Improving KYC Accuracy with Face Match Technology

Your phone recognizes your face even when you’re half asleep and stumbling to the bathroom at 3 am. It’s honestly impressive how well face unlock works in terrible lighting with your hair sticking up everywhere.

So why don’t banks and financial companies use this same facial recognition technology when they’re trying to verify who you are? Most will spend forever checking documents and running database searches, but they never actually confirm the person holding the ID matches the photo on it.

Kind of weird when you think about it. Your phone is 100% sure you’re you, but banks just hope the right person shows up with the right paperwork.

Face match for KYC works exactly like phone unlock, just comparing live selfies against ID photos instead of stored images.

Same technology, different application.

We’ll definitely explore its mechanism and more, but first, here’s the answer to the question you came for.

How can Face Match Technology Increase KYC Verification Accuracy?

Here’s the thing about traditional KYC – platforms are checking everything except whether the person is actually who they say they are. Document authentic? Check. Address verified? Check. Database records match? Check. But is that really John Smith holding John Smith’s driver’s license? No clue.

And adding fuel to the fire, Identity theft numbers are getting ugly. According to FTC data, it became the top fraud category in Q1 2025 – beating the second-place category by nearly 70%.

Most of these fraudsters succeed because businesses can verify documents but can’t verify people. Face match technology bridges that gap by comparing the live person against their ID photo.

The tech analyzes facial geometry and creates a match score, so you know if someone’s using a stolen identity or fake documents. Let’s explore this mechanism more deeply.

Face Match Technology Mechanism

Face match technology works through four distinct steps. We’ll use Sarah as an example to show exactly what happens during the verification process.

Sarah is opening a new bank account online. She uploads her driver’s license, and the system prompts her to take a selfie. Here’s what happens next:

1. Document Processing The system scans Sarah’s driver’s license using OCR technology to locate and extract her photo. It isolates her face from the document background and prepares the image for analysis.
2. Live Image Capture Sarah takes her selfie through the app camera. The system captures her live image and isolates her face, adjusting for different lighting conditions and angles compared to her license photo.
3. Facial Feature Mapping Both Sarah’s license photo and selfie get converted into mathematical maps. The system measures key facial landmarks – the distance between her eyes, nose bridge shape, jawline curve, and cheekbone placement. This creates unique digital “faceprints” for both images.
4. Match Scoring with Liveness The algorithm compares Sarah’s two faceprints and calculates a confidence score showing how likely they match. At the same time, liveness detection confirms Sarah is physically present, not someone using her photo or video.

The whole process takes 2-3 seconds.

Sarah gets approved if both her match score and liveness check meet the bank’s requirements.

Data Protection and Collection Practices

Facial biometric data falls under strict privacy regulations across most jurisdictions.

Laws vary by region, so check your local requirements, but here are the baseline practices you’re typically required to follow.

1.   Obtain Explicit Consent Before Collection

Don’t just bury the biometric collection in your terms of service. Users need to specifically agree to facial data collection before you start capturing anything.

Present biometric consent as its own checkbox, not bundled with other agreements. Once collected, keep dated records of who agreed and when for compliance checks.

2.   Provide Clear Notice and Disclosure

Users deserve to know exactly what happens to their facial data after you collect it. Don’t make them guess or dig through privacy policies to find basic information.

Spell out who processes the data, where it gets stored, how long you keep it, and whether it crosses borders. If third parties are involved in verification, name them. Transparency builds trust and keeps you compliant.

3.   Implement Data Retention and Deletion Policies

Different places have different rules about how long you can keep biometric data:

• GDPR (EU): Delete when purpose fulfilled or upon individual request
• CCPA/CPRA (California): Delete when no longer reasonably necessary for stated purpose or upon consumer request
• BIPA (Illinois): Delete when initial purpose satisfied OR within 3 years of last interaction, whichever comes first
• PIPEDA (Canada): Delete when no longer required for identified purposes

Set up automated deletion wherever possible. Manual processes get forgotten and create compliance problems down the road.

4.   Limit Third-Party Sharing and Commercial Use

Keep biometric data locked down to its original purpose. Don’t sell it, don’t use it for marketing, don’t share it unless absolutely necessary for verification.

When you work with third-party verification services, make sure they follow the same privacy rules you do. Check their practices regularly instead of just trusting their contracts.

5.   Secure Storage and Protection Requirements

Biometric data needs better security than regular customer information. Most laws specifically call this out as requiring extra protection. Below are some security essentials you can’t skip:

• Strong Encryption: Use current standards like AES-256 for stored data and TLS 1.3 for transfers
• Limited Access: Only give biometric data access to people who absolutely need it for their job
• Separate Storage: Keep facial data away from other customer information to limit breach exposure
• Regular Testing: Run security audits and penetration tests to find vulnerabilities before hackers do
• Breach Plans: Have documented procedures ready for when (not if) security incidents happen

Consider storing mathematical templates instead of actual facial images to reduce both security risks and regulatory burdens.

6.   Enable User Rights and Data Control

Give users real control over their biometric data, not just promises in privacy policies. Build these controls into your app or website so people can actually use them.

Let users see what facial data you have, correct errors, and delete everything if they want. Make the process simple enough that people don’t need to call customer service or send emails to exercise their rights.

Choosing the Right Face Match Solution

Not all face-match technologies work the same.

Some solutions work great in perfect conditions but fall apart when users take selfies in bad lighting or their appearance changes since their ID photo. Others catch basic photo attacks but miss deepfakes and sophisticated fraud attempts.

You need something that handles real-world messiness without blocking legitimate customers. Here are some suggestions. You should look for:

• Accuracy across different faces and conditions, so your solution works for all users, not just perfect lighting scenarios
• Liveness detection that stops modern attacks because fraudsters use videos and deepfakes, not just printed photos
• Built-in compliance features, so you don’t have to figure out complex biometric data laws yourself
• Easy integration options because months of development work defeat the purpose of buying a solution
• Performance that scales, so your verification doesn’t slow down when user volume increases

Most providers excel at one or two of these but fall short elsewhere.

Signzy handles the complete package with accuracy, fraud prevention, compliance, and integration that actually works. Want to test it? Book your demo here!