TGO-002

CNSS “Biosecu” – online facial-recognition proof-of-life for pensioners

Download PDF
Togo Sub-Saharan Africa Low income Full Production Deployment Confirmed

Caisse Nationale de Sécurité Sociale (CNSS).

At a Glance

What it does Perception and extraction from unstructured inputs — Identification, verification and record linkage
Who runs it Caisse Nationale de Sécurité Sociale (CNSS).
Programme CNSS “Biosecu” – online facial-recognition proof-of-life for pensioners
Confidence Confirmed
Deployment Status Full Production Deployment
Key Risks Not assessed
Key Outcomes Enables remote proof-of-life for residents and diaspora; streamlines administration (official rationale; no quantified efficiency study published).
Source Quality 3 sources — Government website / press release, News article / media

The Caisse Nationale de Sécurité Sociale (CNSS) of Togo launched Biosecu, a web-based application that uses facial recognition technology to verify the physical existence of pensioners and annuitants — a process known as 'contrôle de vie' (proof of life). According to the official République Togolaise government portal, the CNSS introduced Biosecu as an innovation to facilitate administrative procedures for beneficiaries residing both within Togo and abroad, enabling them to complete the proof-of-life verification remotely using facial recognition technology rather than appearing in person.

The facial recognition system works by comparing a beneficiary's face, captured via the web application, against the biometric photograph held in the CNSS Togo database. As the CNSS explained, 'facial recognition allows us to confirm that your face perfectly matches the picture available in CNSS Togo's biometric database' (Togo First, 2023). The system is designed both to streamline the verification process for beneficiaries and to combat fraud by ensuring that only living, verified individuals continue to receive pension and annuity payments (We Are Tech Africa, 2022).

Prior to the introduction of Biosecu, pensioners and annuitants were required to physically present themselves at CNSS agencies twice a year to confirm their identity before receiving their payments (Togo First, 2023). This in-person verification requirement was suspended in 2020 in compliance with the restrictive barrier measures enacted by the Togolese government to contain the spread of Covid-19. The verification process subsequently resumed from 16 August 2022, with the first campaign running until 31 December 2022 for the payment of pensions and annuities for the first half of 2023.

The CNSS Director General, Ingrid Awade, issued a statement confirming the enforcement mechanism accompanying the system: 'Payment of dues to beneficiaries who will not perform the said operation will be suspended from January 1, 2023, in accordance with the regulatory provisions of the Social Security Code' (Togo First, 2023). This enforcement provision means that non-completion of the facial recognition-based proof-of-life verification directly results in the suspension of benefit payments, making the system a high-stakes automated process for beneficiaries.

Biosecu operates at a national scale, serving all CNSS pensioners and annuitants both within Togo and in the Togolese diaspora abroad. The system allows non-resident beneficiaries to complete the mandatory verification remotely, eliminating the need to travel to Togo or visit CNSS agencies in person (We Are Tech Africa, 2022; Togo First, 2023).

The launch of Biosecu is described as part of a broader digitalization programme undertaken by the CNSS. The institution is noted as a pioneer of digitalization in Togo, having been the first Togolese institution to adopt e-declaration (télédéclaration) and e-payment (télépaiement) systems (We Are Tech Africa, 2022; Togo First, 2023; République Togolaise, 2022). The facial recognition application represents a further extension of these digital reforms to the pension administration process, specifically targeting the verification step that ensures only living beneficiaries continue to receive payments.

No details are provided in the downloaded sources regarding the specific technology vendor, the underlying facial recognition algorithm, the hosting infrastructure, or the data protection measures in place. The sources also do not describe any manual review process, appeals mechanism, or human oversight protocol specific to cases where the facial recognition verification fails or produces inconclusive results. The absence of documented safeguards is notable given the high-stakes nature of the system, where verification failure leads directly to benefit suspension.

Classifications follow the DCI AI Hub Taxonomy. Hover over field labels for definitions.

Social Protection Functions

Implementation/delivery chain
Assessment of needs/conditions + enrolment primary
SP Pillar (Primary) The social protection branch: social assistance, social insurance, or labour market programmes. Social insurance
Programme Name CNSS “Biosecu” – online facial-recognition proof-of-life for pensioners
Programme Type The type of social protection programme, classified under social assistance, social insurance, or labour market programmes. View in glossary Old age, survivors and disability pensions
System Level Where in the social protection system the AI is applied: policy level, programme design, or implementation/delivery chain. View in glossary Implementation/delivery chain
Programme Description CNSS Biosecu is the proof-of-life verification system for the Caisse Nationale de Sécurité Sociale pension and annuity programme in Togo. It enables remote facial recognition-based verification for pensioners and annuitants to maintain their benefit payments.
Implementation Type How the AI output is produced: Classical ML, Deep learning, Foundation model, or Hybrid. Affects validation, compute requirements, and governance profile. View in glossary Deep learning
Lifecycle Stage Current stage in the AI lifecycle, from problem identification through to monitoring, maintenance and decommissioning. View in glossary Monitoring, Maintenance and Decommissioning
Model Provenance Origin of the AI model: developed in-house, adapted from open-source, commercial/proprietary, or accessed via third-party API. View in glossary Not documented
Compute Environment Where the AI system runs: on-premise, government cloud, commercial cloud, or edge/device. View in glossary Not documented
Sovereignty Quadrant Classification of data and compute sovereignty: I (Sovereign), II (Federated/Hybrid), III (Cloud with safeguards), or IV (Shared Innovation Zone). View in glossary Not assessed
Data Residency Where the data used by the AI system is stored: domestic, regional, or international. View in glossary Not documented
Cross-Border Transfer Whether data crosses national borders, and if so, whether documented safeguards are in place. View in glossary Not documented
Decision Criticality The rights impact of the decision the AI supports. High criticality requires HITL oversight; moderate requires HOTL; low may operate HOOTL. View in glossary High
Human Oversight Type Level of human involvement: Human-in-the-Loop (active review), Human-on-the-Loop (monitoring), or Human-out-of-the-Loop (periodic audit). View in glossary HOTL
Development Process Whether the AI system was developed fully in-house, through a mix of in-house and third-party, or fully by an external provider. View in glossary Not documented
Highest Risk Category The most significant structural risk source identified: data, model, operational, governance, or market/sovereignty risks. View in glossary Not assessed
Risk Assessment Status Whether a formal risk assessment, informal assessment, or independent audit has been conducted for this system. Not assessed

Risk Dimensions

Governance and institutional oversight risks
Market, sovereignty and industry structure risks
Operational and system integration risks

Impact Dimensions

Autonomy, human dignity and due process
Privacy and data security
Systemic and societal
CategorySensitivityCross-System LinkageAvailabilityKey Constraints
Beneficiary registries and MISSpecial categoryLinks data across multiple systemsCurrently available and usedCNSS pension registry containing beneficiary identity records; facial biometric match determines continued payment eligibility.
National ID and biometric databasesSpecial categoryLinks data across multiple systemsCurrently available and usedFacial biometric captured via web/mobile camera compared against stored biometric photograph in CNSS database; requires adequate camera quality and internet connectivity for remote verification.

République Togolaise (2022). La CNSS lance Biosécu, un système de reconnaissance faciale pour le contrôle de vie. Lomé: Portail Officiel du Togo. Available at: https://www.republiquetogolaise.com/services-publics/2208-7175-la-cnss-lance-biosecu-un-systeme-de-reconnaissance-faciale-pour-le-controle-de-vie (Accessed 23 Mar 2026).

View source Government website / press release

Togo First (2023). Togo: Social security fund launches app to help pensioners and annuitants get their dues more easily. Lomé: Togo First. Available at: https://www.togofirst.com/en/public-services/2308-10466-togo-social-security-fund-launches-app-to-help-pensioners-and-annuitants-get-their-dues-more-easily (Accessed 23 Mar 2026).

View source News article / media

We Are Tech Africa (2022). Togo: CNSS launches facial recognition platform to confirm beneficiaries' identities remotely. We Are Tech Africa. Available at: https://www.wearetech.africa/en/fils-uk/news/tech/togo-cnss-launches-facial-recognition-platform-to-confirm-beneficiaries-identities-remotely (Accessed 23 Mar 2026).

View source News article / media
Deployment Status How far the system has progressed into real-world operational use, from concept/exploration through to scaled and institutionalised. View in glossary Full Production Deployment
Year Initiated The year the AI system was first initiated or development began. 2022
Scale / Coverage The scale and geographic or population coverage of the deployment. National — all CNSS pensioners and annuitants in Togo and diaspora
Funding Source The source(s) of funding for the AI system development and deployment. Unknown
Technical Partners External technology vendors, academic partners, or development partners involved. Unverified – no primary source naming provider/stack.
Outcomes / Results Enables remote proof-of-life for residents and diaspora; streamlines administration (official rationale; no quantified efficiency study published).

How to Cite

DCI AI Hub (2026). 'CNSS “Biosecu” – online facial-recognition proof-of-life for pensioners', AI Hub AI Tracker, case TGO-002. Digital Convergence Initiative. Available at: https://socialprotectionai.org/use-case/TGO-002 [Accessed: 1 April 2026].

Change History

Updated 31 Mar 2026, 06:35
by system (system)
Created 30 Mar 2026, 08:41
by v2-import (import)