The World Bank has introduced an AI-powered model designed to predict refugee arrivals four to six months in advance. This initiative aims to help governments transition from reactive measures to anticipatory responses, potentially improving relations between host communities and refugees and enhancing public service delivery.
This model considers over 90 variables, including conflict, economic shifts, climate data, and language used in news and social media. It allows for early actions such as building infrastructure like water points, expanding health facilities, and constructing classrooms before the arrival of refugees.
According to the World Bank, "Every year, millions flee their homes due to conflict, climate change, or other crises. When refugees arrive in large numbers, host communities struggle as basic public services—health, education, and water—are overstretched."
The tool supports the Displacement Crisis Response Mechanism (DCRM), which is described as "the world’s first displacement risk financing mechanism." In Uganda, where the model was tested using data from 2014 to 2023 regarding refugees from South Sudan and the DRC, it demonstrated high predictive accuracy by identifying key drivers such as conflict and economic activity.
When Ugandan services faced increased pressure due to refugee inflows, the DCRM was activated. Funds were allocated to scale up services like water access and health center capacity. The World Bank noted that by increasing public service availability, tensions between refugee and host communities can be reduced.
Looking forward, the model could also be adapted for other development challenges such as poverty levels or macro-fiscal pressures. The World Bank sees potential for this tool in better targeting operations and managing displacement by identifying factors driving changes in refugee flows.