This publication provides insights into micro, small and medium enterprises’ access to funding through the alternative finance industry in Latin America based on 540 survey responses from MSMEs in the region.
This report draws upon data from the portfolios of 17 financial institutions to share market insights and reflections on 10 years of practitioner collaboration.
This learning brief summarizes the challenges, opportunities, and responses of agri-SMEs, financiers and development partners to the current food crisis.
Banking in Layers: Five Cases to Illustrate How the Market Structure for Financial Services is Evolving
Exploring the market-level modularization of financial services through case studies featuring new models that are emerging, how they are coming about, and what they mean for the financial inclusion of low-income people in emerging markets and developing economies.
Leveraging Digital ID and e-KYC for the Financial Inclusion of Forcibly Displaced Persons: Risks and Opportunities
This report discusses the challenges and bottlenecks preventing the wider adoption of digital ID and e-KYC to advance the financial inclusion of forcibly displaced persons in Rwanda, Mauritania, and Eswatini.
This slide deck presents the findings of research estimating the size of the medium and small enterprise and low-income credit markets in Kenya and to assess the potential of fintech firms to meet the needs of those markets.
This Focus Note advocates the importance of a segmented approach to addressing micro and small enterprises (MSE) needs and focuses on MSEs with up to 20 employees.
Strategies to Optimize MSME-Centered Supply Chain Finance Solutions: A Study of Ghana, Ethiopia, and Nigeria
Given the urgency of digital transformation to build an inclusive recovery, this paper provides timely insights into how to enable supply chain finance models in three African countries.
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.