How can data and data-driven technologies impact financial inclusion efforts in Africa?

As the region with the most unbanked and underserved citizens, combined with a growing mobile penetration rate and emerging digital identity (DigiID) systems — sub-Saharan Africa (SSA) could prove fertile ground for beneficial data-driven technologies that facilitate digital financial inclusion. While accumulation and production of data alone has limited value, application of data-driven digital technologies such as artificial intelligence (AI) and data analytics (aggregating, combining, repurposing, developing insights, etc.) can spur data use activities that create value from data and contribute to addressing factors that exacerbate current exclusions from financial systems.

However, rising datafication is not without risk, emerging evidence reveals that data-driven AI algorithms can also contribute to discrimination and financial exclusion. Furthermore, the continent also faces limited availability of good quality machine-readable data, inadequate foundational data infrastructure, data systems with weak governance and interoperability, and low AI (data science) related talent, which hinder the ability to create innovative and contextually relevant financial service solutions that have potential to meet the needs of the most marginalized.

The session focused on three overarching questions:  

• What enablers (prerequisites) and safeguards are required for responsible data use and deployment of beneficial AI in African financial services ecosystems?
• What are the examples of data use cases that demonstrate positive outcomes in terms of deepening financial inclusion in nascent data-driven African digital economies?
• What are the risks, harms, and opportunities that arise from using data and data-driven technologies in the context of financial inclusion?