Senior Collections Risk Analyst at Fairmoney Microfinance Bank

FairMoney is the leading digital lending platform in Nigeria. In 2020, we disbursed 40% more than the next competitor. We have continued to scale quickly and prudently culminating in our closing of our $42 million Series B Equity round.Due to our growth, we are scaling our Capital Markets team to further drive an ambitious local currency debt fundraising program. You will be joining an innovative and ambitious team that recently closed a Fintech Private Note with leading investment banks acting as Arrangers to the offer. We have plans to continue to offer debt investors a range of innovative solutions to enable them to provide FairMoney, a fast-growing yet prudent fintech with debt funds. This is where you come in.

We are recruiting to fill the position below:

Job Title: Senior Collections Risk Analyst

Location: Lagos

About the role

• 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.

Responsibilities
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.

Collections Performance Analytics & Risk Segmentation:

• Analyze cohort performance, delinquency trends, and borrower segmentation to optimize collections strategies.
• Evaluate the effectiveness of existing collections treatment paths, identifying areas for improvement.
• Assess the impact of credit underwriting decisions on collections outcomes, ensuring alignment between risk assessment and recovery strategies.
• Support the design and execution of A/B testing for different collections approaches, using data to recommend optimal strategies.
• Monitor roll rates and transition matrices to detect early signs of delinquency risk and recommend intervention strategies.

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
Technical & Analytical Skills:

• Advanced proficiency in SQL and Python for data extraction, manipulation, and analysis.
• Strong expertise in Expected Credit Loss (ECL) modeling, loss forecasting, and provisioning calculations.
• 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.

Experience & Risk Management Expertise

• 3+ years of experience in collections analytics, credit risk, or a related data-driven role.
• 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.

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.

Desired Traits:

• Highly Analytical: Strong problem-solving skills with the ability to break down complex data into actionable insights.
• Detail-Oriented: Ensures accuracy in reporting and forecasting to minimize risk exposure.
• Proactive: Continuously seeks ways to improve ECL forecasting, risk segmentation, and collections efficiency.
• Results-Driven: Focused on optimizing recovery rates and minimizing losses through data-driven strategy execution.
• Adaptable: Thrives in a fast-paced, dynamic environment where collections and risk strategies evolve rapidly.

Benefits

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

Application Closing Date
Not Specified.

How to Apply
Interested and qualified candidates should:
Click here to apply online