The AI and machine learning (ML) based Aadhaar Face Authentication solutions developed in house by the Unique Identification Authority of India (UIDAI) has been witnessing a massive growth with over 78% of the total transactions coming alone in the FY 25 fiscal year, ended 31 March 2025.

Transforming service delivery across India

Since the face authentication solution was introduced in October 2022, UIDAI has recorded a cumulative transaction number of over 130.5 crore, of which close to 102 crores have been recorded in the 2024-25 financial year. It indicates the growing usage, adoption of this solution and how it is benefiting Aadhaar number holders seamlessly.

In the past 3 months (January-March), nearly 39.5 crore face authentication transactions have been recorded. In March alone, the face auth solutions have recorded more than 15.25 crore transactions, a 21.6% jump over the previous month.

This achievement underscores the trust and adoption of this new biometric authentication modality across diverse sectors including fintech, finance and telecommunications.

Dozens of government services offered by both the centre and states are using it for smooth delivery of benefits to targeted beneficiaries. Several flagship schemes including PM Awas (Urban), PM E-Drive, PM-JAY, PM Ujjwala, PM Kisan, PM Internship, are using Aadhaar face authentication.

Face authentication is also working as a robust alternative and helping senior citizens and all those who have issues with the quality of their fingerprints due to several reasons including manual work or health issues.

As of now, 102 entities both in government and private sector are using Aadhaar face authentication. This AI based modality works both on Android and iOS platforms. It is safe against any video replay attacks and static photo authentication attempts by anti-social elements and a contactless, anytime- anywhere modality.

This authentication modality enables users to verify their identity with just a face scan, ensuring convenience while upholding stringent security standards.

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Dharmendra Tewari/ Navin Sreejith  

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