Billions of people worldwide experience poverty, leaving them vulnerable to shocks and crises.
When emergencies occur, a lack of timely information on where affected people live and their needs can slow the delivery of support.
This can delay emergency cash assistance reaching those who need it most, even when resources are ready.
Flowminder develops new methods using big data and pseudonymised mobile operator data for poverty modelling as well as remote cash transfer programming
Banner visual: WFP/Moses Sawasawa
Case studies
Pilot study: Poverty modelling in Ghana
Coming soon
Remote cash transfer programming in DRC
Read about our collaboration with GiveDirectly, where our remote cash transfer programming using mobile operator data offers promising path for delivery of humanitarian assistance