Facing the Facts: Why Traditional Credentials No Longer Cut It

Originally featured in the November 2026 issue of Security Management

Badges get shared. PINs get texted to a coworker running late. Passwords get written on sticky notes and stuck to a monitor. Every credential built around something a person carries, types, or remembers has the same structural weakness: it can be handed off, guessed, or stolen without anyone ever knowing.

That weakness isn’t a training problem or a compliance gap—it’s a design flaw. As long as a credential lives on a card, as a PIN, or in someone’s memory, it can exist in two places at once, with the authorized person and with whoever else has it. Facial authentication closes that gap by tying access to something that can’t be lent out, copied onto a second badge, or read over the phone: the real person standing in front of the camera.

The Security Case

Facial recognition is dramatically changing the way businesses are securing their facilities.

Those that deploy facial recognition are preventing credentials from being easily shared. A keycard or PIN can be used by anyone holding it, but a face can’t be delegated. This closes off an entire category of access control incidents that stem not from a breach, but from ordinary credential sharing: the “just use mine” and the badge left at the register.

Passwords and PINs are token-based, static strings, which is exactly why they’re valuable to steal. Once captured, they work indefinitely—or at least until the security team catches on. Well-engineered facial authentication systems use liveness detection to confirm a live person is present, not a photo, a video, or a mask, which changes the economics of an attack, since there’s no static secret to phish, leak, or sell.

Traditional credentials force a choice between speed and friction: tap a badge, key a PIN, or wait for a guard to check an ID. Modern facial authentication can offer both speed and security. A person walks up, gets verified, and moves through. This matters anywhere volume is high, like employee entrances, loss-prevention checkpoints, and multi-site retail environments—places where every added second at a door compounds across hundreds of daily transactions.

Together, these aren’t just incremental improvements on badges and PINs; they remove the underlying mechanism that makes credential-based fraud possible in the first place.

Privacy Must Be Part of the Architecture, Not an Afterthought

None of the above matters if the system built to verify people can’t be trusted to handle its own data responsibly. Facial data is sensitive by nature, and any organization evaluating this technology should treat privacy as a core design requirement—not a policy add-on.

A responsible facial verification system is built around a few non-negotiables:

• Authenticate with biometric templates, not face images. The system should convert a face into a mathematical template for comparison, rather than retaining and matching against stored photos or video. Biometric templates can’t be reverse engineered into a usable image, which limits what’s exposed even in a worst-case data breach event.
• Data minimization and defined retention. Only the data necessary for verification should be collected, and it should be held only as long as the stated purpose requires—not indefinitely by default.
• Encryption in transit and at rest. This is table stakes, but it’s worth confirming rather than assuming, especially for any data that leaves the device or site.
• Clear consent and opt-out paths. People should know when facial authentication is in use and have a documented way to opt out or use an alternative credential where required by policy or law.
• Compliance with applicable regulations. Depending on jurisdiction, this may include biometric-specific statutes and general data protection frameworks. A vendor should be able to speak to this directly, not vaguely.
• Independent accuracy and bias testing. Verification accuracy should be validated across demographic groups, with results available for review, not asserted without evidence.
• Intent-based activation, not passive scanning. The system should only process a face when a person deliberately engages with it, which is stepping up to a reader and initiating the interaction, rather than continuously scanning everyone who passes within camera range. This is the line between authentication and surveillance: nothing happens until the person chooses to authenticate, and no gallery of passersby ever gets built in the background.

What to Look for When Evaluating a Solution

For any organization comparing facial authentication vendors, the questions worth asking are less about the demo and more about the architecture and engineering underneath it:

1. Does the system store raw images or only biometric templates?
2. Where is data processed and stored: on-premises, at the edge, or in the cloud? Who has access to it?
3. What choices do individuals have regarding where their biometrics are stored?
4. What is the defined retention period, and can it be configured per site or per policy?
5. Does the system activate only on intentional interaction, or does it continuously scan everyone who passes within range?
6. What liveness detection is in place to prevent spoofing with photos, video, or masks?
7. Is there a documented consent and opt-out process for the people being verified?
8. Has accuracy been independently tested across different demographic groups, and are those results available?
9. What happens in a false non-match? Is there a human-reviewed fallback, or does the system create a bottleneck?

A vendor that answers these questions clearly, with documentation rather than reassurance, is signaling that privacy was built into the system rather than tacked on after the fact.

The Bottom Line

Traditional credentials fail in predictable, well-understood ways. They can be shared, stolen, or spoofed, and the tradeoff for tightening them has historically always been authentication speed.

Facial authentication addresses these security gaps by removing the transferable object at the heart of the problem. Whether it earns trust as a replacement depends on whether the underpinning privacy architecture holds up to the same scrutiny as the security claims on top of it.