FairMoney seeks a Senior Credit Risk Analyst to join our team. In this role, you will leverage your deep expertise in Expected Credit Loss (ECL) modeling and collections risk analysis to shape data-driven recovery strategies. You will be critical in analyzing delinquency trends, risk segmentation, and portfolio performance to drive strategic decisions.
What You'll Do
- 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.
- Interpret the outputs of propensity-to-pay 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.
- 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.
What We're Looking For
- 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).
- 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.
- 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.
- 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.
Nice to Have
- Contributed analytics to launching new products or markets.
- Worked in small-to-medium analytics or risk teams; may have mentored junior analysts.
Technical Stack
- SQL
- Python
- Power BI
- Tableau
Team & Environment
You will join a small-to-medium analytics or risk team and report directly to the Collections Analytics Manager.
Benefits & Compensation
- Private Health Insurance
- Pension Plan
- Training & Development
- Hybrid work
- Paid Time Off
Work Mode
This position operates on a hybrid work model.
FairMoney is an equal opportunity employer.
