Togo has emerged as a model for how governments can use digital tools to provide their citizens with better access to public services, including cash aid.
A shining example was how during the COVID-19 pandemic, the country’s Novissi emergency cash transfer program used machine learning to analyze call records and satellite imagery in order to prioritize assistance for the lowest-income people and send money to their mobile phones.
Togo has since distributed $34 million to 920,000 people, or 25% of its adult population. Now, with $100 million from the World Bank, the government is building on what it learned from Novissi to expand its social safety net program. The goal is to send cash transfers to the 1.8 million people living in extreme poverty in the country.
About the author
Catherine Cheneycatherinecheney
Catherine Cheney is the Senior Editor for Special Coverage at Devex. She leads the editorial vision of Devex’s news events and editorial coverage of key moments on the global development calendar. Catherine joined Devex as a reporter, focusing on technology and innovation in making progress on the Sustainable Development Goals. Prior to joining Devex, Catherine earned her bachelor’s and master’s degrees from Yale University, and worked as a web producer for POLITICO, a reporter for World Politics Review, and special projects editor at NationSwell. She has reported domestically and internationally for outlets including The Atlantic and the Washington Post. Catherine also works for the Solutions Journalism Network, a non profit organization that supports journalists and news organizations to report on responses to problems.
