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Credit Risk Analyst

Moniepoint

Posted 2 months agoLagos, Nigeria

Location

Lagos, Nigeria

Job Type

Full-time

Experience

Mid-Level

Category

Other

Job Description

Who we are Moniepoint Inc. is Africa’s all-in-one financial ecosystem, helping 10 million businesses and individuals access seamless payments, banking, credit, and business management tools since 2019. As Nigeria’s largest merchant acquirer, it powers most of the country’s Point of Sale (POS) transactions. Through its subsidiaries, Moniepoint Inc. processes $22 billion monthly for its customers while operating profitably. Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth. About the roleThe 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 Required Tools & TechnologiesData & Analytics 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 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)
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Requirements

  • Key Skills & Competencies:
  • 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
  • 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
  • What to expect in the hiring process:
  • A preliminary phone call with one of our recruiters.
  • A panel interview with the member of the team
  • An executive interview with the hiring manager