Where can biometrics deliver the most value?
Two high-impact areas are identity proofing and authentication, with the former focusing on establishing someone’s identity and the latter verifying it for ongoing access (e.g., logging in or approving a transaction).
Identity Proofing (often during onboarding or KYC - Know Your Customer): This is the process of verifying a person’s identity when they first sign up, apply for a service, or some credential is being issued, such as a digital electronic identity. Traditionally, this might involve a user presenting an ID document and maybe a video call or an in-person check. Biometrics takes this to the next level by enabling remote, automated ID verification or high-quality physical verifications at a greater speed. For example, a user can scan their passport or driver’s license with a mobile app and then take a selfie; the system will compare the face in the selfie to the face on the ID document to ensure the person is indeed the document’s owner. It significantly improves security and streamlines the user experience. This process is already widely used for customer onboarding in banking, fintech, mobile driving license issuance, and more. By leveraging biometrics in identity proofing, organizations can satisfy regulatory requirements (like KYC/AML rules) and reduce fraud (catching identity thieves or people using fake IDs), and save time and cost with streamlined solutions both for the organization AND for their end-customer.
Authentication (Ongoing User Verification): Once a user is onboarded and has an account or credential, biometrics can continuously ensure that “the claimed user is still the real user.” In practice, this means using biometrics for login or transaction approvals. Rather than relying on just passwords or SMS codes (which can be shared or stolen), you ask the user for a quick biometric check – for example, have them look at their phone’s camera for a face scan. The biometric sample is then matched against the enrolled reference (e.g., the face template or fingerprint on file from when the user registered) to verify their identity. This kind of authentication can be done as a primary factor (e.g., face unlock replaces a password) or as a second factor (e.g., after entering a password, the user’s face is scanned for confirmation). The major benefit here is security: biometric authentication binds access to the physical person. Even if an attacker knows someone’s password, they cannot easily fake that person’s face. Biometrics thus helps prevent account takeover, fraud, and identity misuse in scenarios like online banking login, high-value transactions, VPN access for remote employees, etc. From a user’s perspective, it’s also convenient – no extra devices or codes, just themselves. Doing this, also keep in mind that there is a difference between verified biometrics and the unverified device biometrics. Modern devices and apps can handle biometric login seamlessly, but the reference template is not verified, so i can enroll my face associated with your account if i obtain the credentials needed once. Thus there is a need for both device biometrics and verified biometrics authentication where a service provider has verified that the reference is of the claimed user.
Now, how to leverage biometrics effectively in these scenarios? Here are the key elements needed to implement a secure biometric solution for identity proofing or authentication:
- 1. A Trusted Reference Image or Template: You need an enrolled biometric “ground truth” for each user. This could be the photo extracted from an identity document during onboarding, which is what you typically are using in the identity proofing use case, or a face captured during the initial enrollment or you obtain it from references documents that you already have such as previously collected KYC reports. Either way, everything hinges on having a reliable reference to compare against. This reference must be high-quality and securely processed and stored depending on your needs.
- 2. A Capture Client (User Device/App): This is the software and hardware that captures a fresh biometric sample (technically often referred to as the biometric probe). For face recognition, it’s often the user’s smartphone camera or laptop webcam, guided by an app or web interface. The capture client should provide instructions to the user (e.g. “Center your face in the frame”) and ensure the image/video quality is sufficient for matching. It also often includes some on-device checks – for instance, detecting if the face is in good lighting or ensures sufficient quality. The integrity of the capture process is extremely important: you want to trust that the data indeed comes live from the user’s biometric. Leading solutions therefore deploy measures like tamper-resistant capture SDKs with resilient inject attack detection. The goal is to prevent malicious interference with the capture – which leads us to the next component.
- 3. Secure Biometric Processing Pipeline: Once the live biometric sample is captured, it must be sent for verification. A secure processing pipeline will perform the biometric match and simultaneously ensure the sample is genuine. This typically involves a server (or on-device service) that runs advanced algorithms to compare the live sample to the reference and produce a comparison score. Importantly, it also includes multiple layers of anti-fraud defenses: liveness detection, injection attack detection, and deepfake detection. Let’s break those down:
- Presentation Attack Detection with Liveness Detection: Presentation attack is an attack instrument presented to the camera sensor, such as a video display attack or a mask. Liveness detection or Presentation attack detection (PAD) verifies that the camera is seeing a real, live person and not a fake representation like a photo, video replay, or mask. It can be done through active prompts (e.g., “blink and smile” challenges) or passive analysis (examining the image for signs of life, such as skin texture, depth, or subtle movements). With the attacks being better and better, the legacy approach of active prompts that challenge the user for a response is easily fooled. Thus ensuring quality passive presentation attack detection is paramount. This is the first line of defense against imposters holding up someone else’s photo. Modern passive liveness AI can catch most obvious spoofs without requiring the user to do much. Liveness is absolutely essential whenever biometrics are used remotely or unsupervised, ensuring the system isn’t easily tricked by a simple printed photo or screen replay.
- Injection Attack Detection: Injection attacks are a more insidious threat where an attacker tries to feed synthetic or pre-recorded biometric data directly into the system, bypassing the camera. For example, malware on a device might inject a fake video feed, or a fraudster might use a virtual webcam driver to stream a deepfake video into the app. These attacks don’t involve physically presenting a spoof to the camera, so they can evade many of the basic liveness checks methods. Injection Attack Detection (IAD) tools add a “stream integrity” layer – they monitor the data pipeline for signs that the feed has been tampered with or is not coming from a real camera source. By hardening the client app and checking the origin of the video stream, IAD helps ensure the biometric data truly originated from a live capture and not an attacker’s injection.
- Deepfake Detection: As AI-generated deepfakes become more realistic, there’s a rising risk that an attacker could present an AI-created face (or voice) that mimics the genuine user. Deepfake videos can be injected as part of the attacks above or even used in a presentation attack (e.g., displaying a deepfake video on a tablet in front of a camera). To counter this, specialized deepfake detection AI is deployed. These algorithms analyze subtle details in images/video frames to distinguish real human faces from AI-generated or manipulated ones. It’s an arms race – as deepfakes improve, detectors keep adapting – but combining multiple detection techniques dramatically improves security, and ensuring integrity of a biometric verification process is significantly different then detecting all deep fakes on the internet (which is even harder).
When you put all of the above together, the result is a robust biometric verification process. Here’s how it might look in practice: A user wants to log in to a banking app using face ID. The app’s capture client prompts the user to position their face. Behind the scenes, the system ensures it’s a genuine camera feed and maybe performs a quick passive liveness check. The live image is then sent to the decision modules, where the system compares it to the user’s enrolled face reference. Concurrently, the system’s PAD (presentation attack detection) confirms the image wasn’t a photo and the IAD modules flag no signs of feed tampering. The face matching algorithm finds that it’s, say, a 98% match to the reference – well above the threshold – and with all anti-spoof checks green, the user is authenticated successfully. All this happens in a couple of seconds or less. From the user’s perspective, they just looked at their phone and got logged in. From the security perspective, the system had multiple layers verifying both the user’s identity and the authenticity of the biometric data, creating a secure chain from capture to decision.
Identity proofing workflows are similar, just with an added document in the mix. For instance, during onboarding, after the app confirms liveness and captures your selfie, it matches your selfie against the face on your submitted ID document. If there’s a match and the ID is authentic, you’re approved and officially “known”. The next time (for authentication), your live biometrics can be matched against the stored reference from that onboarding session. Notably, many solutions also keep an audit trail – e.g., storing a reference image of the session – to have evidence of who was verified.
The main point is that biometrics can significantly enhance both initial identity verification and subsequent user authentication, but it must be implemented with a holistic security approach. You leverage biometrics by not only deploying accurate matching algorithms, but also by ensuring the biometric is collected and processed securely. Face verification with the triumvirate of liveness, injection protection, and deepfake detection is currently the state-of-the-art in defending against fraud in remote ID verification and login systems. It ensures that the person on the other end of the camera is real, present, and who they claim to be.
Where should you leverage biometrics? In summary, use them anywhere you need high assurance that a user is who they claim, without adding friction or to speed up a process with the ease of use of biometrics. This can be:
- Account Onboarding / KYC: Verify new users by matching selfie biometrics to their photo ID. This stops synthetic identities or stolen IDs from passing through your registration.
- Login & Authentication: Allow users to log in with a selfie (or in addition to) passwords or re-establish trust in account recovery processes. This prevents phishing and shared credential problems – only the true user can log in.
- Step-Up Verification: For high-risk actions (money transfers, password resets), require a quick biometric check. This ensures the person confirming the action is the legitimate account owner, adding a powerful safeguard against account takeover.
- Physical Secure Access: Even beyond digital, biometrics can control access to facilities or kiosks (e.g., face or iris scan to enter a data center). It ties access to an individual’s identity, which is far harder to forge than an access card or PIN code.
When done right, it dramatically reduces fraud (criminals can’t as easily fake biometrics at scale) while keeping the process user-friendly.
Ready to raise the bar on security and user experience? Biometrics can help you onboard customers remotely with confidence and keep accounts secure with seamless logins. The key is using a certified, well-designed solution that incorporates liveness and inject attack prevention with a holistic anti-spoofing approach, and robust matching. If you’re interested in implementing biometric identity proofing or authentication in your organization, contact us for a demo or consultation. Being biometric experts we even offer the option to talk directly 1:1 with a professor in biometrics that has decades of experience. See first-hand how face verification and liveness detection can reduce fraud and make your user journeys both simpler and more secure.