Business Analyst – Debt Review Analytics

SUMMARY:
Are you the kind of Analyst who looks at a messy debt review portfolio and instantly sees structure, patterns, and opportunity? Do you thrive in environments where your analytics directly influence strategy, operational performance, and millions in recoveries? If you’re driven by deep diagnostics, predictive modelling, and transforming complex portfolios into high-performing engines — this role is built for you.

POSITION INFO:
Business Analyst – Debt Review Analytics (Advanced Modelling / Collections Optimisation / Financial Services)

A forward-thinking organisation within the financial services and collections industry is searching for a Specialist Analyst to own and optimise the full debt review (DR) lifecycle. This includes active debt review, pre-termination, and terminated DR portfolios, using advanced analytics to drive yield, reduce drop-off, enhance recovery strategies, and shape operational decision-making.

This is your chance to become the single source of truth for DR performance — delivering insights, models, and frameworks that directly influence commercial outcomes.

Key Responsibilities:

• Build predictive models for drop-off risk, cure, reinstatement, settlement propensity, and post-termination recovery.
• Deliver end-to-end diagnostic insight across active DR, pre-term, and terminated DR portfolios.
• Map and optimise workflows, processes, and data flow across operations, PDAs, DCs, and internal systems.
• Develop portfolio segmentation frameworks and performance dashboards across mandates.
• Analyse payment behaviour, yield trends, reinstatement patterns, and termination economics.
• Provide strategic intelligence to improve collections performance, reduce exceptions, and drive consistent execution.
• Translate analytical findings into actionable operational and financial strategies.

• Education:
  • Degree in Mathematics, Statistics, Data Science, Actuarial Science, or similar (minimum NQF7)
• Experience:
  • 2–3 years’ experience in data analytics within financial services
  • Strong commercial awareness in collections, debt review, or unsecured lending
  • Proven experience in predictive modelling and strategy-driven analytics
  • Experience translating analytics into operational and financial action
  • Understanding of DR lifecycle, NCA processes, PDAs and DC behaviour (advantageous)
• Skills:
  • SQL (advanced)
  • Python/R (modelling & statistical packages)
  • SAS (advantageous)
  • Data visualisation (Power BI / Tableau)
  • Advanced Excel for financial modelling
  • Workflow and process optimisation
  • Strong communication and stakeholder influence
• Non-negotiables:
  • Ability to model, diagnose, and optimise complex DR workflows
  • Commercially minded with strong quantitative and analytical depth
  • Ability to own DR insights end-to-end and influence senior decision-makers

• Actuarial roles (Life, Short-Term, Health, Pensions, Quantitative)
• Data Scientists / Data Analysts (Python, R, SQL, Machine Learning)
• Risk Analysts (Credit, Market, Model Risk, Operational)
• Pricing Specialists (Insurance, Financial Products)
• Machine Learning & AI Data Scientists (ML Ops, NLP, Predictive Modelling)
• Quantitative Specialists across Banking, Insurance, and FinTech