This case study examines the data and experience of two fintechs in India that use different sets of transactional data for credit scoring.

The information in this detailed analysis showcases the remarkable resilience of the microfinance sector across multiple regions.

This guide introduces a gender-lens analytical framework for lenders to determine whether lending decisions and outcomes in their portfolios differ by gender and, if so, how.

This publication shares key learnings from case studies from Guatemala and Bosnia and Herzegovina and illustrates their contribution to co-designing an impact monitoring system for Sweden’s guarantee instrument.

This is the first time that a rating agency specializing in microfinance has been authorized in Panama to rate regulated financial institutions in the country.

This study is part of a market monitoring exercise to understand the range of risks and how they are perceived by multiple stakeholders in the Indian fintech lending sector.

As small businesses go digital, platform data can help MFIs better serve them, contributing to a healthier, more sustainable and more inclusive lending model.

DreamStart Labs explores how to incorporate member-driven assessments into credit scoring through their app.

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 special report elaborates on policy considerations for the implementation of a credit guarantee scheme that can be used to support green lending by financial institutions (such as commercial banks, credit cooperatives or microfinance institutions) to MSMEs.