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Fraud Typology Library
The Fraud Typology Library is a structured spreadsheet for AML, fraud, and compliance teams at financial institutions. It catalogs fraud categories by red flag indicators, regulatory references, and applicable controls. Analysts and MLROs get a single reference document for risk assessments, SAR filing decisions, and examiner-ready documentation.
What is the Fraud Typology Library?
Fraud typologies aren't academic categories. They're the operational vocabulary of your AML and fraud program. When an analyst escalates a case, they need a label. When a compliance officer writes a SAR narrative, they need a regulatory reference. When an examiner reviews your program, they ask which fraud types are in scope and whether the controls match. The Fraud Typology Library is the document that answers those questions in one place.
The library is also the answer to a question every examiner eventually asks: "Show me your typology catalog." Without a structured, current document, teams improvise in real time, and that inconsistency shows up in findings.
The regulatory grounding is FATF Recommendation 1, which requires institutions to assess risk in proportion to their actual exposure. Generic statements like "fraud is a concern" don't meet this standard. Examiners from FinCEN, the FCA, and the Monetary Authority of Singapore expect documented evidence: which specific fraud schemes are plausible for your products and customers, and which controls address each one. FATF's guidance on the risk-based approach for the banking sector is explicit that this level of documentation is a supervisory expectation.
The library also anchors transaction monitoring rule calibration. If a fraud type doesn't appear in the catalog, there's a reasonable chance no monitoring rule covers it. Closing that gap starts with visibility, and visibility starts with a structured inventory.
This spreadsheet works for banks, credit unions, payment processors, money service businesses, and fintechs. The fields accommodate FinCEN, FCA, AUSTRAC, and other major AML frameworks without significant adaptation.
Who needs the Fraud Typology Library?
The people who fill this in are fraud analysts, AML investigators, and BSA compliance officers. The people who sign off are MLROs, Chief Compliance Officers, and heads of financial crime. Model risk teams use it when validating whether a detection model actually covers the schemes it's supposed to catch: if a scheme isn't in the library, the model validation report can flag it as an unscoped risk, and the compliance team has to explain the gap.
Specific trigger moments:
Annual risk assessment. The BSA/AML program refresh requires an enumeration of fraud risks with supporting evidence. The typology library is the working document you update, sign, and attach as a supporting exhibit. Without it, the risk assessment is a narrative assertion.
New product launch. When a bank adds instant peer-to-peer payments or a crypto-to-fiat ramp, the fraud profile changes fast. The library shows which new schemes that product introduces so controls can be built before the product goes live.
Post-SAR cluster review. After a wave of similar fraud filings, the question is: did we know about this pattern? The library is where you show you identified the typology, rated the risk, and had a control in place, or documented the gap.
Exam preparation. Staying continuously exam-ready means this document is current before a regulator asks for it, not assembled under pressure afterward. Examiners can and do compare typology libraries across exam cycles to assess whether a program is evolving.
What's inside the Fraud Typology Library
The spreadsheet has one row per fraud typology. A mid-sized bank typically runs 40-80 rows, covering the full range of schemes relevant to its products, customer base, and geography. Larger institutions with correspondent banking relationships or diverse product lines often exceed 100 rows. Here's what each row contains:
Core identification
| Field | What it contains |
|---|---|
| Typology ID | A reference code (e.g., FT-001) used in SAR narratives and audit trails |
| Typology Name | Standardized name: "Synthetic Identity Fraud," "Card-Not-Present Fraud," "Check Kiting" |
| Category | High-level grouping: Identity Fraud, Payment Fraud, Cyber-Enabled, Insider Threat, Trade-Based |
| Description | 2-3 sentences on the scheme mechanism |
Risk and detection
| Field | What it contains |
|---|---|
| Red Flag Indicators | Observable signals: "multiple accounts linked to one device fingerprint," "low-value test transactions before a large withdrawal" |
| Typical Transaction Pattern | Velocity, amount ranges, channel type, counterparty type |
| Risk Rating | High / Medium / Low for your institution, with a rationale field |
| Detection Difficulty | How hard this scheme is to catch manually, and why |
Controls and regulatory alignment
| Field | What it contains |
|---|---|
| Primary Control(s) | Customer Due Diligence, Enhanced Due Diligence, device fingerprinting, velocity rules |
| Monitoring Rule(s) | The specific transaction monitoring scenario covering this typology |
| Regulatory Reference(s) | The FinCEN advisory, FATF report, or FCA guidance that names this scheme |
| SAR Filing Threshold | Whether the typology typically meets mandatory reporting criteria |
Operational fields
| Field | What it contains |
|---|---|
| Last Reviewed Date | Audit trail for version control |
| Owner | The team responsible for keeping this row current |
| Control Gap / Remediation | If no control exists: the planned fix and target date |
| Notes | Jurisdiction nuances, product-specific considerations, open items |
FinCEN's fraud advisories are a practical starting point for the regulatory reference column. Published advisories name specific schemes, describe observable red flags, and cite the BSA obligations that apply. Use them to populate the regulatory reference field and to pressure-test your red flag list against what FinCEN actually expects investigators to recognize.
How to use the Fraud Typology Library
The library works best as a living document that feeds multiple compliance workflows, not a one-time deliverable.
1. Scope it to your institution. Start from the full typology list and mark each row as applicable or not applicable, with a brief rationale. A commercial lender with no consumer deposit accounts carries different exposure than a retail bank. Document the reasoning. Examiners notice unexplained omissions: if synthetic identity fraud is absent with no rationale, that's a conversation.
2. Assign risk ratings based on your specific exposure. Don't copy risk ratings from published FATF or FinCEN typology reports without adjustment. A scheme rated "Low" at the national level may be "High" for your customer segment or geography. The rationale field is where you record why you deviated from published benchmarks, and that explanation matters during exams.
3. Map every applicable typology to a control. For each row, identify the transaction monitoring rule, CDD step, or manual review process that covers the typology. If a row has no control, mark it as a gap with a remediation date. This column is what turns the library from a risk list into an actual gap analysis.
4. Use the Typology ID in case investigations. When an analyst flags suspicious activity, they should reference the Typology ID in case notes. That ID should flow into the SAR narrative, linking every filing to a documented, pre-approved scheme definition. Consistent labeling reduces quality variance across analysts and makes SAR clusters easier to spot and analyze.
5. Run a retrospective after significant filings. After a fraud loss event or a cluster of similar SARs, pull the library. Ask: was this typology listed? Was the risk rating appropriate? Did the assigned control actually fire? Update ratings and remediation notes based on what you find.
6. Expand coverage as new schemes emerge. If your MLRO is focused on expanding typology detection coverage, the library is where that expansion is anchored. Each new typology added should immediately prompt a control gap review.
Common mistakes to avoid
Not updating it after exam prep ends. Teams build the library for a regulatory exam and don't touch it for three years. Fraud schemes move faster than that. Pig butchering, deepfake-enabled account takeover, and AI-assisted synthetic identity fraud are operational realities now. Review the library at minimum annually, and update it whenever FinCEN or FATF publishes new typology guidance.
Red flags with no detection logic behind them. Listing "unusual transaction patterns" as a red flag helps no one. Every indicator should map to a specific monitoring rule or a field an analyst actually checks. If you can't name the rule, the control exists only on paper.
No gap column. The most common failure: teams populate the typology and control columns but never record whether an actual gap exists. Add a "Control Gap" column and a "Remediation Date" column. If both are consistently empty across the whole library, it isn't functioning as a risk management tool.
Copying published typology lists without adaptation. FATF and FinCEN publish solid typology research. Importing those lists verbatim without adjusting them to your institution creates a credibility problem. If trade-based money laundering is rated "High" in your library but you don't process trade finance transactions, an examiner will ask why.
Inconsistent terminology across teams. Fraud, AML, and cyber teams often use different names for the same scheme. If your fraud team calls it "first-party misuse" and your AML team calls it "friendly chargeback fraud," pick one name and enforce it across the program. The library is the single glossary.
No version history. Regulators sometimes request prior versions of key documents to assess how a program evolved. Keep dated copies, or use a shared drive with version history enabled.
How FluxForce automates this
The Fraud Typology Library documents what your team is supposed to detect. FluxForce closes the gap between documentation and execution. AI-powered fraud detection runs real-time monitoring against the typologies in your library, flags matches as they occur, and generates audit-ready evidence for every decision. When a typology triggers a SAR threshold, FluxForce can draft the narrative automatically.
If your library has 60 typologies but your monitoring rules only cover 30, FluxForce covers the remainder without adding analyst headcount. The library stops being a compliance document and becomes an active detection surface. Contact us to see how it works.
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