Behavioural biometrics is one of the core tools in continuous authentication methods, and it’s quickly becoming a key player in the fight against digital fraud. Unlike more well-known biometric technologies — such as facial recognition or voice verification, which rely on who a user is — behavioural biometrics focuses on what a user does. In other words, how they type, how they navigate a website, or how they interact with a device.
These behavioural patterns are unique and invisible, forming a digital signature that is extremely difficult to replicate, even by the most sophisticated attackers. For example, while a legitimate user will typically type their password key by key, a fraudster is more likely to copy and paste it. This difference — along with thousands of other signals — allows anomalies to be detected in real time without disrupting the user experience.
In this blog, we explore how this technology works, the threats it combats, how it can transform security in key sectors such as banking, fintech and insurance, and how Facephi applies it through its Behavioural Biometrics solution — designed to provide advanced, proactive, and frictionless fraud protection.
How does behavioural biometrics work?
This technology analyses the digital patterns a person generates when interacting with a device. This enables continuous risk assessment throughout the user’s session, from start to finish.
Facephi’s Behavioural Biometrics solution collects and analyses over 3,000 distinct signals using artificial intelligence and machine learning. Through this in-depth analysis, the system creates a unique behavioural profile for each user, allowing it to detect any deviations from their usual behaviour.
What types of signals are analysed?
To build this unique behavioural profile, Facephi’s Behavioural Biometrics evaluates signals such as:
- Typing biometrics: speed, rhythm, and keystroke patterns.
- Mouse biometrics: movement paths, clicks, and scrolling behaviour.
- Mobile biometrics: device movement, screen pressure, and gestures.
These signals help identify deviations from a user’s normal behaviour, enabling the system to detect fraud attempts in real time.
But the technology goes even further. It also takes into account the technical and environmental context of each interaction for more accurate analysis. This contextual approach includes:
- Device and network data: operating system, connection type, proxies, VPNs, etc.
- IP and GPS geolocation, SIM data, accessibility settings, and more.
- Malware indicators: signatures, suspicious traffic, anomalous permissions, etc.
All this analysis results in a dynamic and continuous risk score — capable, for example, of detecting an access attempt from an unknown device that pastes credentials, triggering an alert and blocking the session before it is completed. It adapts in real time, without creating friction for the legitimate user.
Key threats solved by behavioural biometrics
Protection against Account Takeover (ATO)
One of the biggest current challenges in cybersecurity is Account Takeover (ATO). This happens when an attacker gains access to a legitimate user’s credentials and logs into their account.
Behavioural biometrics makes a real difference here. By monitoring each session in real time and combining current and historical data, the solution can instantly identify suspicious behaviour. It also adapts defences seamlessly to avoid interrupting the user experience.
Fraud Detection in New Account Fraud (NAF)
Another growing threat is New Account Fraud (NAF). In this case, fraudsters create fake accounts — often using stolen or synthetic identities — to commit financial crimes, scams, or money laundering. In many cases, attackers bypass initial checks and operate as if they were genuine users.
Thanks to behavioural analysis, Facephi’s Behavioural Biometrics can:
- Detect suspicious behaviour and fraud patterns in real time.
- Prevent takeover attempts from the outset.
- Generate accurate scoring to identify fraudulent accounts.
- Distinguish legitimate users from potential attackers.
All of this translates into a system that offers early protection and drastically reduces the risk of fraudulent accounts slipping through security checks.
Benefits of integrating behavioural biometrics into your fraud prevention solutions
Incorporating this technology into your cybersecurity ecosystem not only strengthens protection — it also improves efficiency and enhances the user experience. Key benefits include:
- Intelligent risk analysis automation powered by adaptive AI.
- Proactive, frictionless protection against financial crime.
- Reduced operational costs by eliminating unnecessary manual tasks.
- Protection of legitimate users by blocking fraudulent access.
In a world where digital identity is becoming the new security perimeter, protecting users without compromising their experience is more important than ever. Traditional methods are no longer sufficient — behavioural biometrics represents a paradigm shift. It enables you to detect fraud before it happens, without disrupting the user journey.
Request a demo of our Behavioural Biometrics solution and discover how to prevent fraud before it occurs.