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Central Banking · Physical, Online
AI for National Payment Systems, Real-Time Payments & Payment Oversight Training Workshop
10 Days5 sessions available Certificate on completion
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
Central bank payment-system oversight officers, national payment system regulators, payment operations managers, RTGS administrators, instant payment system operators, financial market infrastructure specialists, payment policy analysts, payment service provider supervisors, fintech regulatory officers, digital financial services specialists, financial stability analysts, payment fraud and risk analysts, settlement and liquidity risk officers, cybersecurity and operational resilience teams, SupTech and RegTech specialists, financial inclusion policymakers, national payment switch operators, clearing house personnel, mobile money ecosystem professionals, cross-border payments specialists, central bank IT and data analytics teams.
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 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
The programme is designed for central bank payment-system oversight officers, payment infrastructure operators, financial regulators, RTGS and instant payment specialists, payment policy analysts, financial stability teams, fintech supervisors, payment risk analysts and SupTech professionals.
Yes. It covers RTGS, automated clearing houses, instant and fast payment systems, mobile money, electronic funds transfers, card networks, payment switches, interoperability and selected cross-border payment arrangements.
AI can help identify unusual transaction patterns, detect abnormal system performance, prioritise supervisory alerts, analyse settlement delays, monitor payment concentration, assess emerging operational risks and automate parts of regulatory reporting. Outputs require appropriate validation and human review before being used for material supervisory decisions.
Yes. It introduces payment fraud analytics, suspicious transaction patterns, network-based risk indicators and relevant compliance responsibilities. It distinguishes central bank payment-system oversight from the separate statutory responsibilities of financial institutions, financial intelligence units and other competent authorities.
Basic data analysis experience is helpful. Participants undertaking the practical machine-learning exercises will benefit from familiarity with Python or SQL. The workshop can also include non-coding demonstrations using dashboards, synthetic datasets, structured reporting templates and existing analytical platforms.
Yes. The course introduces the Principles for Financial Market Infrastructures, relevant CPMI guidance, ISO 20022 and applicable national regulatory frameworks. The programme can be customised to the legislation, institutional mandate and payment infrastructure of a particular country.
Yes. The programme can be tailored to national payment infrastructure, mobile money ecosystems, instant payment platforms, RTGS operations, regional payment integration, payment service provider supervision, fraud analytics, operational resilience or the development of an AI-enabled SupTech framework.