Scored Lending Analyst

Role Overview

Lead and direct the Scored Lending portfolio by combining rigorous credit risk oversight with a forward-looking view of portfolio health, ensuring every decision stays aligned with the Bank’s approved risk appetite. Your day-to-day work involves interrogating consumer credit data, preparing governance-level risk packs, and translating trends into actionable recommendations that support sustainable lending growth without compromising asset quality.

Key Responsibilities

• Continuously assess the performance of the scored lending book, flagging emerging risks, concentration issues, and deviations from established risk policies.
• Develop and deliver clear, concise credit risk reports for senior management, board risk committees, and other governance forums, turning raw data into decision-ready narratives.
• Lead the monitoring of key risk indicators across consumer lending portfolios, using historical and real-time data to identify shifts in customer behaviour or portfolio quality.
• Extract, transform, and visualise data from multiple internal systems using SQL, SAS, Python, or PowerBI to support analytical projects and recurring reporting.
• Contribute to policy and strategy development by providing empirical evidence on underwriting criteria, limit setting, pricing, and collections triggers.
• Conduct ad-hoc investigations into specific segments, products, or distressed accounts to explain performance anomalies and recommend corrective actions.
• Work closely with product, collections, and risk modelling teams to ensure portfolio decisions are grounded in sound analytics and consistently executed.
• Maintain robust data governance and documentation standards, ensuring all reporting processes are auditable, repeatable, and compliant with internal policies.

Requirements & Qualifications

• A first degree in Statistics, Mathematics, Actuarial Science, Economics, Finance, Data Science, Banking, Accounting, Computer Science, or another quantitative discipline.
• Between 5 and 7 years of hands-on experience in credit data analytics, specifically within consumer banking.
• Demonstrated experience working with digital consumer credit products—such as online loans, credit cards, or buy-now-pay-later facilities—including the use of data to drive portfolio insights.
• Strong proficiency in extracting, cleaning, manipulating, and visualising complex datasets using bank-approved tools such as SQL, SAS, Python, and PowerBI.
• A solid grasp of risk management principles, including early warning indicators, limit management, loss forecasting, and regulatory reporting expectations.
• Ability to structure ambiguous business questions and translate analytical outputs into clear, executive-friendly reports and presentations.
• Excellent attention to detail, with the ability to document processes, maintain data quality, and manage multiple deliverables simultaneously.
• Proven interpersonal skills that support productive collaboration across risk, finance, product, and technology teams.