Fraud Data Analyst

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.

FairMoney thrives on its diverse workforce, bringing together talent from over 27 nationalities. This multicultural team drives the company’s mission of reshaping financial services for underserved communities.

To gain deeper insights into FairMoney’s pivotal role in reshaping Africa’s financial landscape, we invite you to watch an informative video.

• Fraud Detection & Analysis
  • Identify emerging fraud trends, patterns, and attack vectors through data analysis.
    
• Data Analytics & Reporting
  • Build and maintain dashboards and reports to track fraud metrics (fraud rate, false positive rate, detection rate, etc.).
  • Analyze large datasets to identify anomalies and potential fraud indicators.
  • Generate regular and ad-hoc reports for stakeholders on fraud trends and performance.
  • Develop KPIs and metrics to measure the effectiveness of fraud prevention strategies.
    
• Rule & Model Development
  • Design and implement fraud detection rules and business logic.
  • Collaborate with data science teams to develop and refine machine learning models for fraud detection.
  • Continuously optimize fraud rules to balance fraud prevention and customer experience.
    
• Cross-functional Collaboration
  • Work closely with Product, Engineering, Operations, and Customer Support teams.
  • Provide fraud insights to inform product development and feature enhancements.
  • Support the implementation of new fraud prevention tools and technologies.