Facts and figures tell us the story of financial inclusion, and give us information we need to understand how far we’ve come and what more needs to be done. Demand-side datasets, such as the World Bank’s Global Findex, provide information on customers and how they behave, while supply-side datasets, such as the IMF’s Financial Access Survey, provide information on financial service providers and what they offer. 

Data comes in all shapes and sizes, and there are now more data and types of data available than ever before. With the proliferation of digital devices, apps and mobile services, people’s digital footprints have grown exponentially, creating large amounts of electronic data referred to as big data. As the volume and the complexity of data increases, powerful computing tools and algorithms are needed to analyze and interpret it. Data can help financial service providers to develop services tailored to client needs, acquire new clients, facilitate cross-selling activities, and lower their operating costs. But increasing data collection can also bring with it greater risks, including privacy and security challenges that microfinance institutions and other financial service providers need to be equipped to manage. 

What can you find in this Topic Hub?

Curated by FinDev editors, this Topic Hub offers you access to key resources contributed by organizations around the world who work on the topic of data for financial inclusion and microfinance. Our latest blogs and publications on this topic are featured here (in the Resources Tab above), and you can find a collection of papers, case studies and guides to explore further. When there are upcoming webinars, events and recent news on this topic, they will be featured in the Topic Hub as well, so make sure to come back regularly for the latest on this topic. Finally, we’ve selected some key additional resources, which are listed on the right here, where you can learn even more about this topic.

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Slide Deck

This slide deck presents research findings identifying good practices of responsible agents in safeguarding their customers’ data and the role that providers can play in promoting these practices.


This Note describes some of the uses of artificial intelligence and machine learning by financial institutions; considers the supervisory responses to such uses; and highlights some ways in which supervisory authorities can themselves use AI and ML to improve the effectiveness and efficiency of supervision.


This edition of the Global Findex database contains updated indicators on access to and use of formal and informal financial services and digital payments, and offers insights into the behaviors that enable financial resilience.

News & Events

The latest news and upcoming events and training from the global financial inclusion community on this topic.