India's DoT disconnects over 82 lakh connections flagged by ASTR

AI system

System: ASTR, AI and facial recognition powered Solution for Telecom SIM Subscriber Verification
Model: Not assessed
Release: Not assessed
Application developer: Department of Telecommunications, Government of India
Role: Not assessed
Configuration: Not assessed
Inputs and outputs: Not assessed
Autonomy: Not assessed
Workflow: Subscriber KYC photographs held by operators, matched across names by facial recognition. A legal cap of nine connections per subscriber defining violations.
Human oversight: Not assessed
Relation to AI: DoT describes ASTR as an indigenous AI and big-data analytic tool. It uses facial recognition to find connections taken by the same person under different names. Disconnection follows a failed re-verification step, so the tool flags connections rather than deciding. Developer and deployer are the same public body (DoT), which wrote the PIB releases.
AI contribution: DoT describes ASTR as an indigenous AI and big-data analytic tool. It uses facial recognition to find connections taken by the same person under different names. Disconnection follows a failed re-verification step, so the tool flags connections rather than deciding. Developer and deployer are the same public body (DoT), which wrote the PIB releases.

Outcome identifiers: Not assessed
Benefit: disconnected more than 82 lakh connections through ASTR after they failed re-verification
Category: Reduced Risk
Status: Not assessed
Beneficiary groups: Society. Organizations.
Beneficiaries: Not assessed
Reach: Not assessed
Distribution and access: Not assessed
Duration: Not assessed
Expected?: Yes
Costs and harms: Not assessed

Studies: Not assessed
Study design: Not assessed
Measurement: Not assessed
Setting and sample: Not assessed
Measures: disconnected more than 82 lakh connections through ASTR after they failed re-verification
Comparison: Not assessed
Results: disconnected more than 82 lakh connections through ASTR after they failed re-verification
Additional value from AI: Not assessed
Limitations: Not assessed
Denominators: Not assessed
Materials for replication: Not assessed

Participants: Developer: Department of Telecommunications, Government of India. Operator: Department of Telecommunications with telecom service providers.
Jurisdictions: Developer: India. Operator: India.
Ownership and control: Not assessed
Dependencies: Not assessed
Cross-border connections: Not assessed
Geopolitical implications: Not assessed

Conditions for replication: A re-verification step whose failure triggers disconnection. Point-of-sale accountability and police follow-up. Safeguards against misidentification, which the OECD AI Incidents Monitor entry flags as a concern.
Replication attempts: 3 follow-up entries. Benefit recurred: 2. Outcome unresolved: 1.
Later findings: 9 October 2026. Minister of State Pemmasani restated at the India Mobile Congress that over 82 lakh fraudulent connections had been disconnected through ASTR.
Availability: Not assessed
Institutional decision: Not assessed
Grounds: Not assessed
Action and result: Not assessed
Success criterion: Not assessed

Assessed benefits: Society. Organizations.
Depth: Not assessed
Reasons: Society: Disconnection counts are aggregates. No measured reduction in fraud losses is documented. Organizations: DoT and operators report disconnections and blacklisting without an evaluated outcome.
Observed or intended: Not assessed
Rubric: Not assessed
Assessor and date: Not assessed
Alternative assessments: Not assessed
Fill: Independently reported

Kind: Not assessed
Related entries: Not assessed
Field: Telecom-enabled cyber financial fraud. SIM subscriber verification.
Purpose: Analyze, identify and weed out fake, forged and non-bonafide mobile connections to curb cyber crime.
Dates: Date basis unassessed: 2025 (precision unassessed). Updated: 22 October 2026.
Stage: Not assessed
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