Lead Risk Manager

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.

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 this informative video.

The ideal candidate for this role will be a highly skilled and strategic individual who can oversee the credit lifecycle, develop analytics and strategies for optimizing recovery rates, and effectively manage a team. They will combine deep analytical capabilities with a strong understanding of ECL (Expected Credit Loss) modeling, cohort analysis, and risk operations. The role requires a balance of high-level strategic thinking and the ability to dive deep into the math and execution of data-driven decisions. The person must have experience managing people and optimizing the credit processes, while ensuring effective communication across various departments (e.g., call centers, underwriting, collections). This individual must think like a systems engineer to isolate variables impacting recovery performance and create actionable solutions.

A. Analytics and Strategy Development:

• Lead the analytics and strategy for optimizing credit processes across the unsecured lending portfolio
• Develop, maintain, and refine ECL models (Expected Credit Loss) to predict and optimize recovery rates
• Use cohort analysis and book analysis to assess performance, measure recovery effectiveness, and adjust strategy based on trends
• Drive A/B testing, test-learn-iterate approaches to improve credit strategies, optimizing both short-term recovery and long-term customer relationships
• Understand how different data dimensions affect each other and synthesize findings to create actionable insights.
  

B. Modeling & Data Analytics:

• Perform data extraction and analysis (SQL, Python, or other analytics tools) to monitor credit performance, ensuring accuracy and completeness in reporting
• Build sophisticated models to isolate recovery rates impacted by underwriting decisions vs. credit efforts
• Conduct in-depth analyses to understand portfolio behavior and segment customers based on recovery likelihood and repayment capacity
• Evaluate the relationship between credit underwriting decisions and recovery performance, identifying areas for improvement in both functions.
  

C. Team Management & Optimization:

• Manage a cross-functional team of analysts and credit specialists, ensuring they have the tools, training, and support to optimize performance
• Continuously refine and enhance the recovery rates across different segments, ensuring alignment between underwriting, credit, and customer service
• Work closely with the call center teams, providing guidance on the tonality of calls, communication approaches, and overall strategy for handling credit
• Develop and track key performance metrics for the team, providing regular feedback and leading initiatives to improve operational efficiency.
  

D. Strategic Oversight & Process Improvement:

• Ensure the credit strategy aligns with broader business goals, focusing on profitability, risk management, and customer experience
• Manage and optimize the entire credit lifecycle, from initial outreach through final resolution, while balancing risk and customer satisfaction
• Implement innovative strategies to improve recovery rates, considering customer segmentation, call center strategies, and credit tools.
  

E. Collaboration & Stakeholder Communication:

• Collaborate closely with key internal stakeholders, such as the underwriting team, data science teams, marketing, and senior leadership, to refine the credit strategy and align on business objectives
• Effectively communicate insights and recommendations to senior leadership, including reports on performance, improvements, and optimizations
• Advocate for a test-learn-iterate mindset across departments to drive data-informed decisions that continuously improve credit outcomes

A. Experience & Management:

• 7-10 years in credit risk management; must have worked as Senior Analyst or Portfolio Manager before
• Strong exposure to policy setting and portfolio optimisation

B. Ownership of OKRs:

• Direct responsibility for ECL and GP targets for their portfolio/product
• Accountable for growth vs. loss trade-offs in policy decisions
• Unit economics - NPV/IRR/Surplus calculations model knowledge a must

C. Previous Work:

• Designed and implemented credit policies
• Led cross-functional A/B testing initiatives with product/data teams
• Managed multiple credit products or channels

D. Team Size Experience:

• Led 2-5 analysts directly
• Experience hiring, training, and performance managing analysts

E. Growth Experience:

• Proven track record in scaling portfolios profitably — can show before/after metrics

F. Advanced Analytical Skills:

• Proficiency in SQL, Python, or similar data extraction and manipulation tools for handling large datasets
• Strong experience with statistical modeling and analytics tools to develop and improve ECL models and optimize recovery strategies
• Expertise in cohort analysis, book analysis, and segmentation strategies, understanding the nuances between these approaches and their impact on recovery performance
• Ability to apply predictive analytics and build actionable strategies to improve key KPIs, including recovery rates, aging of debt, and delinquency rates

C. Understanding of Recovery and Underwriting:

• A deep understanding of the relationship between underwriting decisions and credit performance, and how those impact the recovery process
• Ability to isolate and quantify the effects of underwriting vs. credit strategies on performance, using data to drive improvements in both areas
• Experience optimizing recovery strategies across different segments of a consumer loan portfolio

D. Strategic Thinking with Tactical Execution:

• Ability to think strategically about credit while being hands-on in analyzing the data and understanding the granular details (SQL queries, statistical models)
• Demonstrated success in test-learn-iterate approaches, where strategies are continuously optimized based on rigorous data testing and insights

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

• Screening call with Senior Recruiter
• Technical Interview
• Business interview with the Chief Risk Officer
• Final Interview with Global CEO