About the Role
A modern, data-driven credit risk management function plays a pivotal role in driving sustainable growth while safeguarding the organisation. By blending advanced analytics, technology, and strategic oversight, it supports, challenges, and advises all areas of the lending business. This involves setting robust policies, strategies, monitoring risk profiles, and proactively identifying and managing emerging risks.
The Analyst will support the risk function by delivering advanced data and analytical solutions to measure, monitor, and manage risk within a lending portfolio. Key responsibilities may include developing predictive risk and pricing models, automating reporting, managing credit analytics databases, and creating decision-support tools. This role enables data-driven decision-making, strengthens portfolio insights, and drives continuous improvement in credit risk management.
Key Deliverables
- Data Management & Feature Engineering: Collecting, cleaning, transforming, and engineering data to ensure accuracy, completeness, and suitability for analysis and model development.
- Analytics & Insights: Conducting deep-dive portfolio analytics, stress testing, and scenario analysis to identify risk drivers and emerging trends.
- Tool & Process Development: Creating calculators, scorecards, decision-support tools, and automation solutions that improve consistency and efficiency in credit
- Reporting & Visualisation: Designing dashboards, reports, and visual insights to clearly communicate risk movements, portfolio trends, and performance outcomes to
- Governance & Continuous Improvement: Ensuring models and tools remain compliant with regulatory expectations, while continuously refining methods to improve decision quality and operational efficiency.
- Predictive Modelling: Building, maintaining and operationalising credit risk models (e.g., Probability of Default, Loss Given Default, Exposure at Default) and other forecasting tools to assess customer behaviour and portfolio performance.
Essential Qualifications, Professional/Skills and Experience:
- University degree in a STEM or related.
- The suitable candidate should possess strong technical expertise, coupled with exceptional business acumen and excellent communication skills.
- Highly numerate and analytical.
- Exposure to analytical tools/ statistical modelling.
- MS Office (especially Excel, Word and Powerpoint).
- Hands on SAS, SQL, R, Python, VBA or other coding tools.
- Understanding of lending and financial concepts.
- Highly numerate and analytical.
Applications are to be addressed to the Senior Manager Talent Sourcing & Attraction and submitted via email to [email protected].
