Monitoring Agent Performance for a Mobile Money Operator

MASAE Analytics supported a mobile money operator in building monitoring dashboards to track agent performance. The project aimed to help the operator grow its business, reach new customers, and optimise its network by providing the right incentives and monitoring tools for agents.

Why This Matters

A robust agent network is critical for the success of mobile money services, particularly in underserved regions. Effective performance monitoring enables operators to identify high-performing agents, address challenges, and ensure reliable service delivery for customers.

Our Approach

  • Data Science:
    Analysed transaction and agent data to identify trends, opportunities, and areas for improvement.

  • Dashboards:
    Developed interactive dashboards for real-time performance tracking and decision support.

  • Strategic Advisory:
    Provided recommendations on incentive structures and network optimisation.

Results and Impact

The dashboards empowered the operator to make data-driven decisions, enhance agent productivity, and expand financial inclusion through improved service delivery.

In 2017, MASAE Analytics, in partnership with Altai, was contracted by UNDP to operationalise the Fragility Index Maturation Model in Jubaland, Somalia. The goal was to model how macro-economic parameters influence socio-economic outcomes and to quantify the impact of interventions in fragile contexts.

In 2017, MASAE Analytics, in partnership with Altai, was contracted by UNDP to operationalise the Fragility Index Maturation Model in Jubaland, Somalia. The goal was to model how macro-economic parameters influence socio-economic outcomes and to quantify the impact of interventions in fragile contexts.

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MASAE Analytics was engaged to develop a geographic sampling frame for a large-scale community survey in Ethiopia, focusing on rural and host communities around 10 refugee camps across four regions. The project utilised remote sensing and data science to remotely sample 900 dwellings, ensuring representative and efficient data collection.