In an age of increasingly sophisticated financial crime, AI is essential for effective treasury compliance and fraud monitoring. This intensive course equips participants with advanced systems—covering AML screening, transaction anomaly detection, sanctions filtering, and identity verification. Using global best practices and real-case scenarios, delegates will design AI-enabled workflows that strengthen internal controls, regulatory compliance, and corporate resilience.
- AI-enabled AML and sanctions screening with KYC/KYD pipelines
- Machine learning for fraud detection: anomaly, check, and payment monitoring
- Transaction monitoring with real-time alerting platforms (Feedzai, ThetaRay)
- Identity fraud detection: document scanning and deep identity verification (AU10TIX)
- Federated learning and Explainable AI for privacy-preserving detection
- Sanctions & PEP screening via NLP and global watchlist matching
- Regulatory AI compliance and governance frameworks
- Voice-deepfake and generative AI frauds: detection and mitigation
- Ethical considerations and systemic AI risk management
- Configure AI-driven AML and sanctions monitoring systems
- Develop anomaly detection pipelines for transaction and payment fraud
- Evaluate identity verification platforms using machine learning
- Incorporate federated learning and XAI for compliant privacy solutions
- Implement AI sanction screening against global watchlists
- Use real-time alert systems to monitor emerging fraud trends
- Apply frameworks for AI governance and compliance traceability
- Recognize and mitigate ethical and systemic AI risks
- Treasury compliance officers and AML analysts
- Risk and operations managers in corporate treasury
- Financial crime, security, and internal audit teams
- RegTech and compliance solution leads
- Digital transformation and data science teams
- Legal and governance professionals in finance
- Expert demos of Feedzai, ThetaRay, AU10TIX, ComplyAdvantage
- Hands-on labs: anomaly model building, federated learning setup
- Interpretability: XAI workshops with SHAP/LIME for auditability
- Case simulations: sanction screening, document fraud, deepfake voice
- Ethical roundtables: bias, explainability, and systemic controls
- Governance clinics: policy design, AI oversight frameworks
- Overview: AML, sanctions, and fraud risk in treasury context
- Case studies: US Treasury fraud recovery, UK fraud surge
- Lab: simple anomaly detector using transaction data
- Tools demo: Feedzai & ThetaRay use cases
- Document fraud: scanning with AU10TIX
- Watchlist screening: ComplyAdvantage, global PEP lists
- Lab: build an identity and sanctions screening flow
- Discussion: balancing accuracy with privacy
- Privacy-first fraud detection: federated learning
- Introduce SHAP/LIME for model explainability
- Lab: federated model with XAI auditing
- Governance: audit trail and compliance documentation
- Emerging threats: deepfake voice scams, AI fraud attacks
- Lab: detect anomalies in audio-transaction streams
- Case study: multi-channel fraud event simulation
- Strategies: cross-team incident response protocols
- AI governance frameworks and risk registers
- Systemic AI risk: model concentration & bias
- Lab: design an AI governance schema with policy checks
- Final review: draft AI oversight roadmap & compliance plan
Group & Corporate Discounts: Available for companies enrolling multiple participants to help maximize ROI. Individual Discounts: Offered to self-sponsored participants who pay in full and upfront. Registration Process: Corporate nominations must go through the client’s HR or Training department. Self-nominations must be prepaid via the “payment by self” option. Confirmation: All registrations are subject to DIXONTECH’s approval and seat availability. Refunds: Provided in case of course cancellation or no seat availability. Tax Responsibility: Clients are responsible for any local taxes in their country.