Moniepoint Incorporated is a global business payments and banking platform and recently became QED Investors’ first investment in Africa. We are the partner of choice for over 600,000 businesses of all sizes, powering the dreams of SMBs and providing them with equal access to the tools they need to grow and scale.
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
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.
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.