Credit Risk Analyst Job 4G Capital
Project Management Jobs. 4G Capital Jobs
Job Purpose
The Credit Risk Analyst supports the execution of 4G Capital’s credit risk and portfolio management strategies through rigorous data analysis, monitoring, and reporting.
Working closely with the Credit Risk Manager, the role focuses on generating insights from credit performance data, identifying emerging risks and opportunities, and supporting data-driven decisions across origination, increments, retention, and collections. The analyst plays a key role in ensuring credit strategies are evidence-based, scalable, and aligned with portfolio objectives.
Roles & Responsibilities
Portfolio Monitoring & Analysis
- Monitor portfolio performance across key risk metrics including default, retention, retention, and collection trends.
- Review credit portfolio dashboards and reports to track credit quality, growth, and stress indicators.
- Identify early warning signals of portfolio deterioration and flag emerging risks to the Credit Risk Manager.
Portfolio Performance & Market Insights
- Support the Credit Risk Manager in the design, testing, and refinement of credit strategies across origination, increments, retention, and collections.
- Analyse the impact of credit policy changes, adjustments, and strategy pilots on portfolio performance.
- Prepare analysis to support credit policy reviews and product enhancements.
- Assist in monitoring the performance of new models, rule changes, or experiments during pilot phases.
Collections & Delinquency Management
- Analyse pre-delinquency and post-delinquency behaviour to identify opportunities for improved risk mitigation and recovery.
- Provide analytical support to collections strategy by evaluating effectiveness of interventions and customer treatment paths.
- Track repayment behaviour and stress patterns to inform proactive portfolio actions.
- Work closely with Operations and Collections teams to provide sufficient analysis to support collection efforts
Risk & Decision Science
- Query, clean, and analyse large datasets using SQL and Python to support credit risk analysis.
- Work closely with the data and decision science teams to ensure data definitions, metrics, and logic are well understood and consistently applied.
- Support the development and validation of scorecards, rules, and risk indicators.
- Document assumptions, methodologies, and findings to ensure transparency and repeatability of analyses.
Stakeholder & Investor Engagement
- Prepare clear, concise analytical outputs for the Credit Risk Manager to share with senior management and other stakeholders.
- Translate analytical findings into practical insights that can be understood by non-technical teams.
- Support internal and external reporting requirements, including investor, audit, and regulatory requests, as required.
Required Skills for Credit Risk Analyst
- Must be curious to ask questions, possess the technical skills to interact and query the data, robustly analyse the data, and then effectively communicate the findings to non-credit experts around the company.
- 2-4 years of experience in credit risk analysis, portfolio analytics, or data analysis within fintech, banking, or financial services in East Africa.
- Bachelor’s or Master’s degree in Business, Economics, Mathematics, Statistics or a related field.
- Strong analytical skills with expertise in hands-on experience analysing credit or transactional data.
- Proficiency in SQL and Python for data analysis and reporting.
- Hands-on experience in analysing credit data, with an understanding of Kenyan and international credit regulations.
- Data-driven mindset with proficiency in modern risk decisioning tools, analytics platforms, and financial modelling.
- Experience in fintech, high-growth lending environments, or alternative credit models is a plus.
Preference
- Experience in Non-Traditional banking credit roles, ideally in Kenya.
- Exposure to mobile-based lending, digital credit products, or high-growth lending portfolios.
- Demonstrated self learner with an interest in developing deeper credit risk and data science skills
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