Data & Artificial Intelligence Head - Transaction Banking, CIB at Standard Bank Group

Job Description

• We are looking for an experienced leader to drive the end-to-end transformation of Transactional Banking (TxB) into an AI-enabled, data-driven business. This role will provide strategic leadership for TxB Data and AI enablement, shaping the function's data and AI agenda, prioritising high-value opportunities, and driving adoption across the value chain.
• The successful candidate will be responsible for translating data and AI capabilities into measurable business outcomes, enhancing productivity, supporting client growth, strengthening risk management, and enabling innovation.
• The role also serves as the custodian of data governance, ensuring data quality, regulatory compliance, and the responsible, ethical use of AI across the business.

Key Responsibilities include

• Define and execute a multi-year Data and AI transformation strategy for Transaction Banking, aligning business objectives with Group technology standards and evolving market capabilities.
• Architect and prioritise a portfolio of high-impact AI and data use cases across Trade, Payments, Investor Services, Liquidity and Cash Management to maximise commercial and operational value.
• Lead the redesign and automation of core business processes through AI integration, improving productivity, accelerating decision-making, and enhancing client and employee experiences.
• Develop advanced analytics, client opportunity dashboards, predictive insights, and next-best-action capabilities by combining internal transaction data with external market intelligence.
• Establish and oversee Data and AI governance frameworks, funding models, prioritisation processes, and decision-making forums to ensure business value realisation and delivery excellence.
• Champion Responsible AI principles, data governance, quality, lineage, and regulatory compliance, maintaining the highest standards of ethical data usage and risk management.
• Drive enterprise-wide AI adoption through change management, capability building, literacy programmes, and the embedding of data-driven decision-making across global TxB teams.
• Lead and mobilise multidisciplinary teams of data scientists, engineers, product owners, and business stakeholders to deliver the Data and AI roadmap through agile methodologies.
• Partner with CIB, Group Technology, fintechs, and external vendors to develop scalable data infrastructure, evaluate emerging technologies, and strengthen Standard Bank's leadership in digital banking innovation.
• Accountable for the financial stewardship, performance measurement, and benefit realisation of the Data and AI portfolio, while mentoring and developing specialist talent to build sustainable organisational capability.

Qualifications

• Qualification: First Degree in Business Commerce, Finance and Accounting, Information Technology, Engineering Sciences Study Direction

Experience Required

• Transaction Banking
• 10+ years in senior executive roles within Financial Services, Digital Transformation, or Data & Analytics.
• Deep understanding of Transaction Banking products (Payments, Trade, Cash Management) and CIB transaction flows.
• Demonstrated experience applying AI/Advanced Analytics to deliver measurable business outcomes (productivity, revenue growth, or risk mitigation) in a complex, multi-national environment.

Behavioural Competencies:

• Adopting Practical Approaches and Producing Output
• Challenging Ideas and Developing Strategies
• Convincing People and Resolving Conflict
• Developing Expertise and Upholding Standards
• Interpreting Data and Taking Action
• Team Working and Valuing Individuals

Technical Competencies:

• Agile Concepts, Agile Principles and Agile Planning
• Agile Development and Agile Engineering
• AI Foundations, AI Platforms and AI Lifecycle Management
• Data Architecture, Data Development and Data Ingestion
• Data Discovery, Data Analytics and Statistical & Mathematical Analysis
• Data Governance, Data Compliance and Data Lifecycle Management
• Data Quality and Data Risk Management
• Machine Learning and AI Foundations
• Risk Management, Risk/Reward Thinking and Promote Good Governance, Risk & Control
• Financial Acumen and Financial and Accounting Control
• Financial Industry Regulatory Framework and Data Compliance
• Quality Management and Root Cause Analysis