AI for National Payment Systems, Real-Time Payments & Payment Oversight Training Workshop

Course overview

The AI for National Payment Systems, Real-Time Payments & Payment Oversight Training Workshop equips central bank professionals, payment-system regulators, financial market infrastructure specialists and payment operations teams with the knowledge and practical skills to apply artificial intelligence, machine learning and advanced analytics to national payment system monitoring, real-time payment infrastructure, regulatory oversight and financial system resilience.

The programme examines how AI can strengthen central bank oversight of real-time gross settlement (RTGS) systems, automated clearing houses (ACH), instant and fast payment systems, mobile money ecosystems, card networks, electronic funds transfers and cross-border payment arrangements. Participants explore AI-powered transaction monitoring, anomaly detection, fraud pattern identification, payment-flow analytics, settlement liquidity monitoring, operational incident detection, systemic risk assessment and supervisory reporting

Course objectives

• Explain how AI, machine learning and real-time analytics can support the safety, efficiency, resilience and oversight of national payment systems.
• Evaluate AI governance, model risk, data protection, cybersecurity, explainability and operational resilience considerations in the oversight of payment infrastructure and payment service providers.
• Design AI-enabled supervisory dashboards, payment-system risk indicators, automated alerts and reporting frameworks for central banks and payment regulators.
• Develop analytical approaches for monitoring settlement liquidity, participant exposures, payment concentration, transaction bottlenecks and systemic vulnerabilities.
• Apply data analytics and AI-based anomaly detection to monitor payment flows, identify unusual transaction patterns, assess operational incidents and investigate emerging payment risks.

Who should attend

Course content

• Module 1: National Payment Systems, Central Bank Mandates and AI Applications National payment system architecture and institutional arrangements, roles of central banks and payment regulators, payment-system operators and participants, RTGS and deferred
• Module 2: Real-Time Payments Architecture, Data Flows and Interoperability Real-time and instant payment processing models, 24/7/365 payment availability, payment initiation and message routing, clearing and settlement workflows, participant connectivity
• Module 3: Payment Data Architecture, Data Engineering and Real-Time Analytics Payment transaction data structures, transaction-level and aggregated reporting, participant and counterparty reference data, payment message fields, timestamps and time-zone c
• Module 4: AI, Machine Learning and Anomaly Detection in Payment Systems AI and machine-learning foundations for payment oversight, supervised and unsupervised learning, clustering and outlier detection, isolation forests, autoencoders and other anomaly d
• Module 5: AI-Powered Payment Fraud Detection and Suspicious Activity Analytics Common payment fraud patterns, account takeover, authorised push payment fraud, identity misuse, mule-account networks, merchant fraud, duplicate payments, transaction manipul
• Module 6: Payment-System Oversight, SupTech and Regulatory Intelligence Central bank payment oversight frameworks, oversight objectives and powers, regulatory reporting requirements, payment-system designation and participation criteria, monitoring payme
• Module 7: Settlement Liquidity, Intraday Exposures and Payment Bottleneck Analytics Settlement liquidity concepts, intraday liquidity requirements, payment queues and settlement delays, participant funding patterns, peak payment periods, liquidity concen
• Module 8: Systemic Risk, Payment Networks and Financial Contagion Payment network structures, participant interconnectedness, transaction network analysis, centrality and concentration measures, payment dependencies, major participant failure scenarios,
• Module 9: Operational Resilience, Cybersecurity and AI-Based Incident Detection Operational risk in national payment systems, service availability and performance monitoring, incident classification and severity, outage detection, abnormal latency and tr
• Module 10: Cross-Border Payments, Remittances and Interoperable Payment Networks Domestic and international payment corridors, cross-border payment lifecycle, correspondent banking, remittance systems, regional payment integration, fast payment system in
• Module 11: Payment Performance, Financial Inclusion and Market Development Analytics Payment volume and value indicators, transaction growth and seasonality, payment channel utilisation, failed and reversed transactions, payment costs and efficiency, geo
• Module 12: Generative AI, Natural Language Processing and Automated Supervisory Reporting Generative AI applications in payment oversight, AI-assisted review of payment operator reports, extracting structured information from operational and compliance d
• Module 13: AI Governance, Model Risk, Data Protection and Regulatory Compliance AI governance frameworks, model inventory and ownership, risk-based AI deployment, model validation and performance monitoring, explainable AI, bias and fairness assessment,
• Module 14: Payment-System Dashboards, Risk Indicators and Supervisory Decision Support Designing payment oversight indicators, transaction volume and value dashboards, real-time system availability metrics, transaction success and failure rates, payment
• Module 15: Capstone — Designing an AI-Enabled National Payment System Oversight Framework Mapping the national payment ecosystem, defining central bank oversight objectives, identifying priority payment risks, designing a payment data architecture, spe
• Practical Exercises and Case Studies Analyse a simulated real-time payment dataset to identify unusual transaction volumes, processing delays and payment failures. Build an anomaly detection model to flag unusual participant-level payment patterns. Dev

General notes

• The workshop also covers AI-assisted oversight of payment service providers (PSPs), payment-system operators, switching companies, clearing and settlement institutions, fintechs and critical technology service providers. Participants learn how to transform payment-system data into actionable intelligence using machine learning, real-time analytics, network analysis, automated alerts, dashboards and supervisory technology (SupTech).
• Recommended Tools and Platforms Payment data engineering and streaming analytics: Apache Kafka, Apache Flink, Apache Spark Structured Streaming, SQL, PostgreSQL, and suitable enterprise data platforms.
• Data storage and analytics: PostgreSQL, Microsoft SQL Server, cloud data warehouses and approved institutional data platforms.
• Supervisory dashboards and reporting: Microsoft Power BI, Tableau, Excel, and approved business intelligence platforms.
• Operational monitoring and incident analytics: Grafana, Prometheus, Elastic Stack, Splunk and comparable monitoring or security analytics platforms, subject to the institution's existing infrastructure.
• AI-assisted document analysis: Approved enterprise AI assistants, natural language processing libraries, document search platforms and retrieval-augmented generation solutions.
• Payment standards and oversight references: ISO 20022, the Principles for Financial Market Infrastructures (PFMI), relevant CPMI guidance, national payment system legislation and regulations, and applicable cybersecurity, privacy and operational resilience frameworks.
• These tools are illustrative options, not mandatory requirements. The course can be delivered using synthetic datasets and open-source software, or adapted to a central bank's approved enterprise platforms. Live payment infrastructure and identifiable transaction data are not required for the practical exercises.
• Expected Practical Outputs National payment system architecture map, payment oversight data inventory, payment transaction data dictionary, real-time payment monitoring framework, payment-system performance indicator catalogue, payment anomaly detection prototype, synthetic payment fraud analytics model, transaction monitoring rules matrix, participant risk scorecard, settlement liquidity monitoring template, payment queue and delay analysis, payment network interconnectedness map, systemic risk indicator framework, operational incident detection dashboard, payment service provider supervisory assessment template, automated regulatory reporting workflow, AI governance checklist, payment data privacy and security checklist, model validation and monitoring checklist, payment oversight dashboard specification, supervisory alert and escalation matrix, cross-border payment performance scorecard, AI-assisted incident reporting template, national payment system oversight assessment framework, and an AI adoption roadmap for payment-system oversight.

Frequently asked questions

Schedule & fees