Behavior Biometrics

Estimate age and prevent Account Takeover with frictionless Biometrics

Every person has a unique digital rhythm, keystrokes, swipes, mouse movements, and navigation patterns. Shufti’s behavioral biometrics captures these subtle signals in real time, detecting impostors and bots without interrupting the user experience so trust is verified continuously, not just once.

44%

Accuracy in determining age

Additional steps to verify age

38%

Higher conversion rate

Verifying age through behavior

Traditional age verification checks rely on documents that can be faked or borrowed. Behavioral Biometrics adds a dynamic layer, analyzing how users interact online to spot patterns inconsistent with claimed age. This silent, continuous approach strengthens compliance and keeps underage users from slipping through without disrupting genuine customers.

Detecting maturity patterns

Typing cadence, navigation speed, and device handling vary significantly between age groups. Behavioral Biometrics solution identifies discrepancies, flagging interactions that don’t align with the user’s claimed age.

Continuous Age Assurance

Instead of one-time ID checks at onboarding, behavior is monitored throughout the user’s session. This ensures minors can’t bypass age gates with borrowed IDs.

Frictionless protection

Users don’t face intrusive tests, behavioral signals run in the background. That means platforms stay compliant while offering seamless access to genuine, age-appropriate users.

Human behavior as proof of trust with Shufti’s Behavioral Biometrics Solutions

Traditional authentication ends at login. Behavioral Biometrics authentication keeps working in the background, ensuring that the person interacting with your platform is the same person who was verified at onboarding. It is seamless for users, impenetrable for fraudsters.

Continuous Authentication beyond login

Behavioral patterns are monitored session-long, not just at entry.

Tracks keystrokes, mouse movement, and swipes.
Identifies subtle deviations from a verified baseline.
Detects account takeovers even after login.

Invisible yet frictionless security

Trust is proven silently in the background.

No extra passwords, OTPs, or manual checks.
Works across devices and platforms without slowing users down.
Protects without interrupting the customer journey.

Adaptive Fraud Detection

Fraud tactics evolve, so does Shufti.

AI-driven models learn from new behavioral data.
Flags anomalies like bot activity, remote access tools, or scripted fraud.
Prevents fraud in real time, before it impacts revenue.

Quick and frictionless onboarding through Behavioral Biometrics Technology

Banking

Behavioral Biometrics in banking keeps customers safe without asking for repeated logins or extra OTPs. By silently monitoring their natural interaction patterns, banks deliver security that doesn’t interrupt, building long-term trust and loyalty.

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iGaming

Players want speed, not hurdles. Behavioral Biometrics continuously verifies them in the background, blocking bots and multi-account abuse while keeping gameplay seamless. The result is fewer drop-offs and stronger player retention.

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Ecommerce

Shoppers abandon carts when faced with friction. With Behavioral authentication, identity and trust are confirmed invisibly, reducing fraud checks that slow buyers down. This ensures smoother checkout flows and higher repeat purchase rates.

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Social media

Communities thrive when users feel authentic and safe. Behavioral Biometrics quietly filters out impersonators and bots, while genuine users enjoy an uninterrupted experience, driving deeper engagement and retention.

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Crypto

Crypto traders need both speed and certainty. Behavioral Biometrics tool secures high-frequency trading sessions without forcing interruptions, ensuring that legitimate users trade freely while fraudsters are locked out. That balance keeps users active and loyal.

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Five steps to Behavior-based trust

Step 1 Data Capture

Step 2Baseline Profile Creation

Step 3Continuous Monitoring

Step 4Anomaly Detection

Step 5Decision & Action

Fraud signals are flagged instantly when behavior diverges.

Identifies bots, automated scripts, or credential stuffing.
Detects account takeover attempts mid-session.
Differentiates between genuine errors and fraudulent intent.

User behavior is recorded across devices and sessions.

Keystroke dynamics.
Mouse movement and click cadence.
Mobile swipe gestures and scroll patterns.

An individual’s unique behavioral fingerprint is built.

Machine learning creates a trusted reference model.
No need for static credentials.
Adapts over time as user habits shift.

Verification runs silently in the background during every session.

Detects sudden behavioral deviations.
Tracks real-time risk, not just static identity.
Works across login, payments, and transactions.

Fraud signals are flagged instantly when behavior diverges.

Identifies bots, automated scripts, or credential stuffing.
Detects account takeover attempts mid-session.
Differentiates between genuine errors and fraudulent intent.

Businesses receive risk scores and recommended actions.

Allow, challenge, or block transactions.
Customizable thresholds for risk appetite.
Full audit trail for compliance and investigations.

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The 1% that matters in fraud prevention

Most vendors boast “99% fraud prevention”, but the real danger hides in the 1% they overlook. In this whitepaper, follow the story of Jack, a seasoned fraudster who thrives in those blind spots. Discover why it’s time for companies to move beyond surface-level checks and adopt solutions that truly understand the nuance in every case.

Download the whitepaper

Frequently Asked Questions

What is Behavioral Biometrics Authentication?

Behavioral biometrics authentication analyzes a user’s unique patterns of behavior, such as typing speed, mouse movements, and device handling, to verify their identity.

How is Behavioral Biometrics Age Estimation different from traditional Age Verification methods?

Unlike traditional methods that rely on documents or self-reported data, behavioral biometrics uses patterns to estimate a user’s age based on behavior, providing a more dynamic and accurate verification.

How does Behavioral Biometrics work?

It tracks and analyzes a user’s interactions with devices and applications, comparing the data to baseline patterns to detect anomalies and verify identity.

What are the most commonly used types of Behavioral Biometrics?

Common types include keystroke dynamics, mouse movement patterns, touchscreen behavior, and gait recognition.

Which industries benefit most from Behavioral Biometrics?

Finance, healthcare, and e-commerce industries benefit from behavioral biometrics for secure, frictionless authentication, reducing fraud and enhancing user experience.

What types of integrations does Shufti offer?

Shufti offers API-based integrations for seamless implementation of behavioral biometrics into your platform, alongside other verification methods like facial recognition and document verification.