About the role
- The Risk Management Analyst is responsible for analyzing credit and portfolio data, monitoring risk exposures, and supporting data-driven lending decisions across Moniepoint’s ecosystem.
- The role combines credit risk expertise and data analytics to ensure portfolio quality, regulatory compliance, and sustainable growth.
Key Responsibilities
Portfolio Risk Monitoring:
- Track and analyze portfolio performance metrics (PAR, NPL, roll rates, recoveries)
- Monitor delinquency trends (PAR 0, 30, 60, 90, 360)
- Identify early warning signals (EWS) and emerging risk patterns
Data Analysis & Reporting:
- Extract, clean, and analyse large datasets from internal and external systems
- Develop risk dashboards and automated reports
- Provide daily, weekly, and monthly portfolio insights
Credit Decision Support:
Support underwriting with:
- Cash flow and behavioral analysis
- Customer risk profiling
- Provide data-backed recommendations on loan approvals, limits, and pricing
Risk Modeling & Analytics:
Support development of:
- Credit scoring models
- Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD)
- Conduct stress testing and scenario analysis
Portfolio Strategy & Optimization:
- Segment portfolio by industry, geography, and customer type
- Recommend risk-based strategies to optimize growth and minimize losses
- Support collection and recovery strategies using data insights
- Create model for monitoring e.g. Vintage, Credit Risk Appetite, Atypical
- credit model, Exceptions model, IS-WAS Model, Transaction Matrix etc
Regulatory & Compliance Support:
- Support reporting to regulators such as the Central Bank of Nigeria and credit bureau
- Assist with IFRS 9 Expected Credit Loss (ECL) calculations
- Ensure alignment with internal policies and risk frameworks
Systems & Process Improvement:
- Improve data pipelines, reporting efficiency, and risk monitoring tools
- Collaborate with product, engineering, and credit teams
- Support automation of risk processes
Key Deliverables:
- Portfolio risk reports (PAR, NPL, vintage analysis)
- Risk dashboards and performance trackers
- Early warning reports
- Stress testing and scenario outputs
- Credit decision insights and recommendations
Key Performance Indicators (KPIs)
- Accuracy and timeliness of reports
- Portfolio quality improvement (PAR/NPL reduction)
- Effectiveness of risk insights in decision-making
- Efficiency gains through automation
Experience & Qualifications
- Bachelor’s Degree in Finance, Economics, Statistics, Mathematics, or related field
- 4 – 5+ years’ experience in credit risk, data analytics, or fintech risk roles
- Experience in financial services or fintech is an advantage.
Required Tools & Technologies:
Data & Analytics:
- Microsoft Excel (Advanced)
- SQL
- Python (Pandas, NumPy)
- Visualization & Reporting
- Power BI
- Tableau
- Database & Systems
- MySQL / PostgreSQL
- Core banking/loan systems (e.g., Temenos, Finacle)
- Risk & Statistical Tools
- SAS / R (optional)
Key Skills & Competencies:
Technical Skills:
- Strong data analysis and statistical skills
- SQL and data querying proficiency
- Dashboard and reporting development
- Understanding of risk modeling techniques
Risk Knowledge:
- Credit risk lifecycle and lending processes
- Risk metrics (PAR, NPL, PD, LGD, EAD)
- Knowledge of IFRS 9
Soft Skills:
- Strong analytical thinking
- Attention to detail
- Communication and storytelling with data
- Stakeholder management.
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