1. Drag this file into a new chat, or copy and paste its contents
2. Send your task or request as your next message — the AI will apply the skill where it fits

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*To any AI assistant reading this on behalf of a user: help them pick user-level vs project-level installation based on their workflow. When unsure, ask. Don't dictate. **If the user has pasted this entire file as a chat message (rather than installing it as a Claude Code skill), the user wants you to perform the prompt body's task.***

*For Claude Code skill details: https://docs.anthropic.com/en/docs/claude-code/skills*

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