Job Title Group Manager Continuous Data-Driven Assurance & Innovation
Reports to Group Lead, Continuous Data-Driven Assurance & Innovation
JOB PURPOSE
The Continuous Data-Driven Assurance & Innovation role is responsible for driving the modernization of internal audit through the integration of data analytics, automation, artificial intelligence, and emerging technologies. The role designs and operationalizes continuous, data-driven assurance approaches across the Group, embeds innovation into audit methodologies, and supports the transformation of Internal Audit into a forward-looking, technology-enabled function. This position plays a key role in enabling enhanced risk visibility, proactive issue identification, and stronger governance through advanced analytics, real-time monitoring, and automated audit workflows.
JOB CONTEXT
This position will require the candidate to exhibit integrity, intellectual curiosity, flexibility and objectivity. The candidate should bring strong technical and analytical instincts, the ability to translate complex data and emerging technologies into actionable assurance insights, and a proven capacity to partner with stakeholders across audit, risk, technology, and business functions.
The person will play a key role in elevating the bank's assurance capability through advanced analytics, automation, and innovation, and in strengthening the governance, risk management, and controls environment through digital assurance solutions.
KEY RESPONSIBILITIES
1. AI-Enabled Audit Transformation
• Drive the integration of artificial intelligence, automation, and emerging technologies into audit processes and methodologies.
• Identify, evaluate, and operationalize AI/ML use cases for predictive, proactive, and smarter assurance capabilities.
• Champion innovation in audit execution, methodology, and stakeholder engagement, embedding emerging practices into the function.
• Stay abreast of emerging audit technologies, analytics platforms, and AI/ML capabilities relevant to internal audit and assurance.
• Establish appropriate governance, risk, and quality safeguards over the use of AI and emerging technologies in audit activities.
2. Continuous & Data-Driven Assurance
• Design and implement continuous auditing approaches using data analytics, real-time monitoring, and automated controls testing.
• Develop and maintain analytical models, dashboards, and visualizations for risk trending, issue tracking, and key audit metrics.
• Enhance risk visibility and proactive issue identification across the Group through advanced analytics and continuous monitoring.
• Integrate data from core banking, digital channels, and enterprise systems to enable end-to-end audit coverage.
• Use analytics to support annual and risk-based audit planning, including trend analysis, risk scoring, and prioritization of focus areas.
• Deliver analytical insights that strengthen auditors' understanding of risk exposures across business lines and jurisdictions.
• Develop analytics and automated monitoring routines to identify suspicious transactions, anomalous activities, control override patterns, and emerging fraud indicators across the Group.
• Support investigations and forensic reviews through advanced data analytics, digital evidence analysis, and data-driven investigative techniques.
• Collaborate with investigations, compliance, AML, and security teams to enhance enterprise-wide fraud intelligence and proactive risk monitoring capabilities.
3. Audit Innovation & Methodology Modernization
• Evolve internal audit methodologies to reflect emerging risks, technologies, and business models.
• Develop reusable analytics, scripts, automated tests, and connectors that streamline and standardize audit procedures.
• Establish and maintain quality assurance over data analytics activities, ensuring methodology compliance, accuracy, and traceability.
• Document queries, models, and analytic procedures for audit workpapers, knowledge management, and methodology continuity.
• Embed innovation into audit execution and stakeholder engagement, ensuring the pillar's contribution evolves with the business.
4. Technology Enablement of Internal Audit
• Lead adoption of digital tools, analytics platforms, and audit management systems across Internal Audit.
• Support the broader transformation of Internal Audit into a forward-looking, technology-enabled function.
• Lead and develop a team of data and automation analysts within the pillar, providing technical guidance, mentoring, and performance management.
• Collaborate closely with Audit Managers, IT Auditors, Business Auditors, and the Technology Assurance & Cyber Security team to embed data-driven insights into audit outcomes.
• Present complex analytical findings clearly and concisely to non-technical auditors, senior management, and Audit Committees.
• Manage budgets, costs, and resources of the activities under accountability, ensuring effective delivery against the audit plan.
QUALIFICATION AND EXPERIENCE
Background/Experience
Experience
• At least 10 years of experience in data analytics, automation, internal audit, risk management, or technology assurance, preferably within the banking or financial services sector.
• Demonstrable experience leading or delivering continuous auditing, data analytics, and audit automation programs in a complex, multi-affiliate environment.
• Experience designing and operationalizing analytics solutions, dashboards, and automated audit workflows.
• Experience applying AI/ML or advanced analytics in audit, risk, fraud analytics, AML, or operational risk contexts is an added advantage.
Knowledge and Skills
Technical Expertise
• Strong hands-on expertise across data analytics and automation tools, including SQL, Python, ACL, Power BI, and Power Automate.
• In-depth understanding of database architecture, data integration, and cloud data platforms (AWS, Azure, GCP).
• Familiarity with audit management and continuous auditing platforms, and with analytics libraries and frameworks.
• Working knowledge of banking operations, core banking systems, and digital channels.
• Awareness of AI/ML governance, model risk management, and emerging analytics technologies.
• Working knowledge of internal audit processes, risk-based audit principles, and controls testing.
Risk Management and Audit:
• Excellent understanding of Risk-Based Audit principles and the ability to fully comply with IIA (Institute of Internal Auditors) standards.
• Solid understanding and ability to apply risk and control concepts in the context of data and technology assurance.
• Strong knowledge of IT and data governance, risk, and compliance best practices, with experience in assessing and mitigating technology, data, and analytics-related risks.
Analytical and Problem-Solving Skills
• Strong analytical and problem-solving skills, with the ability to translate complex datasets into clear insights and actionable recommendations.
• Detail-oriented yet able to grasp the big picture, identifying key risks, anomalies, and patterns within complex data environments.
• Inquisitive mindset to challenge assumptions, identify gaps in logic, and escalate issues in a timely manner.
Leadership and Management
• Proven track record of leadership and management in a complex, multi-affiliate environment, particularly in overseeing data quality assurance and audit data analytics.
• Proven experience in people management and leadership abilities, with the capacity to lead and mentor a team of data and audit innovation analysts.
• Ability to manage multiple projects simultaneously and meet deadlines, demonstrating a high degree of personal initiative and a proactive approach to work.
Communication and Interpersonal Skills
• Excellent communication skills, both written and verbal, with the ability to articulate complex technical and analytical concepts to non-technical stakeholders.
• Strong team player who collaborates effectively with colleagues and peers across the organization while being able to work independently when required.
• Demonstrates a positive, can-do attitude with a commitment to continuous improvement and professional development.
Other Requirements
• High degree of integrity, professionalism, and ethical standards, with a commitment to maintaining confidentiality and handling sensitive information with discretion.
• Demonstrates a strong understanding of the evolving technology and analytics landscape and keeps up-to-date with emerging data architectures, AI/ML developments, and analytical practices.
Qualifications
• Master's Degree in a related field (e.g., Data Analytics, Data Science, Computer Science, Engineering, Information Systems, Business, or Accounting), or Equivalent Combination of Work Experience and Education.
• Professional certifications such as CISA, CIA, CDPSE, or equivalent are desirable.
• Data analytics, data science, or cloud certifications (e.g., Microsoft, AWS, Google) are an added advantage.
PERSONAL ATTRIBUTES
• Ability to work effectively under pressure and meet deadlines.
• Strategic thinker with strong problem-solving capabilities and an innovative mindset.
• Culturally sensitive and able to work effectively in a diverse, pan-African environment.
• Excellent written and oral communication skills.
• Excellent time management and organizational skills.
• Good interpersonal skills.
• Strong analytical and result-oriented skills, with attention to detail and documentation discipline.
