Biometric authentication is a way to prove who you are by using something unique about you - like your face or fingerprint. When you first sign up, the system securely saves a version of these traits. This step is called verification. Later, when you log in or confirm something like a payment, the system checks if your current traits match what was saved. This step is called authentication.

It’s a modern alternative to older authentication methods like passwords, SMS codes, or call centers. All of these aim to do the same thing: prove that the person trying to access the account is the same one who originally signed up. Biometrics just do it in a faster, more secure way.

Biometrics offer the strongest way to prove who someone is - something called identity assurance. This means confirming that the person trying to log in or take action is the same one who originally signed up.

Other methods like passwords, SMS codes, or even voice calls don’t really check who you are. They just check that you have access to something: a device, a phone number, or a code. These things can all be stolen or guessed.

Biometrics are different because they link directly to a person’s physical traits - like a face or fingerprint. This makes it much harder for someone else to pretend to be you.

However even faces can be copied using deepfake technology. That’s why the best biometric authentication systems now also use device binding. This checks that the person is not only showing the right face, but also using the same phone or device they used when they first signed up. So even if someone creates a perfect fake version of your face, they won’t be able to authenticate (log in or approve actions) without your actual device.

There are three main types of biometric authentication systems, each with different levels of security:

Yes, biometrics are more secure than passwords. They can’t be guessed or stolen. Passwords can easily be compromised, as most are reused and can be guessed with information on the owner.

More importantly, biometrics prove identity, while passwords only confirm that someone knows the password. The same goes for text codes - they just show that someone has access to your phone, not that it's actually you.

Decentralized biometrics combine the privacy of local systems with the security and usability of centralized systems. They process data on the device, like local biometrics, but then transform or encrypt it before sending it to the cloud for authentication. This way, no identifiable biometric data is ever stored or shared.

There are two ways to handle this process in decentralized systems: sharding and data transformation. With sharding, biometric data is split into pieces and stored across different cloud servers. However, these pieces can be reverse-engineered to reveal the original biometric data, which creates security risks.

The more private method is data transformation, where the biometric data is altered so that it not only resembles its original form but no longer legally counts as biometric data or Personally Identitifiable Information (PII). This means that even if the data is intercepted, it can’t be recognized as biometric information, offering the highest level of privacy and security.

Local biometrics are authentication methods stored directly on your device, like FaceID or Samsung's biometric system. When you authenticate, the app asks the manufacturer (Apple, Samsung) to confirm your identity.

The benefit is that users don’t need to enroll in each app separately, as their biometric data is already set up on the device. Additionally, the data stays private - it never leaves the device unless you choose to transfer it to another device from the same manufacturer.

However, the downside is that manufacturers only confirm if the face matches the one enrolled with their own system, not the face used to set up an account. The app has no way of knowing if the face has been changed, meaning fraudsters could potentially swap faces without detection, as long as the new face is linked to the same account.

Centralized biometrics store biometric data in the cloud, not on the device. Unlike local biometrics, they are tied to the app, not the device, so you can use them across different devices. For example, after verifying your face during account setup, a bank can compare it to your face later when you log in or make a payment.

Another key benefit is that you can enroll on one device (e.g., an iPhone) and authenticate on another (e.g., an Android tablet). However, the downside is privacy risks - any data stored in the cloud is susceptible to breaches.

Yes, biometric authentication significantly improves user experience compared to traditional methods.

Biometrics, on the other hand, offer a seamless experience. A quick facial scan or fingerprint recognition takes just milliseconds, providing faster and more reliable access.

Local biometrics (e.g., FaceID) store data on your device and are used to authenticate with apps. The benefit is that users don’t need to re-enroll; they can authenticate right away. Additionally, biometric data stays private on the device unless explicitly transferred. However, the app can't verify if the enrolled face changes or if multiple faces are added.

Centralized biometrics store data in the cloud, linking the biometric template to the app, not just the device. This allows you to use the same biometric data across devices (e.g., enroll with an iPhone and authenticate on an Android tablet). The downside is that cloud storage poses a privacy risk - data is vulnerable if the server is breached.

Yes, most biometrics take less than a second.

Passkeys require a biometric check, so they are about the same speed as biometric authentication. The issue with passkeys, however, is that they are not fully secure – they are an add-on to an existing knowledge-based check, like a password. If the biometric check fails, the user – or fraudster – can still access the system if they know the password.

Biometric authentication can fail due to factors like poor lighting, distance from the camera, or if the user is wearing too many accessories. Biometric models are constantly trained and improved to minimize these issues.

This failure, known as FRR (False Reject Rate), is very low with Keyless. Our FRR was tested by FIME and is FIDO Biometric certified, with an FRR of just 0.03%, well below the 3% threshold.

If authentication fails, businesses can choose alternative methods to authenticate users, such as using a password, PIN, or email verification.

Cloud-based biometrics can be used on any device with a camera, as the biometric data is stored in the cloud and not tied to a specific device. This allows users to authenticate on multiple devices, such as phones, tablets, or computers, regardless of the operating system.

Local biometrics, on the other hand, are tied to the device where the data is stored. For example, FaceID on Apple devices or fingerprint recognition on certain Android phones can only be used on those specific operating systems. This makes local biometrics less flexible, as they cannot be used across competing platforms.

Yes, but only with cloud-based biometrics. Cloud-based systems store biometric data in the cloud, allowing authentication across multiple devices. However, there are usability issues - such as needing to ensure each user’s biometric data is properly associated with the device and user account.

For example, in a retail store or on a factory floor, where multiple employees use shared devices, cloud-based biometrics can allow each employee to quickly authenticate on the same device using the device camera. This eliminates the need for PINs or passwords, speeding up processes while maintaining security across a shared environment.

Biometric systems can be GDPR compliant, but not all are. GDPR requires that biometric data must not be improperly stored or transferred - data must stay secure and only be processed with explicit consent.

Local biometrics (like FaceID) are generally compliant since the data never leaves the device, ensuring privacy. However, there are usability and security issues - such as limited device compatibility and difficulty in recovering data if the device is lost.

Centralized biometrics, on the other hand, are not GDPR compliant in most cases because they store biometric data on cloud servers, which may be located in different countries, posing risks of unauthorized access or data breaches.

Decentralized biometrics can be compliant, but it depends on how data is handled. If sharding is used (splitting the data into parts and storing them across servers), the data can still be reconstructed, violating GDPR.

The only way to guarantee compliance without using local biometrics is cloud-based biometrics that transform biometric data into cryptographic keys. These keys cannot be reverse-engineered as they don’t contain any biometric data by themselves. The key is only useful when paired with the device that created it, ensuring biometric data is protected and compliant with GDPR.

Multi-factor authentication (MFA) was first introduced to enhance security by requiring users to provide two or more forms of verification. It consists of three parts: knowledge (something you know, like a password or PIN), possession (something you have, like a phone or banking fob), and inherence (something you are, like your face or fingerprint).

MFA is the foundation of strong access security. All secure systems should require at least two of these three factors. Strong Customer Authentication (SCA), introduced in 2019 as part of the EU’s PSD2 regulation, mandates that payment systems use at least two factors to verify identity, helping to reduce fraud and improve security.

Multi-factor authentication (MFA) improves security by requiring two of the three factors whenever someone needs to prove their identity online.

A simple example is a vault with a key. If access could be granted with just the key (something you have), anyone who finds or steals the key could open the vault. This is a single-factor authentication system, and it's not very secure.

Now, imagine if you needed both the key (something you have) and a password (something you know) to open the vault. This would make it much harder for someone to gain unauthorized access, as they would need both pieces of information. MFA works in the same way by combining factors like knowledge, possession, and inherence to provide stronger protection.

Multi-factor authentication (MFA) works by requiring two out of three parts to prove identity:

By combining at least two of these factors, MFA ensures that gaining access requires more than just knowing a password or having one piece of information, making it much harder for unauthorized users to gain access.

The safest combination of authentication factors eliminates the knowledge factor - passwords or PINs. These are outdated technologies, easily hackable, and often guessable, especially if a fraudster knows some basic information about the person. This leaves us with possession (something you have, like a phone) and inherence (something you are, like your face). These are the most secure factors because they are harder to replicate. 

However, for the best multi-factor authentication (MFA), both factors need to be proven independently. This means one shouldn’t trigger the other if one fails.

Take FaceID as an example. It looks multi-factor, but it’s not fully secure. If the inherence check (your face) fails, it falls back to the possession factor (your phone). Here’s how it works: imagine a fraudster sees you enter your PIN and steals your phone. If FaceID is set up, they will fail the face check but then can use your PIN (the one used to unlock your phone) to access your bank account. Since they know your PIN, they bypass the security and gain access. This is why both factors must be independent for MFA to be truly secure.

Passwordless authentication refers to any technology that doesn’t rely on a knowledge factor, like a password or PIN, to verify identity. Instead, it uses alternative methods, such as:

These methods offer a more secure and user-friendly way to verify identity without needing a password.

Authentication is the process of confirming who you are. It answers the question, "Are you who you say you are?" This is usually done through passwords, biometric data, or other authentication methods.

Authorization, on the other hand, determines what you are allowed to do once your identity is verified. It answers the question, "What can you do now that we know who you are?" For example, after you log into a banking app (authentication), the system will determine if you can view your account balance, make transactions, or access certain features based on your permissions.

Keyless specializes in authentication, providing a secure, passwordless authentication solution using biometrics to prove a person’s identity.

Biometric data refers to unique physical characteristics used to identify individuals, such as facial features, fingerprints, and iris patterns. These data points are used in biometric authentication systems to verify and authenticate identity. 

The EU GDPR regulation classifies it as a special category of personal data, requiring strong protections to ensure privacy and security.

Yes, biometric data is considered personal data under GDPR. Biometric data, like facial features or fingerprints, is classified as sensitive personal data, which requires enhanced protections. Under GDPR, biometric data must not be transferred or stored improperly, and it must be processed securely. Local biometrics are generally GDPR-compliant because the data never leaves the device. However, there are usability and security issues, such as limited device compatibility and challenges with recovering data if the device is lost.

Centralized biometrics often aren’t compliant, as they store data on cloud servers, which can be located in different countries, raising privacy concerns.

Decentralized biometrics can be GDPR-compliant, but only if the data is transformed or encrypted properly. If the data is split (sharded) into parts and stored across servers, it can still be reconstructed, violating GDPR. The safest method is cloud-based biometrics that transform biometric data into data that no longer legally counts as biometric data, which can’t be reverse-engineered. Only the device used to create the key can access the biometric data.

Yes, FaceID does protect biometric privacy by keeping your biometric data stored securely on your device. It never leaves the phone or goes to the cloud, ensuring that your facial data stays private.

However, while FaceID excels at privacy, it does have some limitations in usability and security. Since the data is tied to the device, it can only be used on that specific phone, making it hard to recover if the device is lost or damaged. Additionally, if the face on the device is changed, FaceID cannot verify if the new face is really you, which could make it easier for fraudsters to bypass security.

Yes, cloud-based biometrics can protect biometric privacy, but only if done correctly. There are two types of cloud-based biometric authentication: centralized and decentralized.

Centralized biometrics store biometric data on cloud servers, which can be located in different countries. While this allows for easy access across devices, it raises privacy concerns as the data is stored in one central location and could be vulnerable to breaches.

Decentralized biometrics, on the other hand, process data on the device and then encrypt it before sending it to the cloud. The biometric data is transformed, ensuring it cannot be reconstructed or misused. This method combines the flexibility and security of cloud-based systems with the privacy of local storage, making it the more secure option for protecting biometric privacy.

No, hashed biometric data is not completely private. While hashing is designed to protect data by converting it into an unreadable format, there’s a significant issue with biometric data. Unlike typical data, biometric templates - such as a fingerprint or facial scan - can be reconstructed from hashed data.

This means that even though the data is hashed, it can still be reverse-engineered to reveal the original biometric template beneath.

Privacy-preserving authentication is a form of biometric authentication designed to protect user privacy. It ensures that even if a biometric template is accessed, the actual biometric data cannot be read or reconstructed.

Privacy is a major concern for many users when it comes to biometrics. While the technology offers convenience, users are often cautious about how their data is stored and used. This is particularly true in industries like crypto, where privacy and security are critical. Privacy-preserving authentication addresses these concerns by using encryption and other secure methods to protect biometric data at all times.

Privacy-enhancing technologies (PETs) are tools designed to protect personal privacy by minimizing data collection and ensuring data remains secure. They use methods like encryption and anonymization to reduce privacy risks.

In biometric authentication, PETs ensure that biometric data, such as facial scans or fingerprints, stays private. Instead of storing raw data, PETs transform it so it can’t be accessed or reconstructed, addressing privacy concerns while enabling secure authentication.

Identity verification is the process of confirming that the person setting up an account is who they claim to be. This step is common in industries where it’s crucial to verify that account owners are legitimate, such as banking, online dating, or travel.

It typically involves uploading an identity document and taking a selfie. The verification technology, often built into the app, compares the selfie with the photo on the ID and checks the ID details against national databases to ensure it’s a valid, real ID.

These terms are often confused. Identity verification is the process of confirming that the person setting up an account is who they say they are, typically by uploading an ID and taking a selfie.

Authentication, or identity authentication, is the process of proving that the person trying to access the account is still the same one who passed the identity verification. This can be done using methods like SMS codes or biometric face scans.

In short, identity verification confirms the account owner is real, while authentication ensures the person accessing the account is still the same.

Digital identity is an online version of a person, created through identity verification. This typically involves checking that the person setting up an account is who they say they are, often using a national ID card and a face scan - just like when setting up a bank account.

Governments around the world are working to implement national digital identity wallets for their citizens, offering huge benefits, from improved security to easier access to services.

Identity assurance is the process of proving beyond reasonable doubt that the person performing an action online is who they say they are. This can be done in several ways, including:

Identity portability refers to the ability for individuals to carry their verified digital identity across different platforms, services, and devices without having to re-authenticate their identity each time. This allows users to maintain consistent and secure access to their personal information and services across various applications, much like how a traditional identity card can be used in multiple places.

Digital wallets use biometrics in two main ways:

While most digital wallets verify users with biometrics during setup, many don’t perform authentication checks once the user is inside the wallet, leaving room for security gaps.

Digital identity wallets are as safe as the verification and authentication methods that protect them.

When these verification and authentication methods are robust, digital identity wallets can be very secure. However, their safety ultimately depends on the strength of the security measures in place.

An account takeover occurs when someone gains access to an online account without the owner’s consent.

A classic example is when a fraudster calls someone, pretending to be from the app they’re trying to break into, and tricks them into sharing the security code sent to their email. The fraudster pretends the person has forgotten their password, receives the security code, and convinces the person to read it out loud. Once they have the code, the fraudster is in.

Account takeover fraud happens when someone gains unauthorized access to an account and then uses it for fraudulent activities, like stealing money or selling personal details.

A common example of account takeover fraud is the SIM swap attack. In this attack, a fraudster calls the mobile carrier, tricking them into transferring a victim’s phone number to a new SIM card they control. Once they have control of the number, they can bypass security checks, like two-factor authentication, and access the victim’s accounts.

There are several ways to prevent account takeovers, and one of the main methods is authentication - ensuring that the person trying to access the account is really the one who set it up. This is done through authentication. Some of the best ways to authenticate include:

Another important way to prevent account takeovers is through security education and training. Teaching customers and employees to avoid clicking on scammy links or falling for phishing attempts can stop fraudsters before they get a chance. However, with AI making phishing more convincing, this has become more challenging.

There are many ways fraudsters can take over accounts. Some of the most common include:

Biometric authentication helps prevent account takeover fraud by ensuring that the person trying to access an account is the same one who originally set it up. It does this by comparing the authentication template (the live scan of the person’s face, fingerprint, etc.) to the enrollment template (the data collected when the account was created).

However, not all biometric systems provide the same level of security.

Cloud-based systems are generally more secure as they allow for more advanced verification methods and easier updates to the biometric data, reducing the risk of account takeovers.

Presentation attacks occur when a fraudster shows a video or photo to the camera in an attempt to bypass biometric authentication. This could involve using a printed photo, a video displayed on a screen, or even a deepfake, all of which are presented to the camera to mimic the original person. These types of attacks try to trick the system into thinking the real person is present, even when they’re not.

Injection attacks occur when videos are fed directly into a device's camera feed, effectively "injecting" the video. These videos can either be real footage of the person or deepfake videos designed to bypass biometric authentication systems. The goal is to trick the system into thinking the real person is present, allowing unauthorized access.

SQL injection attacks occur when a hacker inserts malicious SQL code into a website or application’s input fields, such as search bars or login forms. This code is then executed by the database, allowing the attacker to manipulate or access sensitive data stored in the database.

For example, instead of entering a regular username or password, an attacker might input malicious SQL commands that can delete records, retrieve confidential information, or even alter data in the system. These attacks exploit vulnerabilities in the system's input validation and can cause significant damage if not properly secured.

Biometrics detect deepfakes in a variety of ways. Keyless uses a 4-step process to ensure secure authentication:

Liveness detection is the process of confirming that the person in front of a screen is a real, live individual, rather than a photo, video, or deepfake. There are two types of liveness detection:

Phishing-resistant authentication makes it harder for attackers to steal credentials. While phishing can’t be fully eliminated, it can be minimized through:

Phishing-resistant MFA (multi-factor authentication) is any authentication method using two or more factors that significantly reduces the risk of phishing. While phishing can’t be fully stopped, phishing-resistant MFA makes it much harder for attackers to bypass.

For example, a combination of knowledge (password) and possession (phone) could seem phishing-resistant, but if a fraudster manages to steal both the password and phone, they can still access the account.

Another example is FaceID, which combines inherence (your face) and possession (your device). However, FaceID isn’t fully phishing-resistant. If a fraudster knows your PIN (used to unlock your phone), they could bypass FaceID’s authentication and access your account, making it vulnerable to phishing.

A spoofing attack occurs when someone pretends to be someone they’re not in order to abuse the trust of a user. Some famous examples include:

Biometric authentication defends against phishing by proving that the person authenticating is the same one who set up the account. Unlike passwords, PINs, or SMS texts, which only show that someone knows the information or has access to the phone, biometrics directly link a person’s unique traits - such as their face or fingerprint - to their account.

However, local biometrics like FaceID and Samsung Touch are weak against phishing. While they authenticate the user’s face or fingerprint, they often fall back on additional factors, like a PIN, if the biometric scan fails. If a fraudster gains access to the phone and knows the PIN, they can bypass the biometric check and access the account, making local biometrics vulnerable to phishing attacks.

A man-in-the-middle attack happens when a fraudster secretly intercepts communication between two parties. For example, if you’re sending sensitive information, like login credentials, over the internet, the attacker can capture and manipulate the data before it reaches its destination. The attacker essentially "sits" between you and the service you're communicating with.

A SIM swap attack occurs when a fraudster tricks a mobile carrier into transferring a victim's phone number to a new SIM card that they control. Once the fraudster has control of the phone number, they can bypass two-factor authentication and gain access to the victim’s accounts, even if the victim has security measures in place like SMS-based codes.

A cryptographic key is a string of data used to encrypt or decrypt information. In the context of public-key cryptography, there are two keys:

For biometric authentication, Keyless transforms the biometric data and splits the resulting values into a public-private key pair, with the private key stored securely on the user's device and the public key placed in the cloud. This ensures that even if the public key is compromised, it is essentially useless on its own, as it’s just random data without the private key to decode it.

False Acceptance Rate (FAR) is the likelihood that a biometric system will incorrectly accept an unauthorized person. False Rejection Rate (FRR) is the likelihood that the system will incorrectly reject an authorized user.

Keyless was tested by FIME, and the results showed:

Device binding is the process of linking a specific device to a person to prove possession. If a fraudster manages to gain access to your account remotely and attempts to perform actions, such as transferring money, they will fail because they don’t have access to the device (e.g., your phone).

Device binding typically happens at two steps of the user journey - enrollment into an app, and recovering your account if the device is lost.

By associating the device with the user, not just their face, it ensures that even if a fraudster gains access to the account, they still need the actual device to authenticate, adding an extra layer of security.

Device binding helps stop fraud by adding a possession factor. Combined with an inherence (face) or knowledge (password or PIN), it forms part of a multi-factor authentication (MFA) flow, which is one of the most effective ways of stopping fraud.

Imagine a remote fraudster trying to hack into an account. Even if they manage to spoof the user’s face using a deepfake, they still cannot authenticate without the original device. This is because device binding ensures that possession of the device is required in addition to the biometric check.

Yes, but it depends on the type of biometric system.

Local biometrics (e.g., FaceID or fingerprint recognition) are tied to a specific operating system, such as Apple or Samsung. The biometric data is stored on the device, and it can only be used on other devices within the same OS.

Cloud-based biometrics allow the same biometric identity to be used across different devices. However, for this to work, each device needs to be bound to the user's account. This means the system needs to verify that the device is trusted and belongs to the real owner before access is allowed.

Payment authentication is the process of verifying that the person initiating a payment is the account holder. This typically involves confirming the user’s identity using two or more authentication factors (knowledge, possession, or inherence).

For example, Keyless provides passwordless payment authentication by using biometrics (inherence) and device binding (possession). Instead of entering a password, users authenticate using their face, and the system checks that the device they’re using is the same one they originally enrolled into the app with.

PSD2 (Payment Services Directive 2) is an EU regulation that requires banks and payment providers to authenticate customers using at least two independent factors from the following categories: something the user knows (e.g., PIN or password); something the user has (e.g., phone or hardware token); something the user is (e.g., fingerprint or facial recognition).

In addition to this, PSD2 also mandates dynamic linking, which means that a customer’s approval of a transaction must be tied to both the exact amount and the recipient’s account details.

PSD3, expected to come into effect in 2026, will introduce even stricter rules regarding fraud liability and consumer protection. One key change is that banks and payment providers will bear greater responsibility if unauthorized transactions occur. To meet these stricter requirements, it’s crucial to ensure that the right person approves each transaction.

By combining biometric authentication (inherence) with dynamic linking (possession), organizations can reduce fraud risk, improve security, and ensure compliance with both PSD2 and the upcoming PSD3 regulations.

PSD2 focuses on requiring Strong Customer Authentication (SCA) for online payments, ensuring security by authenticating users with at least two factors: something they know, have, or are, along with dynamic linking to tie transactions to specific amounts and recipients.

PSD3, expected in 2026, will build on PSD2 by introducing stricter rules around fraud liability and consumer protection. Banks and payment providers will face more responsibility if unauthorized transactions occur, making it even more crucial to prove that the right person approved each action.

Dynamic linking is a requirement under PSD2 that ensures a transaction is tied to both the exact amount and the recipient’s details. If either of these details changes, the original approval is invalid, and a new, verified confirmation is required. This adds an extra layer of security, preventing fraud by ensuring that the correct transaction is being approved.

Keyless supports PSD2 compliance by enabling dynamic linking. It authenticates users each time they make a payment over a certain threshold determined by the app. The transaction is then tied to a unique code, or User ID, that includes both the amount and recipient, ensuring the User ID is always linked to the specific transaction details. This helps meet PSD2’s dynamic linking requirement for secure and compliant transactions.

Yes, biometrics can be used for transaction approval. When a user shows their face to their device camera when making a payment, their biometric data is compared to the enrolled template to confirm that the person initiating the transaction is the same one who set up the account. This adds an extra layer of security, ensuring that only the authorized user can approve transactions, helping prevent fraud and unauthorized access.

Step-up authentication is when a user is asked to provide additional authentication when performing a high-risk action within an app. Essentially, it's an extra layer of security for actions like changing account details, deleting an account, making a payment, or recovering an account - anything where the app wants to verify that it’s still the authorized user performing the action. This helps ensure that sensitive activities are properly protected.

Step-up authentication is triggered whenever the app or website wants to verify the user’s identity before allowing access to certain high-risk actions. It can include:

For example, every time you receive a text message with a one-time code, that's a form of step-up authentication, as it checks that it's really you trying to access or perform an action.

Step-up authentication is important for high-risk actions because, without it, fraudsters or hackers could perform any action once they’ve gained access to an app. It’s like having a locked building with no alarms or cameras inside. Once the intruder gets in, they can do whatever they want. Step-up ensures that actions within an app are protected, even if someone gains initial access.

Biometric account recovery works by allowing a user to recover access to their account if they’ve lost access to their device. For example, if a user loses their phone and their phone number changes, how do they access their bank account without relying on an SMS text check?

Traditionally, account recovery is done through call centers, but they are costly and not user-friendly. To regain access, the device must be re-bound to the user to prove possession. Since the user no longer has the original device (the possession factor), the user needs to re-bind the device. This can be done in a few ways:

The NIST FRVT 1:N recognition is a benchmark that tests how well biometric systems can identify a person from a large database of faces. 

Keyless was evaluated in 2025 and ranked 11th out of over 150 vendors, achieving 99.93% accuracy when identifying faces from 1.6 million identities.

The NIST FRVT 1:1 verification tests how well a biometric system can verify an individual's identity by comparing their live scan to the original enrolled template. 

In 2025, Keyless ranked among the Top 50 globally, excelling in the Mugshot category, which tests real-world identity verification accuracy.

ISO/IEC 30107-3 is an international standard for Presentation Attack Detection (PAD), ensuring biometric systems can detect and prevent fraud attempts like fake photos, masks, or deepfakes. 

Keyless is certified under this standard, confirming its ability to protect against presentation attacks and identity fraud.

The FIDO Biometrics Certification verifies that a biometric system meets the FIDO Alliance’s criteria for false acceptance rates (FAR), false rejection rates (FRR), and resistance to spoofing. 

Keyless is certified, ensuring its face recognition system is secure and highly usable, with privacy-preserving biometric authentication.

FIDO2 Certification ensures compliance with the FIDO Alliance’s passwordless authentication standards, which include WebAuthn and CTAP protocols. 

Keyless is FIDO2 certified, providing privacy-preserving authentication that integrates with FIDO2-compatible systems for scalable, secure authentication across devices.

eIDAS (Electronic Identification and Trust Services) is an EU regulation that ensures the trustworthiness and interoperability of digital identity solutions across the EU. It sets standards for electronic identification, authentication, and the use of trusted services in sectors like banking, finance, and public services.

Keyless is certified under eIDAS for Identity Proofing Services, enabling secure online transactions and compliance with high assurance levels required for electronic transactions in sectors like banking and finance.

Being GDPR compliant means that biometric data is processed securely and privately, in line with EU data protection regulations. 

Keyless is built with privacy-by-design and follows zero-knowledge principles, ensuring biometric data is never stored, shared, or accessible, even by Keyless itself.

CCPA compliance refers to meeting the requirements of the California Consumer Privacy Act, which gives California residents more control over their personal data. 

Keyless complies with CCPA by ensuring that biometric data is never stored or processed in a way that could be linked back to an individual.

ISO 27001 is an internationally recognized standard for Information Security Management Systems (ISMS). It sets out a framework for managing and protecting sensitive information.

Think of ISO 27001 like having a security system for your house. It sets up rules and measures to protect your personal belongings (in this case, your data), like locked doors, security cameras, and alarms to keep intruders out.

Keyless is certified under ISO 27001, ensuring that it has robust processes and controls in place to protect data and manage security risks effectively.

ISO 9001 is a certification for Quality Management Systems (QMS). It ensures that organizations consistently meet customer expectations and regulatory requirements, focusing on continual improvement.

Think of ISO 9001 as a company making sure all their products are made to a high standard. For example, a bakery that checks the ingredients and baking process to ensure every loaf of bread is consistently good.

Keyless holds this certification, demonstrating its commitment to reliability and high-quality service delivery.