Mapping data capabilities to technology assets to drive transparency and alignment between stakeholders Identifying duplication and inefficiencies across complex enterprise portfolios Supporting investment decisions through capability-based assessments How hard could it be saying NO ? Other challenges of data capability management.
Building data infrastructure that supports scalable AI and machine learning capabilities Applying AI in areas such as fraud prevention, predictive analytics, and operational automation Ensuring ethical, explainable, and regulation-compliant deployment of intelligent systems Positioning architects to evaluate and integrate AI solutions strategically within the enterprise
How does AI impact on the role of EA? How can EA use AI to be more effective in delivering value to the organisation? Examples of how Standard Bank enterprise architects use AI in their daily roles
Applying Zero Trust principles to strengthen architectural security postures Architecting systems to comply with frameworks such as the Digital Operational Resilience Act (DORA) Embedding cybersecurity design throughout application, data, and infrastructure layers Supporting rapid threat detection, containment, and recovery via resilient architectural patterns
Designing architectures that support instant payment processing and clearing Preparing infrastructure for central bank digital currency (CBDC) integration and experimentation Ensuring interoperability between traditional and digital financial systems Maintaining security and latency standards for next-generation transaction models
Comparing leading frameworks such as TOGAF, ArchiMate, and Zachman for real-world application Establishing effective architecture governance councils and decision-making workflows Aligning frameworks with enterprise priorities, compliance, and delivery models Evaluating fit-for-purpose approaches across decentralized and federated environments
Implementing hybrid and multi cloud models compliant with regulatory frameworks and data residency requirements Mitigating operational, contractual, and technical risks associated with cloud transitions Designing cloud governance models that balance flexibility, cost control, and oversight Exploring case studies on legacy system modernization through secure cloud adoption
Architecting for the secure integration of blockchain and DLT into core banking systems Understanding use cases such as digital identity, smart contracts, and payment clearing Ensuring compliance, privacy, and security in decentralized ledger environments Assessing the architectural impact of tokenization and real-time settlement models
Designing modular systems that support independent service deployment and agile development Integrating microservices with legacy core systems and critical banking platforms Managing complexity in distributed systems through orchestration and service lifecycle governance Addressing challenges of data consistency and operational monitoring at scale
Embedding agile delivery principles within architectural governance structures Facilitating collaboration across architecture, development, and operations teams Enabling faster time-to-value through continuous integration and delivery models Aligning architecture processes with iterative planning and adaptive execution cycles
Architecting enterprise-wide data governance frameworks for compliance and decision support Establishing transparency through metadata management, lineage, and audit capabilities Integrating real-time analytics and data quality controls into architecture strategies Aligning data governance with enterprise objectives and risk management practices
Architecting scalable API ecosystems to support open banking and embedded finance models Managing API lifecycle and governance to ensure performance and regulatory compliance Managing API lifecycle and governance to ensure performance and regulatory compliance Enabling agile partnerships while maintaining data integrity and customer trust
Creating architectures that support personalized, omnichannel customer journeys Integrating behavioral data, CRM systems, and AI to tailor digital experiences Supporting real-time responsiveness and user-centric service delivery at scale Ensuring consistent customer experience across legacy and modern platforms
Implementing Data Mesh, Data Governance and Data Lineage as well as Data Quality
Exploring how enterprise architects are addressing increasing regulatory pressure while enabling innovation. Sharing cross-functional practices that align architecture decisions with compliance, legal, and operational objectives. Highlighting leadership roles in anticipating regulatory shifts and building adaptive frameworks. Facilitating collaboration between architecture, risk, and compliance units to support long-term resilience.
