You've got 90 days to document how your institution detects, prevents, and responds to fraud. This isn't a compliance summary or a list of tools. It's a risk-based framework showing how your fraud controls map to the specific threats you face.
Nacha requires covered entities to implement and document risk-based fraud prevention processes. With fraud losses projected to reach $15.9 billion in 2025, this isn't about checking boxes. It's about building a fraud program that adapts to AI-driven attacks, faster payment windows, and the unique risks in your customer base.
Here's a template you can customize to meet the requirements and actually improve your fraud defenses.
Purpose of This Template
This template helps you document your fraud prevention framework to satisfy Nacha's risk-based approach while providing your fraud team with a practical blueprint. It covers:
- Risk assessment methodology
- Detection and monitoring controls
- Response procedures
- Annual review process
The template assumes you're an ACH Originating Depository Financial Institution (ODFI) or Third-Party Service Provider (TPSP). If you're a Receiving Depository Financial Institution (RDFI), adjust the origination-specific sections.
Prerequisites
Before customizing this template, gather:
- Your institution's ACH transaction volume by payment type (Same Day ACH, standard ACH, real-time payments if applicable)
- Historical fraud incident data (types, dollar amounts, detection methods)
- Current fraud detection tools and their integration points
- Customer segment profiles (business vs. consumer, industry verticals, geographic concentrations)
- Existing fraud policies and procedures documents
You'll also need buy-in from compliance, operations, and technology teams. This isn't a fraud-only document. Your risk assessment will reference account opening procedures, vendor management, and customer authentication protocols that live outside your fraud team's direct control.
The Template
FRAUD PREVENTION FRAMEWORK
[Institution Name]
Last Updated: [Date]
Next Review: [Date + 12 months]
1. RISK ASSESSMENT METHODOLOGY
1.1 Payment Type Risk Profile
- Same Day ACH: [Describe volume, typical use cases, fraud exposure]
- Standard ACH: [Describe volume, typical use cases, fraud exposure]
- Real-time payments (if applicable): [Describe volume, typical use cases, fraud exposure]
1.2 Customer Segment Analysis
For each significant customer segment, document:
- Segment definition (e.g., "Small business originators, <$500K monthly volume")
- Primary fraud risks (e.g., business email compromise, account takeover)
- Specific vulnerabilities (e.g., limited internal controls, high employee turnover)
- Risk rating: Low / Medium / High / Critical
1.3 Fraud Typology Inventory
Current threats identified in our environment:
- [Fraud type]: Frequency, average loss, detection rate
- [Fraud type]: Frequency, average loss, detection rate
- [Fraud type]: Frequency, average loss, detection rate
Emerging threats under monitoring:
- [Threat description and monitoring approach]
2. DETECTION AND MONITORING CONTROLS
2.1 Pre-Transaction Controls
- Account validation: [Method, coverage, exception handling]
- Originator onboarding: [KYC procedures, risk scoring, approval thresholds]
- [Multi-Factor Authentication](/glossary/multi-factor-authentication) (MFA): [When required, methods used, fallback procedures]
2.2 [Transaction Monitoring](/glossary/transaction-monitoring)
- Rule-based alerts: [List key rules, thresholds, review SLA]
- Behavioral analytics: [Models in use, training frequency, false positive rate]
- [Velocity checks](/glossary/velocity-checks): [Parameters, time windows, escalation triggers]
- [Watchlist Screening](/glossary/watchlist-screening): [Lists checked, update frequency, match resolution process]
2.3 Post-Transaction Monitoring
- Return monitoring: [Return codes tracked, investigation triggers]
- Customer dispute analysis: [Review frequency, pattern detection]
- [Suspicious Activity Report](/glossary/suspicious-activity-report) (SAR) filing: [Criteria, timeline, coordination with BSA/AML]
2.4 Technology Stack
- [Tool name]: [Function, integration points, data sources]
- [Tool name]: [Function, integration points, data sources]
Manual review triggers:
- [Condition requiring human review]
- [Condition requiring human review]
3. RESPONSE PROCEDURES
3.1 [Alert Triage](/glossary/alert-triage)
- Initial review SLA: [Timeframe]
- Escalation criteria: [Dollar threshold, fraud type, customer impact]
- Decision authority: [Who can approve/decline, dollar limits]
3.2 Investigation Process
When fraud is suspected:
1. [First action, e.g., "Freeze originator's ACH access"]
2. [Second action, e.g., "Pull transaction history for 90 days"]
3. [Third action, e.g., "Contact customer using verified phone number"]
4. [Documentation requirements]
5. [Resolution timeline]
3.3 Customer Communication
- Notification triggers: [When we contact customers about fraud]
- Communication channels: [Phone, email, secure message]
- Information provided: [What we tell customers, what we don't]
3.4 Recovery Actions
- Return filing: [Process, timeline, return codes used]
- Law enforcement referral: [Criteria, contact process]
- Loss recovery: [Internal write-off vs. recovery efforts]
4. CROSS-FUNCTIONAL COORDINATION
4.1 AML Integration
- SAR filing coordination: [How fraud team works with BSA/AML]
- Information sharing: [What data moves between teams, how often]
4.2 Cybersecurity Coordination
- [Indicator of Compromise](/glossary/indicator-of-compromise) (IoC) sharing: [Process for fraud team to receive threat intel]
- Incident response: [When fraud triggers broader security investigation]
4.3 Business Operations
- Customer experience considerations: [How we balance fraud prevention with friction]
- Revenue impact assessment: [How we evaluate controls that may affect legitimate transactions]
5. ANNUAL REVIEW PROCESS
Review schedule: [Month/quarter]
Review participants: [Roles, not names]
Review components:
- Fraud loss analysis: Actual vs. projected, trends, outliers
- Control effectiveness: Detection rates, false positive rates, response times
- Technology assessment: Tool performance, integration issues, vendor roadmap
- Regulatory changes: New requirements, industry guidance, peer practices
- Risk profile updates: New customer segments, payment types, fraud typologies
Documentation requirements:
- Written summary of findings
- Control changes implemented or planned
- Risk rating adjustments
- Board/committee reporting
6. DOCUMENTATION AND AUDIT TRAIL
We maintain records of:
- Risk assessments (current and historical)
- Fraud incidents (case files, investigation notes, outcomes)
- Control changes (what changed, why, when)
- Annual reviews (findings, actions, approvals)
Retention period: [Years, per internal policy and regulatory requirements]
Storage location: [System/repository]
Access controls: [Who can view, edit, approve]
How to Customize It
Section 1 (Risk Assessment): Use your actual incident data. If you've never seen a particular fraud type, don't list it just to look thorough. Your risk assessment should explain why certain threats matter to your institution.
Section 2 (Detection Controls): List what you actually use, not what you wish you had. If you're running rule-based monitoring without machine learning, document the rules and how you tune them. The faster your payment types, the more you should emphasize pre-transaction controls, because you won't have time to catch fraud mid-flight.
Section 3 (Response Procedures): Write this for the fraud analyst who's been on the job for three months. Include decision trees: "If the alert involves a Same Day ACH transaction over $X, escalate immediately to [role]." Specify your communication protocols to avoid creating more problems than you solve.
Section 4 (Cross-Functional Coordination): This section separates functional fraud programs from siloed ones. If your fraud team doesn't talk to your BSA/AML team until it's time to file a SAR, you're missing pattern intelligence. If your cybersecurity team discovers a phishing campaign targeting your customers and your fraud team doesn't hear about it until victims start calling, your controls are reactive when they should be proactive.
Section 5 (Annual Review): Schedule this review before year-end. You need time to implement changes before your next compliance cycle. Bring data: fraud loss by typology, false positive rates, customer complaint trends. If your controls blocked $2 million in fraud but also declined $500,000 in legitimate payments, that's a calibration problem worth documenting.
Validation Steps
After you've customized the template:
Cross-reference with Nacha's requirements. Confirm your framework addresses risk assessment, monitoring, response, and annual review. If you're a TPSP, verify you've documented how you support your ODFI clients' fraud programs.
Test a scenario. Walk through a hypothetical fraud case using your documented procedures. Can your team follow the steps without filling in gaps from institutional knowledge? If not, add detail.
Review with compliance and legal. They'll catch gaps in regulatory alignment and documentation requirements you might have missed.
Share with your fraud team. The people using this framework daily will tell you if it's realistic. If they say "we don't actually do it that way," either update the template or update your procedures.
Confirm your annual review date. Put it on the calendar now. Nacha requires at least annual reviews. If your fraud environment is evolving faster than that, consider quarterly updates to specific sections.
Your fraud prevention framework isn't static. As criminals adopt AI to scale attacks and faster payment adoption accelerates, you'll update detection models, adjust thresholds, and add controls. Document those changes in Section 6, and incorporate them into your next annual review. The institutions that treat this as a living program rather than a compliance artifact will build the structural differentiation that matters when fraud losses are climbing 27% year-over-year.
