Manager: Fraud Data Insights and Analytics

Empowering Africa’s tomorrow, together…one story at a time.

With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group.

This role sits within the Fraud Strategy function and focuses on data-driven fraud prevention, analytics-based insights, and strategic reporting to enhance decision-making, control design, and fraud loss reduction. The purpose is to lead the design, delivery, and continuous improvement of data-driven insights, analytical models, and fraud intelligence reporting for the Business Banking segment. The role leverages advanced analytics to detect emerging fraud patterns, optimize controls, and inform strategic fraud risk decisions across products, channels, and customer segments.

It ensures that the organization maintains a proactive, intelligence-led approach to fraud prevention and detection.

• Develop and implement data analytics frameworks to identify, quantify, and monitor fraud risk trends across Business Banking products and digital platforms.
• Produce actionable fraud insights, dashboards, and MI for senior management and fraud committees.
• Conduct deep-dive root-cause and loss analytics to support strategic decision-making.
• Partner with Fraud Operations to identify control weaknesses and recommend data-informed improvements.
• Design and maintain data models to track key metrics such as fraud losses, recovery rates, and prevention ROI.

• Apply predictive analytics and machine learning to detect anomalous behaviour, identify emerging fraud threats, and enhance early-warning systems.
• Collaborate with data science teams to develop, test, and calibrate fraud risk models.
• Evaluate performance of existing rules and models, ensuring optimal detection vs. false-positive rates.
• Support digital and product teams with data-driven fraud control design for new initiatives.

• Manage end-to-end fraud data collection, validation, and integrity across systems.
• Build automated fraud reporting pipelines (Power BI, Tableau, or other visualization tools).
• Translate complex data into clear narratives and visual storytelling for business and executive audiences.
• Contribute to monthly, quarterly, and ad hoc fraud performance reports to committees and regulators.

• Partner with internal stakeholders (Fraud Strategy, Fraud Operations, Business Banking Product Heads, Data & Analytics teams) to ensure a unified data approach.
• Support governance and risk functions with fraud data for audits, risk assessments, and regulatory submissions.
• Build strong relationships with Group Data, IT, and Cyber teams to align on data standards and security.

• Stay current with industry trends, analytics techniques, and fraud typologies.
• Lead or participate in data innovation projects – e.g., behavioural biometrics, network analytics, or AI-driven detection.
• Mentor analysts and develop the team’s analytical capability.
• Contribute to the strategic fraud roadmap by identifying new opportunities for data-led efficiencies.

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or Risk Management.
• Postgraduate qualification (MSc, MBA, or equivalent) advantageous.
• CFE (Certified Fraud Examiner) advantageous.
• Data Analytics Certifications (SAS, SQL, Python, R, Power BI)
• Machine Learning or AI certifications (AWS, Google, Microsoft)

• 7–10 years’ experience in data analytics, business intelligence, or fraud analytics (preferably in financial services or business banking).
• Proven track record in data modelling, dashboard design, and analytical problem-solving.
• Exposure to fraud risk management frameworks, digital banking, and payments ecosystems.
• Experience using big data environments (e.g., Hadoop, Spark, Databricks) and cloud analytics platforms.

• Analytical Thinking –…