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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.
AI-Image Detection New AI Image Detection Detect manipulated or AI-generated images using advanced AI analysis
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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.
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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.
Shared Device Authentication Verify users on shared devices with secure facial biometrics.
Passwordless SSO Passwordless login powered by 3D liveness detection for secure enterprise access.
Step-Up Authentication Trigger real time 3D liveness checks for high risk or sensitive actions.
Self-Service Account Recovery Restore account access quickly through a face scan with no support needed.
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.
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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.
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In This Post
NIST IR 8491 establishes NIST’s benchmark for detecting face presentation attacks through passive software-based face presentation attack detection methods. The best competing algorithm in the tested scenario still allowed 6.9 percent of spoof attempts to succeed at face presentation attack detection. The bank processes 10000 new customers every day, which results in 690 fake identities that could pass KYC verification every 24 hours.
Liveness detection systems that operate with proper deployment will achieve zero false acceptance rates against 2D attacks, which enable them to eliminate all related threats. The difference between those two points of measurement holds significant importance for the bank. The entire fraud equation undergoes transformation because of this particular element.
Passwords were never designed to hold that line. They were designed to keep casual intruders out of early computing systems, not to stop a fraudster with a stolen identity document, a printed photo, and 30 seconds of patience.
Passwordless multi-factor authentication (MFA) with biometric liveness verification removes that attack surface entirely. This article covers the business case for making that transition: the security argument, the financial model, the compliance angle, and a phased implementation path.
A password is a shared secret. The user knows it. The system knows it. That means it can be stolen, guessed, phished, reused, leaked, and frequently is. None of these failure modes requires technical sophistication. Most phishing kits cost less than a coffee.
The management overhead compounds the security problem. Password resets, account lockouts, complexity enforcement, and help desk escalations consume IT capacity that could be redirected. A Forrester Research report on passwordless authentication found that organisations using passwordless authentication saved an average of 35% in IT support costs from password-related issues alone.
The more serious risk is what happens after credentials are compromised. An attacker with valid credentials plus a stolen photo ID can walk through a standard MFA check without triggering any alert. That is the gap that biometric liveness detection is designed to close. It does not just strengthen the password layer. It replaces it with something that cannot be handed to another person or extracted from a database breach.
The threat landscape for authentication has expanded well beyond credential stuffing. Understanding the specific attack types that biometric liveness detection addresses is essential before evaluating any vendor.
Presentation attacks are the oldest category: a printed photo, a screen replay, a paper mask, or a silicone replica held in front of a camera. Without liveness detection, a system processing a selfie-based KYC check cannot distinguish a live face from a high-quality photograph.
Digital injection attacks are the harder problem. Rather than presenting a physical artefact to a real camera, the attacker inserts a synthetic video feed at the operating system or API level, before the camera feed reaches the liveness check. Server-side liveness systems are blind to this attack because the fake feed replaces the real camera before the check runs. Only a client-side SDK, which secures the camera feed at the device level, can intercept and stop an injection attack before it reaches the server.
Synthetic identity fraud uses entirely AI-generated or composite identities to pass KYC onboarding. This is where biometric liveness and deepfake detection work together: liveness confirms a real person is present, and deepfake detection confirms the face is not AI-generated.
A bank, fintech, or digital platform that deploys only password-based MFA has no defence against any of these vectors. Biometric liveness detection is not an upgrade to that system. It is a replacement for the assumption that credentials alone can verify identity.
Procurement teams need a financial model. Here is a framework built around four cost categories.
Helpdesk cost reduction. Pull 12 months of password reset tickets and multiply by your average IT support cost per hour. According to Forrester Research, a single password reset costs organisations between $70 and $100 in IT support expenses. For most mid-size organisations, annual password-related support is a five- or six-figure number. Passwordless authentication eliminates that category of ticket almost entirely.
Fraud loss reduction. Ask your fraud team for the credential-based incident count and average cost per incident over the past year. Apply the Juniper Research 50% reduction estimate as a conservative working assumption.
Onboarding conversion improvement. Users are significantly more likely to complete an onboarding process without a password creation step.
Implementation cost. Factor in integration work, a three-month parallel-run period, and training. Modern biometric MFA solutions offer REST APIs, SAML, and OIDC support, and Android and iOS SDKs. Integration timelines are shorter than most IT teams expect.
Most organisations reach break-even within 12 to 18 months. One GDPR enforcement action for a breach involving stolen credential databases can dwarf an entire biometric MFA implementation budget. That liability belongs in the ROI model alongside the operational savings.
The regulatory argument is often the fastest path to internal approval because the cost of non-compliance is concrete and auditable.
PSD2 and EBA (Europe): The European Banking Authority requires Strong Customer Authentication (SCA) for online payments. Biometric MFA fulfils this requirement directly. Passwords plus SMS OTP are increasingly scrutinised under SCA.
GDPR: Biometric data is special-category personal data under Article 9. On-device biometric storage, where the raw biometric never leaves the user’s device, reduces the volume of sensitive data transmitted and stored centrally. This directly lowers GDPR exposure versus server-side processing.
NIST SP 800-63B (US): The US digital identity guidelines include biometric authentication requirements at Authentication Assurance Level 2 (AAL2). For AAL3, biometric liveness serves as part of a broader hardware-backed authentication architecture.
HIPAA, SOC 2, and ISO 27001: All three frameworks benefit from the stronger access controls and verifiable audit trails that biometric MFA generates. Every biometrically verified, timestamped authentication event satisfies audit requirements without manual reconstruction.
Organisations that delay passwordless adoption face both a current compliance gap and a more expensive reactive implementation when enforcement tightens.
Facia’s passwordless SSO replaces passwords, one-time passwords (OTPs), and hardware tokens with biometric face authentication across enterprise applications. One biometric layer, verified in under one second, covers every connected system via SAML, OAuth, or OIDC without replacing existing identity providers.
For high-risk actions within an authenticated session, such as fund transfers, admin changes, and sensitive data access, step-up authentication triggers a real-time 3D liveness check when it matters, without requiring a full re-login. For account recovery, self-service account recovery restores access through a biometric face scan with no help desk involvement.
The underlying liveness engine is iBeta Level 2 certified with 0% APCER, a 1-in-100-million FAR, and a sub-1% rejection rate, completing every check in under one second. Facia deploys via Android SDK, iOS SDK, and REST API. No new hardware is required.
The organisations that make this shift earliest gain a measurable security and compliance advantage over peers still managing password databases, reset workflows, and credential breach exposure.
Book a free Facia demo and see the liveness detection and passwordless SSO products in a live environment.
Passwordless authentication removes the need for passwords, while MFA adds extra verification factors. Biometric MFA can replace passwords and serve as a strong second factor, combining both functions securely.
Risks include potential device-level compromise, false rejections, and privacy concerns over biometric data storage. Proper on-device storage and certified liveness detection mitigate most of these concerns.
Step-up authentication adds an extra verification check for high-risk actions like fund transfers. It ensures strong security without forcing users to re-enter passwords for routine logins.
Yes, passwordless biometric MFA removes shared secrets that can be stolen or phished. Combined with liveness detection, it blocks sophisticated attacks that traditional MFA cannot stop.
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The Business Case for Passwordless MFA and Biometric Authentication
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