Senior Credit Risk Analyst

FairMoney is a pioneering mobile banking institution specializing in extending credit to emerging markets. Established in 2017, the company currently operates primarily within Nigeria, and it has secured nearly €50 million in funding from renowned global investors, including Tiger Global, DST, and Flourish Ventures. FairMoney maintains a strong international presence, with offices in several countries, including France, Nigeria, Germany, Latvia, the UK, Türkiye, and India.

In alignment with its vision, FairMoney is actively constructing the foremost mobile banking platform and point-of-sale (POS) solution tailored for emerging markets. The journey began with the introduction of a digital microcredit application exclusively available on Android and iOS devices. Today, FairMoney has significantly expanded its range of services, encompassing a comprehensive suite of financial products, such as current accounts, savings accounts, debit cards, and state-of-the-art POS solutions designed to meet the needs of both merchants and agents.

To gain deeper insights into FairMoney's pivotal role in reshaping Africa's financial landscape, we invite you to watch  informative video.

A highly analytical professional with deep expertise in Expected Credit Loss (ECL) modeling forecasting and collections risk analysis. This role is critical in shaping data-driven recovery strategies by analyzing delinquency trends, risk segmentation, and portfolio performance.

The individual must have a strong understanding of how predictive models work, impact collections strategies, and how to interpret their outputs to optimize recovery efforts.

The individual will be responsible for analyzing risk trends, evaluating collections effectiveness, and providing actionable insights to improve recoveries.

This position requires hands-on experience with SQL, Python (for data analysis), and statistical modeling concepts, as well as a thorough understanding of how underwriting decisions and collections operations impact Expected Credit Loss and overall portfolio risk.

ECL Modeling & Forecasting:

• Analyze and interpret ECL models and forecasts, providing insights into expected recoveries and risk exposure.

• Utilize historical delinquency and recovery data to assess the accuracy of ECL projections and recommend refinements.

• Perform vintage analysis and roll-rate modeling to understand credit deterioration and its impact on collections risk.

• Support stress testing efforts to evaluate portfolio performance under different collections strategies and economic conditions.

• Monitor and assess loss provisioning trends, ensuring alignment between collections strategies and expected recoveries.

Understanding of Predictive Models & Strategy

• Interpret the outputs of propensity-to-pay models and predictive risk models, using insights to refine collections outreach.

• Work closely with data science teams to understand how machine learning models assess collections risk and borrower behavior.

• Leverage model-driven insights to enhance borrower segmentation, call center efficiency, and digital engagement strategies.

• Identify leading indicators of non-repayment, ensuring proactive collections intervention before delinquency worsens.

• Collaborate with strategy teams to refine contact strategies based on predictive insights, improving recovery rates.

Collaboration & Process Improvement:

• Work closely with finance, risk, and collections operations teams to ensure accurate forecasting and risk assessment.

• Provide data-driven recommendations to improve collections efficiency, reduce cost to collect, and enhance customer engagement.

• Develop automated reporting and dashboards for tracking collections KPIs, recovery rates, and delinquency trends.

• Support the Collections Analytics Manager in refining risk models and implementing strategy improvements based on data insights.

• Evaluate and recommend new data sources to improve collections risk analysis and forecasting accuracy.

Key Skills & Qualifications:

A. Experience:

• 3–5 years in consumer lending risk, credit analytics, or data science roles.

• Exposure to at least two stages of the credit lifecycle (e.g., underwriting + portfolio monitoring).

B. Ownership of OKRs:

• Delivery of specific portfolio KPIs (e.g., DPD 30+ %, approval rate uplift, loss ratio reduction).

• A/B test execution and analysis under direction of lead/manager.

C. Previous Work:

• Built and maintained risk monitoring dashboards.

• Supported scorecard development or cut-off changes.

D. Team Size Experience:

• Worked in small-to-medium analytics or risk teams; may have mentored junior analysts.

E. Growth Experience:

• Contributed analytics to launching new products or markets.

F. Technical & Analytical Skills:

• Advanced proficiency in SQL and Python for data extraction, manipulation, and analysis.

• Familiarity with statistical modeling, machine learning outputs, and predictive analytics in a credit risk or collections setting.

• Understanding of vintage analysis, roll-rate modeling, and transition matrices for delinquency risk assessment.

• Experience with Power BI, Tableau, or similar visualization tools to present collections insights effectively.

• Knowledge of IFRS 9 and other credit risk regulatory frameworks affecting ECL calculations.

G. Experience & Risk Management Expertise:

• Strong track record in forecasting delinquency trends and optimizing loss provisioning strategies.

• Experience working with ECL models, understanding their inputs, outputs, and business implications.

• Understanding of underwriting policies and how they influence collections risk and recovery strategies.

• Experience in A/B testing for collections strategy optimization.

• Strong ability to interpret predictive model outputs and apply insights to optimize collections operations.

H. Communication & Stakeholder Engagement:

• Strong ability to translate complex data findings into actionable recommendations for senior leadership.

• Experience working cross-functionally with finance, risk, and collections operations teams.

• Ability to present technical insights in a clear, non-technical manner to business stakeholders.

• Strong written and verbal communication skills to drive alignment on collections risk strategy.

• Private Health Insurance
• Pension Plan
• Training & Development
• Hybrid work
• Paid Time Off

• Screening interview with a Senior Recruiter- 1 hour
• Technical Interview with Hiring Manager- 1 hour
• Business and Final Interview with Chief Risk Officer- 1 hour