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Method of Application
Latest Jobs at FairMoney
Senior Accountant
- Job Type Full Time
- Qualification BA/BSc/HND
- Experience 5 years
- Location Lagos
- Job Field Finance / Accounting / Audit 
Job Summary
- The Finance department at FairMoney is a key component in this mission to provide banking services to all consumers across emerging markets.
- Finance drives the reporting, the strategic analysis and the financial operations to make FairMoney’s mission possible. We are currently looking for a senior accountant:
Key Responsibilities
Monthly Management Reporting:
- Review monthly management report prepared by accountants and sign off.
- Ensure there are relevant schedules supporting the items on the financial statement
- Investigate and explain variances
Taxation:
- Update tax policies as may be required
- Ensure PAYE, Pension, WHT and VAT are appropriately deducted and remitted
- Manage the current income and deferred tax computation with the support of consultants
- Carry out tax planning and arrange transaction to ensure tax burden is optimized
- Manage tax audits and desk reviews with the support of consultant
- Ensure annual and monthly filings are done on or before due dates
Finance Operation:
- Carry out cash planning to ensure that expenses and obligations are met as at when needed
- Ensure excess cash are passed to the Treasurer for investment
- Update Standard Operating Procedures (SOP) and accounting policy manuals as may be required
- Manage the transaction processing team and ensure transactions are treated timely.
Year End Close/Statutory Audits:
- Support year end close and annual statutory audit.
Requirements
- Bachelor’s degree in finance, accounting, or a related field.
- ACCA or ICAN professional certification is an added advantage
- Have an advanced Microsoft Excel Skills
- Have a minimum of five (5) years of experience in audit or financial service industry
- Strong experience in tax practice will be an added advantage
- Be an effective team player with a positive attitude
- Must be able to work without supervision.
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Method of Application
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.
Requirements
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.
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.
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.
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.
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