Facia.ai
Company
About us Facia empowers businesses globally with with its cutting edge fastest liveness detection
Campus Ambassador Ensure countrywide security with centralised face recognition services
Events Facia’s Journey at the biggest tech events around the globe
Sustainability Facia’s Mission for a sustainable future.
Careers Associate with FACIA’s team to create a global influence and reshape digital security.
ABOUT US
Facia is the world's most accurate liveness & deepfake detection solution.
Facial Recognition
Face Recognition Face biometric analysis enabling face matching and face identification.
Photo ID Matching Match photos with ID documents to verify face similarity.
(1:N) Face Search Find a probe image in a large database of images to get matches.
DeepFake
Deepfake Detection New Find if you're dealing with a real or AI-generated image/video.
Detect E-Meeting Deepfakes Instantly detect deepfakes during online video conferencing meetings.
Liveness
Liveness Detection Prevent identity fraud with our fastest active and passive liveness detection.
Single Image Liveness New Detect if an image was captured from a live person or is fabricated.
More
Age Verification Estimate age fast and secure through facial features analysis.
Iris Recognition All-round hardware & software solutions for iris recognition applications.
Customer Onboarding New Seamlessly and comprehensively onboard your customers.
Read to learn all about Facia’s testing
Industries
Retail Access loyalty benefits instantly with facial recognition, no physical cards.
Governments Ensure countrywide security with centralised face recognition services
Dating Apps Secure dating platforms by allowing real & authentic profiles only.
Event Management Secure premises and manage entry with innovative event management solutions.
iGaming Estimate age and confirm your customers are legitimate.
KYC Onboarding Prevent identity spoofing with a frictionless authentication process.
Banking & Financial Prevent financial fraud and onboard new customers with ease.
Contact Liveness Experts To evaluate your integration options.
Use Cases
Account De-Duplication (1:N) Find & eliminate duplicate accounts with our face search.
Access Control Implement identity & access management using face authorization.
Attendance System Implement an automated attendance process with face-based check-ins.
Surveillance Solutions Monitor & identify vulnerable entities via 1:N face search.
Immigration Automation Say goodbye to long queues with facial recognition immigration technology.
Detect E-Meeting Deepfakes New Instantly detect deepfakes during online video conferencing meetings.
Pay with Face Authorize payments using face instead of leak-able pins and passwords.
Facial Recognition Ticketing Enter designated venues simply using your face as the authorized ticket.
Passwordless Authentication Authenticate yourself securely without ever having to remember a password again.
Meeting Deepfake Detection
Know if the person you’re talking to is real or not.
Learn
Blogs Our thought dumps on all things happening in facial biometrics.
News Stay updated with the latest insights in the facial biometrics industry
Whitepapers Detailed reports on the latest problems in facial biometrics, and solutions.
Knowledge Base Get to know the basic terms of facial biometrics industry.
Deepfake Laws Directory New Discover the legislative work being done to moderate deepfakes across the world.
Case Studies Read how we've enhanced security for businesses using face biometrics.
Press Release Most important updates about our activities, our people, and our solution.
FAQs Everything there is to know about Facia’s offerings, answered.
Implement
Mobile SDK Getting started with our Software Development Kits
Developers Guide Learn how to integrate our APIs and SDKs in your software.
On-Premises Deployment New Learn how to easily deploy our solutions locally, on your own system.
Most important updates about our activities, our people, and our solution.
Try Now
Get 10 FREE credits by signing up on our portal today.
Companies adopting biometric systems must not have difficulties during enrollment. The system is not accurate or trustworthy when users are unable to register their biometrics or other identifiers. This is why FTE is important.
Failure to Enroll Rate, also referred to as FTE, is the percentage of individuals who do not successfully input their biometric data when registering with a biometric system. It is calculated as a ratio of the number of failed enrollments to the total number of enrollments attempted and then expressed as a percentage.
Considering an example, when 100 individuals make attempts to register their fingerprints in the system. Among them, three individuals fail because of the poor-quality prints, the FTE is 3%. The lower the rate, the more convenient and reliable the system becomes. High FTE rates may reflect technical limitations, as well as the environmental factors or demographic status that interfere with biometric capture.
FTE directly impacts the accessibility of a biometric system. When too many users are unable to enroll, the trust in the technology decreases, and alternative authentication methods must be provided. This creates both cost and operational challenges for the businesses.
Consider a hospital adopting fingerprint biometrics for staff authentication. When multiple workers are unable to enroll due to damaged fingerprints, the system supports fallback options, which complicates the process. Likewise, when passengers are not capable of checking in at the facial recognition terminals at airports, manual inspections slow down the procedure.
Therefore, the accuracy and inclusivity of every attempt should be factored into the design of the biometric systems with high/low FTE. A balance between advanced sensors and fallback options helps ensure the adoption across diverse user groups.
The Failure to Enroll Rate (FTE) is influenced by a variety of factors, the majority of which are beyond the user’s control. The quality of biometrics is imperative, and to that end, low-quality fingerprints, uncertainty in iris recognition, or environmental factors such as inadequate light can be a hindrance in enrollment. Demographic aspects, including age and physical conditions, are also a factor, as with elderly people and laborers who might have worn-out fingerprints.
Furthermore, sensors may be disturbed by environmental factors such as dust, humidity, and glare, and aging hardware or software may not accommodate natural biometric changes. With this, user collaboration is equally essential, since a lack of knowledge or wrong placement during capture may cause errors.
Understanding these factors helps organizations take steps to reduce high FTE rates during biometric enrollment.
Biometric error rates are critical indicators that reflect the integrity of a biometric system. Failure to Enroll (FTE) provides the frequency of the inability of users to enroll in the system. Other measures focus on errors after enrollment.
The False Acceptance Rate (FAR) indicates an impostor getting access, while the False Rejection Rate (FRR) indicates the chance of denying access to a rightful user. The Equal Error Rate (EER) is where FAR and FRR are the same, striking a balance between security and convenience.
FTE is important to take into account with these rates as high FTE may complicate the enrollment process, and high FAR or FRR may influence user experience and security.
Identity authentication depends on every stage of the biometric system functioning. If individuals cannot enroll, they can’t undergo authentication in the future. This makes FTE a foundational metric, shaping the usability of any biometric solution.
For identity authentication in banking, for example, customer onboarding begins with successful enrollment. If FTE is elevated, the bank experiences a higher drop-off, customer frustration, and an extra expenditure on manual verification. Likewise, in government initiatives where digital IDs are issued, high FTE has a negative impact on inclusivity, as it makes it difficult for non-citizens or excluded groups to register their biometric identifiers. FTE is not just a technical metric, it also affects equality and accessibility.
International organizations and standards bodies recognize FTE as a core performance metric. Guidelines on biometric performance testing, as defined by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC), describe FTE.
Thus, adherence to these standards ensures that biometric products are thoroughly tested prior to being deployed. The vendors who report low FTE rates under standardized conditions provide organizations with transparency and confidence in their solutions.
The trust in biometric systems relies on two qualities, which are accuracy and fairness. A low FTE system means that most users will be able to use that system without any barrier. Companies that share their FTE performance publicly are showing usability and inclusiveness.
Not only does this transparency increase user confidence, but it also provides assurance to regulators and other stakeholders that the system is constructed in a responsible manner. Such trust cannot be compromised in environments where identity authentication is mission-critical.
06 Oct 2025
CPRA vs GDPR: Navigating Biometric Data Privacy Regulations
In contrast, the CPRA considers biometric data as “sensitive...
03 Oct 2025
Why Is It Crucial to Understand Behavioral Biometrics for Digital Fraud Prevention?
The challenge is to adjust to the valid modifications...
01 Oct 2025
Why Are Deepfakes a Major Cyberthreat for CFOs?
Deepfakes were a passing fad on the internet a...
Recent Posts
How Deepfake Awareness Training Protects Your Organization Against AI Fraud?
Previous post
Alaska Senate Bill 2 (SB 2) – Legality and Implications of Deepfakes
Next post
What Is Tennessee’s ELVIS Act, and How Does It Protect Against AI Misuse and Deepfake Content?
Related Blogs