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Head: Fraud Data Insights and Analytics

Job in Sandton, 2172, South Africa
Listing for: Absa Group
Full Time position
Listed on 2026-03-04
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, AI Engineer, Data Security
Job Description & How to Apply Below

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.

Job Summary

To provide strategic leadership and direction for the development and execution of data-driven fraud insights, analytics, intelligence capabilities and automation within the Business Banking Fraud Strategy function. This role is responsible for building and overseeing an integrated ecosystem that uses data science, machine learning, advanced analytics, and intelligent automation to deliver proactive, predictive, and efficient fraud risk management. The incumbent ensures that data insights and automation are leveraged to reduce fraud losses, optimize controls, streamline processes, and inform executive decision-making, while maintaining compliance and governance standards.

Job Description Key accountabilities

Strategic Leadership
  • Define and drive the Data, Analytics & Automation strategy for Fraud Strategy in alignment with the Business Banking and Group Fraud vision.
  • Set the data and automation roadmap to deliver measurable fraud detection and prevention outcomes.
  • Champion the adoption of AI, robotic process automation (RPA), and intelligent workflow solutions to strengthen fraud operations and insights.
  • Partner with Group Data, Risk, IT, and Digital leadership to align analytics and automation initiatives with enterprise transformation goals.
Data Analytics & Insights
  • Lead the design and implementation of advanced analytics frameworks to detect and predict emerging fraud risks.
  • Develop and oversee data models and algorithms that support early‑warning indicators and proactive fraud monitoring.
  • Translate complex analytical findings into clear strategic insights and actionable intelligence for executives and business leaders.
  • Ensure the delivery of accurate, timely, and meaningful MI dashboards for Fraud Strategy and senior governance forums.
  • Drive data storytelling and visualization excellence using Power BI, Tableau, or similar platforms.
Automation & Innovation
  • Identify and implement automation opportunities across fraud detection, reporting, and investigation processes (e.g., RPA, machine learning, workflow orchestration).
  • Collaborate with technology partners to design and deploy AI/ML‑driven solutions that improve fraud detection accuracy and reduce manual interventions.
  • Oversee process optimization projects aimed at improving fraud system efficiency, speed, and scalability.
  • Champion continuous innovation by testing and integrating emerging technologies such as natural language processing, graph analytics, and behavioural biometrics.
Data Governance & Compliance
  • Ensure adherence to data governance principles, data privacy laws (POPIA, GDPR), and ethical AI standards.
  • Establish data quality, lineage, and integrity controls across fraud systems.
  • Collaborate with Group Data Management and Compliance teams to maintain full regulatory compliance in fraud analytics and automation activities.
  • Develop and maintain model governance and validation frameworks.
Fraud Intelligence & Reporting
  • Integrate multiple data sources (internal fraud databases, external intelligence, cyber feeds) to provide a comprehensive fraud risk view.
  • Produce trend analyses, predictive insights, and executive briefings on emerging fraud patterns.
  • Build a fraud analytics centre of excellence (CoE) to support strategic and operational fraud decision‑making.
Leadership & People Development
  • Lead a multi‑disciplinary team of data scientists, automation engineers, fraud analysts, and BI specialists.
  • Foster a culture of innovation, data curiosity, and continuous improvement.
  • Develop talent pipelines and ensure team members are equipped with evolving analytical and automation capabilities.
  • Promote a collaborative partnership with Fraud Solutions, Risk, Compliance, and Product teams.
Preferred Education
  • Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or Risk Management.
  • Postgraduate…
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