A customer applies for a financial product or an iGaming account online. Their documents look legitimate, their credentials check out, and their selfie matches the photo on their ID.
Or does it?
As AI-generated deepfakes become more convincing and document fraud grows increasingly sophisticated, you’re probably finding it harder than ever to determine whether the person on the other side of the screen is genuine.
At the same time, your company must balance security with customer experience, preventing fraud without introducing friction that drives genuine users away.
Biometric authentication can help. By verifying unique physical and behavioural characteristics (such as facial features, fingerprints, or voice patterns), biometrics provide an additional layer of assurance that users are who they claim to be. And when implemented effectively, biometric verification can strengthen your fraud prevention without leading to drop-offs.
But biometrics aren't without challenges. In fact, they introduce important considerations around bias, false rejections, and false positives. And as a business building secure digital experiences, you naturally want to know what to keep in mind before implementing biometrics into your onboarding process.
That’s exactly why we’re written this article. We’ll go over:
GBG is a digital identity technology company with more than 30 years of experience in the identity verification space. To strengthen your biometric verification, book a demo and discover how our identity proofing solutions can help safeguard your business against fraud.
Biometric authentication is a method of verifying identity using unique physical or behavioural characteristics, such as a person's face, fingerprint, voice, or typing patterns. Because these traits are difficult to replicate, biometrics provide a secure and convenient way to confirm that someone is who they claim to be.
Today, biometric authentication is widely used across industries, from authorising financial transactions to securing border crossings and verifying patient identities in healthcare.
In a nutshell, biometric verification works by comparing a digital representation of a person's biometric trait against a previously enrolled template. If the two match within an acceptable threshold, the individual's identity is verified.
Biometric verification systems should:
The real convenience of biometric authentication is that we carry our credentials with us wherever we go. With no PINs, passwords, or other knowledge-based responses required, biometrics don’t tax our memories in order to deter impostors.
As such, onboarding is quicker, with most biometric processes completed in a matter of seconds.
Read more: How to improve KYC conversion rates: 8 strategies
Unlike knowledge-based systems, biometric authentication isn’t a very appealing target for hackers.
Passwords and security answers can be stolen, shared, or exposed in bulk during large-scale data breaches. But biometric data is harder to exploit at scale because successful attacks typically require more targeted attempts to compromise an individual’s biometric traits.
The impersonation of an individual’s physical characteristics (often referred to as a ‘presentation attack’ or ‘spoof’) requires sophisticated circumvention of scanner or camera sensors in a biometric system. This is far less easy than hacking a password.
Biometric authentication is only effective if the genuine user is actually present during verification. Just as a passport is only valid when presented by its rightful owner at border control, digital identity systems must confirm that the person behind the screen is real.
This is where liveness detection plays a key role. Independently tested by organisations such as the U.S. National Institute of Standards and Technology (NIST), liveness detection is a technology that verifies that the person submitting biometric data is physically present during the verification process – not a photo, video, mask, or AI-generated imitation.
By coupling biometric identity authentication with liveness or presentation attack detection, biometric systems are hard to spoof. In facial recognition, for example, a still photo of a face or a rubber mask will fail the genuine presence test.
Learn more about the benefits of biometrics and how we can help you build a more secure onboarding process by scheduling a demo today.
A false match can occur when the biometric data of two different individuals is confused.
Although rare, this can happen:
To successfully reduce the false acceptance rate (FAR) in biometric authentication systems, the system must be able to capture high-quality biometric samples and regularly update biometric reference templates to correctly match against enquiries.
Sometimes, the reverse can occur: a known identity might get falsely rejected by a biometric authentication system.
For example, this can happen when a person’s biometric traits change: an older person’s fingerprint has become worn with age or an individual may have had a change in facial appearance due to weight loss or weight gain.
Poor image capture quality caused by blur or glare can also result in false rejection.
Again, you should ensure that the sensors your systems rely on to capture high-quality biometric samples and templates are regularly updated. This should minimise the false rejection rate (FRR).
It's also important to remember that biometric matching isn't an exact science. Authentication systems use sophisticated algorithms to assess how closely a biometric sample matches a stored template.
This means you'll need to decide where to strike the balance between security and user experience. A stricter threshold may reduce the risk of fraud but increase FRR, while a more lenient approach can improve convenience at the cost of higher FAR.
Biometric authentication systems are powered by machine learning algorithms. In past studies, The US National Institute of Standards and Technology revealed that African-American and Asian people experienced a 10 to 100 times higher FAR compared to Caucasian people when encountering some facial recognition systems.
That’s why care must be taken to train these algorithms on data sets that are inclusive and don’t inadvertently discriminate against any demographic or result in racial bias.
To avoid unintentional partiality, the best authentication systems follow ISO standards to ensure the design and development of AI systems and applications don’t discriminate or disadvantage any group, or deny access to essential digital services.
Strong security shouldn’t come at the expense of the customer experience. Today's users expect fast, seamless interactions, whether they're opening an account, making a payment, or accessing a service. If biometric verification is slow or difficult to complete, it can lead to lost business.
That's why you need to strike the right balance between security and onboarding speed. The level of authentication should reflect the level of risk, allowing you to protect against fraud without creating unnecessary barriers for genuine users.
Multimodal biometrics systems, for example, help increase security and accuracy by combining authentication checks against several biometric features, such as the face and the iris or the iris and fingerprints. However, this may be at the expense of speed.
One way to solve this issue is to combine biometric authentication with identity data checks, such as verifying a user's name, date of birth, and address against trusted data sources. This helps to quickly triangulate trust in that person’s identity with reference to credit bureaus or mobile operator databases, which means the user can get through onboarding more quickly.
We’ve built our end-to-end KYC platform, GBG Go, to help speed up your identity verification process with global, comprehensive, and multi-source data checks. Book a quick call with one of our team to learn more.
Our face, fingerprints and eyes have all become everyday methods of proving who we are. But what are the features of a biometric trait that make it useful for authentication?
Universal
Every individual accessing the system should possess the same feature.
Distinctive
Biometric characteristics should be sufficiently different to distinguish any two individuals.
Permanent
The biometric identifier should not change significantly with time or with age.
Measurable
The digitized feature should provide recognition speed and accuracy.
As your customers’ lives become increasingly digital, they expect fast, smooth onboarding experiences. At the same time, fraudsters are getting increasingly sophisticated, using deepfakes, presentation attacks, and synthetic identities to bypass traditional verification methods.
This leaves you with a difficult choice: strengthen your authentication controls (which adds friction for users) or make onboarding quicker and easier, but risk higher fraud losses.
As a global identity technology company with more than 30 years of experience, we help businesses like yours build secure, low-friction onboarding and authentication journeys. We power more than 800 million identity checks each year for over 20,000 customers worldwide.
With our solution, you can deploy standalone biometric verification capabilities or use GBG Go, an end-to-end identity orchestration platform, to unify your verification workflows through a single API. By accessing more than 80 KYC modules – including biometrics, document verification, and identity data checks – you can verify customers globally while adapting verification flows to different risk levels, regulatory requirements, or user experiences.
Here are three reasons businesses like Santander, Nike, and Lottoland partner with us:
Biometric authentication is only as good as the data it captures. A blurry selfie, a shadow across an ID document, or glare from a camera flash can all make it harder to verify a genuine customer.
Our smart capture technology uses the camera on a customer’s mobile device to automatically recognise and classify identity documents during verification. It also guides users through the process with step-by-step instructions and real-time feedback, helping them avoid glare, blur, and other common issues that can affect optical character recognition.
Once the document is captured, our facial biometric matching compares the customer’s selfie with the image on their identity document. The technology analyzes 68 facial landmarks to help confirm that the person presenting the document is its rightful owner. Our algorithms are NIST-accredited and designed to minimise demographic bias across age, gender, and ethnicity.
What’s more, our velocity fraud intelligence helps identify suspicious behavioural patterns across accounts and transactions. For example, the system can detect when the same biometric image or document has been used across multiple identities or onboarding attempts, which is a common indicator of fraud.
And our passive liveness testing works from a single selfie capture. Customers do not need to blink, smile, turn their head, or complete extra actions, which helps reduce user error.
Fraudsters are becoming more sophisticated. From AI-generated selfies to deepfakes and presentation attacks, today's threats are designed to exploit gaps in standalone verification methods. Simply put, relying on a single identity check is no longer enough.
A layered approach to identity proofing gives you more confidence that customers are both who they claim to be and genuinely present during onboarding. By combining biometric verification, document authentication, and fraud intelligence, you can build a more resilient verification process that is better equipped to detect and stop fraud early in the onboarding process.
Of course, the strength of this approach lies in the quality of the checks behind it. Our document library contains more than 8,500 identity document types (including Digital IDs) from 195 countries and territories. Continuously updated by Cifas-accredited forensic document experts using millions of real-world samples, it helps ensure broad global coverage and reliable verification outcomes.
Every identity document is subjected to up to 50 forensic authentication tests in seconds, which identify signs of tampering, forgery, or manipulation. And for biometrically chipped documents, NFC technology can authenticate identity data directly with the issuing authority.
Enhanced tamper detection adds another layer of protection: it identifies fraudulent modifications made after a document has been issued with 98% effectiveness and a false detection rate of less than 1%.
No two onboarding journeys are the same. The checks you need, the regulations you must comply with, and the experience you want to deliver will depend on your industry and risk appetite.
Whether you're looking to add biometric verification to an existing identity workflow or build a fully orchestrated KYC journey from the ground up, you can deploy the capabilities that best fit your needs.
If you integrate with our end-to-end KYC orchestration platform, GBG Go, you’ll be able to bring all KYC checks into one centralised environment. This’ll give you a single source of truth for onboarding decisions and compliance reporting, and can also eliminate the time-consuming process of manually piecing together verification data from multiple vendors and systems.
What’s more, you’ll be able to customise user journeys based on risk, jurisdiction, and previous verification results. For instance, a genuine user who has passed all required data checks can be fast-tracked, while a higher-risk identity is automatically rerouted for document and biometric verification or EDD (enhanced due diligence).
And with our drag-and-drop workflow builder, you can configure and modify your onboarding flows without custom development.
Book a demo to learn how we can help you improve your biometric authentication process and strengthen your fraud prevention capabilities.
Biometric authentication is one of the most secure authentication methods available today. However, it is not infallible.
For example, fingerprint scanning technology can potentially be tricked using a fingerprint impression, face recognition systems may be fooled by sophisticated silicone masks, and iris scans can sometimes struggle to detect certain eye colours or may not work as effectively if you wear glasses or contact lenses. As with all authentication solutions, effectiveness depends on the quality of the technology and how it is implemented.
Biometric authentication technology is not biased, but as with all AI and ML solutions, biometric algorithms benefit from and respond to training with varied and inclusive data sets. The latest datasets have reduced demographic bias, making biometric identification processes more globally inclusive and effective than first-generation solutions.
Biometric authentication technology has long been built into mobile devices and has become more widely available and affordable over time.
Most smartphones have fingerprint scanners built into the home button, and voice recognition is regularly used as an input to various smartphone apps. Some devices also other forms of behavioural biometrics to verify users. These technologies often replace traditional passcodes or work alongside them to strengthen security.
Yes, and this is considered good practice. An identity is made up of several different elements. By combining data checks such as name, date of birth, and address with documents, devices, and biometric authentication, organisations can build a more complete picture of a customer's identity. This layered approach helps prevent identity fraud and identity theft, while improving onboarding and reducing risk.
Biometric authentication is generally more expensive than a simple password- or PIN-protected security system. However, as biometric security technology has evolved, costs have decreased significantly. Today, many authentication solutions powered by biometrics are available at price points comparable to alternative identity verification methods.