Togo built a fully digital, mobile-money cash-transfer system using satellite imagery and phone data to target its poorest citizens during COVID-19, then turned it into a permanent, independently evaluated social-protection platform now scaling to 1.24 million people.
920,000+ people
People reached by Novissi Phase 1 cash transfers (2020–2022)
34 USD million
Total disbursed in Novissi Phase 1 (2020–2022)
154,238 people
Additional beneficiaries reached via AI/satellite targeting (Dec 2020–Apr 2021)
4–21 %
Reduction in exclusion errors vs. geographic targeting
42 %
Improvement in targeting precision
9–35 %
Higher exclusion errors vs. a full social registry
700,000 households
Households targeted under ASTRE's new cash-transfer round (from Dec 2025)
1.24 million people
People targeted for ASTRE by 2029 (by 2029)
Details
Maturity
Scaling
Promoter
Togolese Ministry of Digital Economy and Digital Transformation (with UC Berkeley CEGA and J-PAL)
Period
2020–2026 (ongoing)
Keywords
social protection, cash transfers, artificial intelligence, mobile money, financial inclusion
Context
Togo launched Novissi in April 2020 as one of the world's first fully digital, mobile-money-based social protection programmes, created in response to COVID-19 income shocks among informal workers with no formal safety net. The programme used self-registration by mobile phone and mobile-money delivery to reach over 920,000 people between 2020 and 2022.
Objectives
From September 2020, the Togolese government worked with researchers from UC Berkeley's CEGA and J-PAL to extend the programme into rural areas that lacked prior survey data, aiming to identify and reach the poorest households more precisely than simple geographic targeting could.
Activities
Machine-learning models trained on satellite imagery (roof material, plot size) and mobile-phone metadata (call patterns, mobile-money balances) were used to rank poverty across Togo's 100 poorest cantons, reaching 154,238 additional beneficiaries between December 2020 and April 2021 with $20 a month for three months. Building on this experience, Togo's government subsequently launched ASTRE, a national social-protection programme backed by the World Bank that combines a biometric ID system, an AI-updated dynamic social registry and an interoperable digital payment platform.
Results
A peer-reviewed evaluation (Aiken, Bellue, Blumenstock, Karlan & Udry, published in the Journal of Development Economics and covered by Nature in 2022) found that phone-based targeting cut exclusion errors by 4-21% compared with simple geographic targeting and improved targeting precision by 42%. The same study was explicit about the approach's limits: compared with a full social registry, which Togo did not have, the ML method still produced 9-35% higher exclusion errors, and it could not reach anyone without a mobile phone. A new cash-transfer round under ASTRE launched in December 2025, delivering CFAF 25,000 to a first wave within a programme targeting 700,000 households, with plans to reach 1.24 million people by 2029.
Conclusions
World Bank monitoring in 2025 noted a slower-than-planned rollout of ASTRE's Programme Coordination Unit and Independent Verification Agent, though a new government appointed in October 2025 was expected to accelerate delivery — illustrating that institutionalising an emergency digital-cash innovation into permanent infrastructure remains a work in progress.
Implementation
Implementation detail (cost, timeline, staffing, conditions for success) is not yet available for this practice.
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Data sources
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