Age Verification: Privacy, Tech & The Future 🚀🔒

FACIAL AGE ESTIMATION: A SHIFTING LANDSCAPE
The global push for age verification is gaining momentum, driven by increasingly stringent laws and a growing recognition of the need to protect minors online. Currently, more than 30 nations have implemented age assurance measures, with the UK’s Online Safety Act and Australia’s under-16 rules representing key milestones. The dominant approach—facial age estimation—offers a seemingly efficient solution, avoiding the need for traditional identification documents or extensive database searches. However, this reliance on facial data exposes significant vulnerabilities, prompting a critical reassessment of current practices and a drive towards more secure, privacy-centric alternatives.

THE GROWING THREAT TO BIOMETRIC DATA
The traditional method of server-based facial age estimation—capturing a user's face, transmitting it to a server for analysis, and storing the results—is increasingly untenable. Data breaches are on the rise, with the U.S. experiencing a record-breaking 3,322 compromises in 2025 alone, a 79% increase over five years. Coupled with the escalating threat of agentic fraud—fraud attempts facilitated by AI—Incode’s data reveals a concerning trend: 40% of fraud attempts now rely on AI assistance, projected to reach 90% within 18 months. This rapid evolution of attack vectors underscores the urgent need for robust security measures and a fundamental shift in how biometric data is handled. The industry’s reliance on privacy-by-policy, a legal promise of data protection, proves inadequate against sophisticated threats, highlighting the critical need for architectural safeguards.

ON-DEVICE AGE ESTIMATION: A NEW STANDARD
Incode’s response to these challenges is the introduction of On-Device Age Estimation, a groundbreaking technology that enables age verification without ever transmitting or storing a user’s face. This innovative approach leverages on-device processing, running Incode’s facial age estimation and passive liveness models directly within the user’s smartphone, tablet, or laptop. This eliminates the risk of data interception and storage, aligning with the industry’s shift towards privacy-by-architecture—building systems that inherently prevent sensitive data from becoming accessible. By compressing the models and utilizing knowledge distillation, Incode has created highly efficient, low-resource solutions capable of running seamlessly across a wide range of devices, fundamentally altering the security landscape of age verification.

ON-DEVICE AGE ESTIMATION: A NEW STANDARD FOR VERIFICATION
On-Device Age Estimation represents a significant shift in how platforms verify user age, moving away from centralized processing and reliance on external data. This innovative approach leverages advanced machine learning models directly on the user’s device, dramatically enhancing privacy and security while maintaining a high degree of accuracy. The core technology combines sophisticated deepfake detection, injection attack prevention, and replay attack mitigation – all proven within Incode’s robust security layer – with a dedicated age estimation engine. This holistic defense strategy addresses the evolving threat landscape and sets a new benchmark for age assurance globally.

INCODE’S SECURITY LAYER: A PROVEN TRACK RECORD
For over a decade, Incode’s security models have operated within some of the world’s most heavily targeted environments, including banking, fintech, and healthcare. This extensive operational experience has yielded a remarkable record of success, with the Incode security layer achieving 99% spoof detection across a range of attacks – deepfakes, injection attacks, and replay attacks – alongside physical spoofing. Notably, this layer is trusted by eight of the top ten U.S. banks and has successfully flagged over 1 million face attacks across the Incode platform in 2026. This consistent performance demonstrates the maturity and reliability of Incode’s technology, providing a solid foundation for the new On-Device Age Estimation offering.

COLLABORATIVE FRAUD FIGHTING AND COMPLIANCE
The development of On-Device Age Estimation was directly spurred by the need for effective fraud prevention strategies, alongside increasing regulatory pressure around age verification. Institutions recognized the shared challenge of combating fraud without compromising customer data privacy. Incode, in partnership with Identiq, created a solution that now offers a comprehensive approach, encompassing SOC 2 Type 2, ISO/IEC 27001, HIPAA Attestation of Compliance, FedRAMP Ready, the Age Check Certification Scheme (ACCS), and the Kantara IAL2 Component Services Trust Mark. This robust compliance program, combined with over 7 billion trust checks processed and the new “face never leaves the device” shipping product, signifies a paradigm shift in how platforms can meet age assurance requirements while simultaneously safeguarding user data.