Data & Artificial Intelligence Head - Transaction Banking, CIB

A significant opportunity exists within a leading financial services group for a strategic leader to spearhead the transformation of Transaction Banking into a truly data-driven and AI-enabled business. This pivotal role will define and execute a comprehensive, multi-year strategy, ensuring that the power of data and artificial intelligence is harnessed to unlock measurable business value across the entire transaction banking value chain.

Driving Data and AI Transformation

The core of this position involves architecting a clear vision for how data and AI can revolutionise Transaction Banking. This includes identifying and prioritising high-impact use cases across various segments such as Trade Finance, Payments, Investor Services, and Cash and Liquidity Management. The objective is to translate advanced analytical capabilities and AI solutions into tangible outcomes, such as enhanced productivity, accelerated decision-making, improved client experiences, and more robust risk management.

Key responsibilities will encompass:

• Developing and implementing a forward-thinking, multi-year Data and AI transformation strategy for Transaction Banking, ensuring alignment with broader Group technology standards and emerging market trends.
• Designing and prioritising a robust portfolio of AI and data initiatives, focusing on those with the greatest potential for commercial and operational impact.
• Leading the redesign and automation of critical business processes through the strategic integration of AI, aiming to boost efficiency and streamline operations.
• Building advanced analytics capabilities, including client opportunity dashboards and predictive insights, by effectively combining internal transaction data with external market intelligence.

Governance, Ethics, and Team Leadership

Beyond strategic planning and execution, this role carries significant responsibility for establishing and maintaining robust data governance and AI ethical frameworks. The incumbent will act as the custodian for data quality, regulatory compliance, and the responsible, ethical application of AI across the business. This includes championing principles of Responsible AI, ensuring data lineage, and upholding the highest standards of data security and risk management.

Furthermore, the position demands strong leadership and change management skills to drive enterprise-wide adoption of AI and data-driven decision-making. This involves cultivating data literacy programmes, building capabilities within global Transaction Banking teams, and fostering a culture of continuous improvement.

The successful candidate will lead and inspire multidisciplinary teams, comprising data scientists, engineers, product owners, and business stakeholders, to deliver the Data and AI roadmap using agile methodologies. Collaboration will be key, working closely with other divisions within the banking group, Group Technology, fintech partners, and external vendors to develop scalable data infrastructure and explore cutting-edge technologies.

Key governance and leadership aspects include:

• Establishing and overseeing Data and AI governance frameworks, including funding models, prioritisation processes, and decision-making forums.
• Championing Responsible AI principles, data governance, data quality, data lineage, and regulatory compliance.
• Driving AI adoption through effective change management, capability building, and literacy programmes.
• Leading and mobilising diverse teams using agile methodologies to achieve strategic objectives.
• Partnering with internal and external stakeholders to build scalable data infrastructure and evaluate new technologies.
• Ensuring effective financial stewardship and benefit realisation for the Data and AI portfolio.
• Mentoring and developing specialist talent to build sustainable organisational capacity.

This is a senior executive position requiring a minimum of 10 years of experience in financial services, digital transformation, or data and analytics, with a deep understanding of Transaction Banking products and CIB transaction flows. Demonstrated success in applying AI and advanced analytics to achieve measurable business outcomes in complex, multinational environments is essential. Strong behavioural competencies in strategic thinking, problem-solving, and team leadership, alongside technical expertise in data architecture, AI lifecycle management, and risk management, are highly valued.

In South Africa, a role at this executive level, leading significant digital and AI transformation within a large financial institution, typically commands a competitive remuneration package. The career path often involves progression into broader strategic technology or business unit leadership roles. Employers for such positions are predominantly major banking groups and established financial services providers looking to innovate and maintain a competitive edge in the digital landscape.

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