How will the evolving global macroeconomic situation impact the microfinance sector in emerging markets? Financial inclusion consultant Erik Geurts shared his thoughts on a recent Let's Talk Microfinance podcast. 

The use of artificial intelligence and machine learning in the financial sector is spreading exponentially across advanced and emerging economies. What are the risks and opportunities presented by these innovations?

This Special Report identifies inclusive green finance (IGF) as a subset of sustainable finance, shows that a successful IGF framework rests on six building blocks, and identifies five policy tools that further the framework.

This reading deck for policy makers shows how rural Cash-in/Cash-out (CICO) agent network expansion is key to ensuring poor people can capture the benefits of digital financial ecosystems and presents a set of policies that have been effective in enabling rural CICO in a way that benefits vulnerable segments.

This reading deck for regulators shows how expanding rural Cash-in/Cash-out (CICO) agent networks is key to ensuring more inclusive digital financial systems, illustrates industry innovations that are making rural CICO more viable and presents a set of regulatory considerations that can enable such innovations within a stable financial system. 

This special report on central bank digital currencies (CBDC) and financial inclusion looks at the current state of financial inclusion across different developing and emerging economies, and identifies the main use cases CBDC can contribute to.

This report shows how digital payment platforms, digital financial products, and enabling policies can make a difference in helping the most vulnerable populations adapt to and mitigate climate risk and environmental degradation.

This paper synthesizes desk research and in-depth discussions with consumer advisory panel representatives around the world.

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.