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About the Organisation
Senior Collections Risk Analyst job at FairMoney | Apply Now
Kampala, Uganda
Fair Money is a leading digital financial institution committed to providing accessible, fast, and reliable financial services, including loans, payments, and banking solutions, to underserved individuals and businesses. Recognized for its innovation and customer-centric approach, Fair Money has built a strong reputation as a trusted fintech company, leveraging technology to bridge financial gaps and promote financial inclusion.
With a dynamic and inclusive work culture, the company offers employees a collaborative environment, professional growth opportunities, and competitive benefits, fostering innovation and excellence. Fair Money provides diverse job opportunities in fintech, engineering, customer service, risk management, and product development, with flexible work arrangements to support work-life balance. Since its inception in 2017, Fair Money has evolved from a digital lending platform into a full-fledged financial services provider, continuously innovating through artificial intelligence, data analytics, and mobile banking to enhance user experience and financial accessibility.
Operating across multiple regions, the company serves millions of customers, expanding its reach and impact in emerging markets. Rooted in core values of transparency, innovation, customer focus, and financial empowerment, Fair Money is committed to corporate social responsibility through financial literacy programs, community engagement initiatives, and support for small businesses. By revolutionizing digital finance, Fair Money continues to drive economic growth and financial well-being. For more information, visit their official website at www.fairmoney.io.
Are you looking for Finance jobs in Uganda 2025 today? then you might be interested in Senior Collections Risk Analyst job at FairMoney
Full Time
Deadline:
31 May 2025
Job Title
Senior Collections Risk Analyst job at FairMoney
FairMoney
Job Description
This role requires an analytical professional with expertise in ECL modeling, collections risk analysis, and predictive model interpretation. The analyst will analyze delinquency trends, forecast credit losses, evaluate collections effectiveness, and provide actionable insights to enhance recovery efforts. They will collaborate with data science, finance, risk, and collections teams to refine risk models, design experiments, and develop automated reporting tools. Proficiency in SQL, Python, statistical modeling, and visualization tools is essential, alongside a strong understanding of underwriting impacts on collections risk.
Duties, Roles and Responsibilities
Qualifications, Education and Competencies
See all details of the qualifications, competencies and education for this role under the "How to Apply" section below.
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How to Apply
Analyze and interpret ECL models and forecasts to assess expected recoveries and risk exposure.
Conduct vintage analysis, roll-rate modeling, and stress testing to evaluate portfolio performance.
Monitor loss provisioning trends and align collections strategies accordingly.
Analyze cohort performance and borrower segmentation to optimize collections approaches.
Evaluate the impact of underwriting decisions on recovery outcomes.
Design and execute A/B tests on collections strategies for continuous improvement.
Interpret predictive model outputs and leverage machine learning insights for better collections targeting.
Develop automated dashboards and reporting tools for tracking KPIs and trends.
Collaborate cross-functionally with finance, risk, and operations teams to improve forecasting accuracy and reduce collection costs.
Recommend new data sources to enhance risk analysis and forecasting precision.
SERVICES
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RESIDENTIAL
Bachelor’s degree or higher in a relevant field.
3+ years experience in collections analytics, credit risk, or a data-driven risk role.
Advanced skills in SQL and Python for data analysis and manipulation.
Deep knowledge of Expected Credit Loss (ECL) modeling, loss forecasting, and IFRS 9 regulatory framework.
Experience with statistical modeling, vintage analysis, roll-rate models, and predictive analytics.
Familiarity with data visualization tools such as Power BI or Tableau.
Strong ability to translate technical insights into clear recommendations for non-technical stakeholders.
Excellent communication and stakeholder management skills.
Proven track record in optimizing collections strategies and forecasting delinquency trends.
Ability to work effectively in a fast-paced, evolving environment with a proactive and results-driven mindset.
