A tailored course, built for your situation
Operationally-Sound Anti-Money-Laundering Programs for Cross-Functional Programs
Build implementation-grade AML programs that align compliance, technology, and operational execution
The situation this course is for
Traditional compliance frameworks struggle to keep pace with agile delivery cycles. Siloed ownership between legal, risk, and tech teams leads to inconsistent implementation, delayed launches, and reactive fixes. Without an operationally-sound approach, organizations face inefficiencies, rework, and misalignment when scaling.
Who this is for
Technology and compliance professionals in fintech, digital banking, and regulated platforms who need to operationalize AML programs across product, engineering, and risk functions.
Who this is not for
This is not for auditors seeking checklist compliance, or professionals focused solely on regulatory interpretation without implementation intent.
What you walk away with
- Design AML controls that are embedded, not bolted-on
- Align compliance objectives with product development timelines
- Operationalize monitoring and reporting across data and engineering systems
- Lead cross-functional implementation with shared accountability
- Deploy a living AML program that evolves with business model changes
The 12 modules (with all 144 chapters)
- Defining operational soundness in AML
- From policy to executable control
- Mapping regulatory intent to system design
- Key differences: traditional vs. operational AML
- The role of cross-functional ownership
- Common failure modes in deployment
- Establishing shared KPIs across teams
- Integrating AML into SDLC
- Risk taxonomy for technology products
- Data provenance and control ownership
- Scaling AML with product velocity
- Building feedback loops into compliance
- Governance vs. gatekeeping
- Designing AML oversight councils
- RACI models for compliance delivery
- Escalation protocols for edge cases
- Aligning compliance cadence with sprint cycles
- Documenting decisions across silos
- Versioning control frameworks
- Managing exceptions with traceability
- Cross-team onboarding for AML
- Metrics that matter to engineering leaders
- Reporting up to executive risk committees
- Adapting governance to organizational scale
- AML-aware data modeling
- Transaction monitoring at ingestion
- Identity verification in onboarding flows
- Real-time risk scoring pipelines
- Event-driven AML architectures
- Data lineage for audit readiness
- API contracts for compliance services
- Rate limiting as a control mechanism
- Geo-based transaction routing rules
- Anomaly detection at the edge
- Data retention and compliance triggers
- Audit logging for automated systems
- Dynamic KYC workflows
- Risk-based document collection
- Liveness checks and synthetic fraud
- Integration with identity providers
- Adaptive friction models
- Behavioral biometrics in onboarding
- Cross-border onboarding constraints
- Handling incomplete profiles
- AML flags in user journey analytics
- Fallback paths for manual review
- Automated escalation triggers
- User experience vs. compliance tradeoffs
- From rules-based to behavior-based detection
- Designing signal pipelines
- Feature engineering for fraud models
- Threshold calibration strategies
- Reducing false positives with context
- Real-time vs. batch processing tradeoffs
- Case management workflow design
- Integrating investigator feedback
- Model validation for compliance
- Versioning detection logic
- Backtesting control efficacy
- Alert triage prioritization models
- Jurisdictional control mapping
- Local licensing impact on features
- Currency corridor restrictions
- Sanctions screening at transaction level
- Local partner due diligence
- Data residency and AML
- Cross-border reporting obligations
- Local regulator engagement models
- Adapting controls by market
- Geofencing transaction capabilities
- Multi-lingual alert handling
- Global incident response coordination
- AML data inventory design
- Data ownership across domains
- Schema evolution with compliance needs
- PII handling in monitoring systems
- Data quality monitoring for AML
- Cross-system reconciliation patterns
- Data retention and deletion workflows
- Audit trail design for regulators
- Query performance under compliance load
- Data access controls for investigators
- Anonymization for model training
- Data lineage tooling integration
- Immutable logs for compliance events
- Automated evidence generation
- Control execution tracing
- Time-series validation for transactions
- Automated gap detection in coverage
- Audit-ready reporting views
- Regulator-facing dashboards
- Automated control assertions
- Versioned compliance artifacts
- Self-documenting system design
- Audit trail compression strategies
- Chain of custody for digital evidence
- From prototype to production AML models
- Feature store for compliance signals
- Model drift detection in transaction patterns
- Human-in-the-loop validation design
- Explainability for regulator review
- Bias testing in risk scoring
- Model versioning and rollback
- Shadow mode deployment
- Performance monitoring for models
- Feedback loops from investigators
- Retraining cadence planning
- Model inventory management
- AML incident classification
- Technical containment playbooks
- Regulator notification timelines
- Cross-functional war room setup
- Evidence preservation protocols
- Public statement coordination
- Customer communication templates
- Post-mortem compliance review
- Systemic fix tracking
- Regulatory follow-up workflow
- Third-party incident coordination
- Lessons learned integration
- Automated control testing
- Red teaming AML workflows
- Synthetic transaction testing
- Control gap scanning tools
- Production telemetry for compliance
- Regression testing compliance paths
- Penetration testing AML systems
- Third-party control audits
- Benchmarking against peers
- Control maturity assessments
- Remediation tracking systems
- Executive reporting on control health
- Monitoring regulatory change pipelines
- Scenario planning for new rules
- Adapting to crypto-native patterns
- DeFi exposure assessment
- AI-generated fraud trends
- Biometric fraud detection
- Privacy-preserving AML techniques
- Zero-knowledge proofs in compliance
- Cross-chain transaction monitoring
- Preparing for central bank digital currencies
- Building AML adaptability into architecture
- Leadership communication for evolving risk
How this maps to your situation
- Designing AML systems for fast-moving product teams
- Integrating compliance into agile engineering cultures
- Scaling AML across jurisdictions and product lines
- Proving compliance without slowing innovation
Before vs. after
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3 hours per module, designed for integration into real-world planning cycles.
How this compares to the alternatives
Unlike generic compliance certifications or academic courses, this program is built for practitioners implementing AML systems in technology organizations, focusing on execution, integration, and real-world tradeoffs.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.