Fraud Analytics Lead

Let's Write Africa's Story Together!

Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this.

Job Description

At OM Bank, we strive to attract great people who are passionate about coming together for a higher purpose- building something unique and aspirational, always aiming to be the best they can be. We are rooted in our purpose of inspiring and enabling our customers to grow and sustain their prosperity. 

ROLE OVERVIEW

 

As the Fraud Strategy and Analytics Lead at the Bank, you will play a pivotal role across the FRAML team in driving the data-driven decision-making processes. You will also form part of the Analytics Chapter, a function which provides the principles, support and guidance across the Control, Serve and Learn pillars.

• Your team will be responsible for ensuring the accuracy, integrity, and accessibility of data while fostering a culture of innovation and continuous improvement. The successful incumbent also has a track record of leading Analytical teams within a bank, driving outcome-based performance.
• Reporting directly to the Head of FRAML, you will be responsible for designing, implementing, maintaining, and enhancing fraud detection strategies and business rules to identify and mitigate fraud risks.
• This role combines strategy, data science, and collaboration, focusing on aligning fraud strategies with organizational goals while leveraging data science models and tools. The role will involve analyzing and integrating insights into Feedzai-based decisioning tools to ensure accurate, effective fraud prevention mechanisms.
• The successful candidate will drive innovation in fraud detection by combining business needs, stakeholder insights, data science techniques, and technology expertise to optimize fraud detection strategies and rulesets.

• The Fraud Strategy Lead will operate across technical and operational teams, ensuring business rules and models are well-tested, documented, and aligned with changing fraud patterns and business needs.
• The role also demands continuous learning to stay abreast of evolving fraud techniques, market trends, and technical advancements.The development of machine learning models, driving Fraud detection, rule efficiencies and fraud loss ratios and tolerance levels, the implementation of the AML strategy as defined for the group.

 

KEY RESULT AREAS

 

OM Bank aims to set a differentiated standard for its Fraud and Analytical capabilities. This includes:

Control

• Policy Development:
  • Assist in developing and updating fraud detection policies, procedures, and best practices.
  • Ensure compliance with regulatory requirements and internal controls.
• Adhere to data and analytical standards and governance
• Utilise and expand on the peer review process, and implement best standards when it comes to analytical processes, tooling and model lifecycle management.
• Establish strategies grounded in business insights, emerging fraud trends, and data science findings to minimize financial loss and operational risk.
• Map fraud strategy priorities to Feedzai models and tools by designing rule sets and decision frameworks to operationalize detection.

Serve

• Fraud Detection and Prevention:
  • Develop and execute The Bank’s Fraud Strategy, ensuring alignment with overall business objectives and PO goals.
  • Lead the development, implementation and maintenance of Fraud data models.
  • Utilize advanced analytics techniques to uncover trends, patterns, and opportunities for optimization.
  • Identify emerging fraud trends and recommend prevention strategies.
• Identify and prioritize data requirements for fraud initiatives, working with internal and external stakeholders to ensure data accuracy, completeness, and compliance.
• Stay informed about industry trends, emerging technologies, and best practices in fraud analytics, and recommend innovative solutions to enhance our data capabilities.
• Develop a deep understanding of the commercial levers and trade-offs across the fraud landscape. Use this understanding to inform data-driven decision-making processes  and the resulting business impact.
• Collaborate closely with cross-functional teams.
• Mentor and develop a high-performing team of data analysts and insights specialists, fostering a culture of collaboration, learning, and excellence.

Learn

• Actively partake in Analytical Community Events
• Share expertise and knowledge to support business wide analytical growth
• Pursue opportunities for professional development and certifications.

KPIs

• Accuracy and timeliness of reports and analyses.
• Adoption and usage rates of analytics services.
• Employee skill development and satisfaction.
• Quality and relevance of insights provided.
• Stakeholder satisfaction with analytical support. Align own behaviour with the organisation culture and values.
• Establish testing methodologies to validate business rules and strategies before deployment to ensure they are robust and effective.
• Maintain clear, comprehensive documentation of strategy designs, model integration plans, testing protocols, and business rule changes to support transparency and auditability.
• Monitor implemented strategies for effectiveness and adjust as needed, based on observed performance and fraud trends.

ROLE REQUIREMENTS

• Post Graduate Degree in Data Science, Statistics, or a related field.
• 5+ years of experience in Fraud.
• 3 Years’ experience in a leadership role within an analytics environment.
• Proficiency in data analysis tools (SQL, Python, R, SAS).
• Demonstrated expertise in data visualization tools such as Tableau, Power BI or Amazon QuickSight
• Strong analytical and problem-solving skills.
• Excellent communication and presentation abilities.
• Ability to work collaboratively in a team environment.
• Commitment to continuous learning and development.

 

Proven experience in:

• Leading fraud strategy, risk modelling, or fraud decision-making frameworks.
• Experience building business rules, integrating fraud strategy with machine learning models, and testing new strategies.
• Experience managing cross-functional teams or collaborating with technical and non-technical stakeholders.
• Proven success translating business needs into actionable strategies and models.
• A strong foundation in machine learning concepts and their practical application in fraud detection and risk modelling.

Manage a team of business analysts, statisticians, data scientists, and data modelers in using data to provide insights into business performance and suggest areas for and methods of improving operations. Translate the work of the Analytics function into findings for application by the broader business, including for use in strategic decision making and planning. Implement analytical approaches and methodologies and assist in the interpretation of results. OML Roles mapped to this profile are: Manager Analytics.

Responsibilities

Data and Analytics Strategy

Plan all business and technical aspects of different data and analytics systems and platforms. Understand features and properties, ensure data integrity of new and existing tracking, and own the maintenance and administrative functions of these systems and platforms. Understand and clearly articulate business challenges and translate these into actionable insights which can be acted on by business.

Data Exploration and Manipulation

Perform complex statistical analysis and utilize mining, modeling, and testing techniques to enable data exploration, manipulation and analysis.

Enterprise Business Analysis

Proactively interpret the business need and identify solution recommendations to business problems at a business unit level. Lead the improvement efforts that are within span of control at this level, according to best practice guidelines.

Insights and Reporting

Contribute to the design and creation of reporting strategies and templates. Lead execution of complex reports, identifying and interpreting complex patterns and trends, and translating those insights into actionable recommendations.

Leadership and Direction

Communicate the actions needed to implement the function's strategy and business plan within the team; explain the relationship to the broader organization's mission, vision, and values; motivate people to commit to these and to do extraordinary things to achieve local business goals.

Performance Management

Manage a team and report on the performance of a substantial, diverse team; set appropriate performance objectives for direct reports or project / account team members and hold them accountable for achieving these; take appropriate corrective action where necessary to ensure the achievement of team / personal objectives.

Business Requirements Identification

Elicit complex business requirements using a variety of methods such as interviews, document analysis, workshops, and workflow analysis to express the requirements in terms of target user roles and goals, in order to garner the "why" of the requirements and the benefits of such requirements.

Organizational Capability Building

Use the organization's formal development framework to identify the team's individual development needs. Plan and implement actions, including continuing professional development specified by professional or regulatory institutions, to build their professional capabilities. Provide informal training or coaching to others throughout the organization in own area of expertise to enable others to improve performance and fulfill personal potential.

Performance Improvement through Business Intelligence

Recommend changes and seek incremental improvement to policies, processes, standards and practices that would improve operational support, while owning critical prioritisation.

Internal Client Relationship Management

Manage relationships with internal clients and act as a business partner to them, building high levels of professional credibility and mutual trust, and managing the deployment of appropriate internal and/or external resources to support in delivering business strategy and plans.

Data Management

Manage key aspects of the data management system. This includes being responsible for developing or operating key elements of the system.

Data Commercialisation

Ensure data and information provided to business is of commercial value.

Skills

Action Planning, Adaptive Thinking, Agile Project Management, Business Requirements Analysis, Commercial Acumen, Computer Literacy, Data Compilation, Data Controls, Executing Plans, IT Network Security, Management Reporting, Negotiation, Policies & Procedures, Project Risk Management, Readiness Assessments, Report Review, Workflow Management

Competencies

Builds Effective Teams

Business Insight

Communicates Effectively

Cultivates Innovation

Decision Quality

Develops Talent

Directs Work

Drives Engagement

Education

NQF Level 7 - Degree, Advance Diploma or Postgraduate Certificate or equivalent

Closing Date

09 February 2025 , 23:59

The appointment will be made from the designated group in line with the Employment Equity Plan of Old Mutual South Africa and the specific business unit in question.

Old Mutual Limited is pro-vaccination and encourages its workforce to be fully vaccinated against Covid-19.

All prospective employees are required to disclose their vaccination status as part of the recruitment process.

Please refer to the Old Mutual’s Covid-19 vaccination policy for further detail. Kindly note that Old Mutual reserves the right to reinstate the requirement to vaccinate at any point if it is of the view that it is imperative to do so.

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