The Central Bank of Brazil has launched the Geotec project, a capacity-building programme that attracted more than 5,300 registrations and is designed to strengthen monitoring and supervision of rural credit operations and the Agricultural Activity Guarantee Programme (Proagro) through the use of geotechnologies and satellite imagery. The initiative is funded via Germany–Brazil Cooperation through a partnership with Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) under the Brazilian Sustainable Finance Project (Fibras II). The programme focuses on systematic use of remote sensing and cross-checking financial, cadastral and territorial databases to continuously assess productive conditions, land use and territorial compliance, reducing reliance on formal declarations and ad hoc inspections and supporting a more accurate view of risks and potential defaults. The central bank also framed the project as a way to build capacity across oversight and control bodies and within the central bank’s own rural credit supervision teams, while improving financial institutions’ efficiency in monitoring and oversight. The official opening at the central bank’s headquarters included 65 representatives from ministries and agencies responsible for agricultural and environmental policies, the Federal Police and directors from major rural credit lenders, alongside an inaugural lecture delivered by the head of the central bank’s rural credit and Proagro regulatory and supervisory department.
Central Bank of Brazil 2026-02-11
Central Bank of Brazil launches Geotec project to train stakeholders in satellite and geospatial tools for rural credit and Proagro oversight
The Central Bank of Brazil launched the Geotec project, funded by Germany–Brazil Cooperation, to enhance monitoring of rural credit operations and the Agricultural Activity Guarantee Programme using geotechnologies and satellite imagery. It aims to improve risk assessment and oversight efficiency by employing remote sensing and cross-referencing financial and territorial data.