ANALYST: FRAUD STRATEGY
On-siteCape Town, Western Cape, South Africa
Job Summary
Analyse fraud data to identify trends, emerging risks, control weaknesses, and opportunities to improve prevention and detection. Support the development, implementation, and monitoring of fraud strategies across application and transaction fraud, while assessing detection system effectiveness and rules. Monitor fraud performance metrics including losses, customer impact, and residual risk, then conduct root-cause analysis on fraud events and control gaps. Perform pre- and post-implementation analysis for strategy changes, translating findings into practical recommendations for stakeholders. Maintain strong data quality and reconciliation practices to ensure accurate governance reporting. This role contributes to strengthening WFS fraud capability across current platforms and future strategic initiatives, balancing risk minimisation with business growth and customer experience.
Required Qualifications
- Bachelor's degree in Finance, Economics, Statistics, Mathematics, Data Science, Actuarial Science, Engineering, Computer Science or a related quantitative discipline
- Strong analytical skills with the ability to work with large, complex datasets
- Proficiency in SQL and strong Excel capability
- Understanding of statistical, modelling and analytical techniques
- Ability to communicate complex analytical findings to technical and non-technical audiences
- Understanding of fraud risk, credit risk, customer lifecycle management and financial services products
- Knowledge of fraud strategy monitoring, fraud controls, decisioning systems and performance reporting
- Ability to assess rule effectiveness, alert quality, false positives, missed fraud and operational impacts
- Knowledge of, or ability to quickly learn, application and transaction fraud typologies
- Experience supporting strategy reviews, impact assessments and root-cause analysis
- Experience analysing data using SQL, SAS, Python, R, Excel or similar tools
- Experience working with large datasets, data quality assessments and reconciliations
- Ability to communicate analytical insights clearly to diverse stakeholders
- Ability to manage multiple priorities and deliver high-quality outputs independently
- High level of confidentiality, integrity and judgement when working with customer, fraud, transactional and business-sensitive data
- Ability to work with ambiguity, investigate data movements, ask the right questions and translate findings into practical fraud strategy recommendations
- Strong attention to detail, with the ability to produce accurate, evidence-based outputs suitable for management, governance and audit-related discussions
- Willingness to continuously build fraud, analytics, systems and business knowledge in line with the evolving WFS fraud strategy agenda
Desired Qualifications
- Postgraduate qualification in a quantitative, analytics, risk or business-related field
- Relevant fraud, risk, analytics, data science or business intelligence certifications
- Exposure to SQL, Python, R, SAS, Power BI, Tableau or similar tools
- Experience in fraud risk, credit risk, collections, recoveries, financial crime, customer analytics, decisioning, reporting or business intelligence
- Experience within financial services, retail credit, banking, payments, cards or lending
- Exposure to fraud detection systems, rules engines, transaction monitoring or decisioning platforms
- Experience supporting strategy monitoring, governance reporting and control performance reviews
- Previous fraud experience is not essential if the candidate demonstrates strong analytical capability, learning agility and the ability to apply data-driven thinking to fraud-related business challenges
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.