Fraud Analytics

Detect Fraud Before Onboarding Completes

Multi-signal fraud analytics across biometric, document, device, behavioural, and cross-session layers. Real-time risk scoring flags synthetic identities, deepfakes, and coordinated rings before approval.

Request A Demo

Europe’s First iBeta Level 3 Certified Liveness Provider

Fraud Hub case review — multi-layer risk signals showing injection attack, device intelligence, document forensics, and biometric liveness correlated in one verification session

Fraud Detection You Can Verify

Measured Across Live Production Onboarding

2.29M

Fraud Attempts Blocked Yearly

2.29M

Injection Attacks Caught Daily

2.29M

Median Detect and-Block Time

Trusted By 2000+ Clients Worldwide

No Single-Signal Decisions. No Static Models. No Post-Approval Surprises.

Catch Fraud at the Signal, Not at the Manual Review Queue

Multi-Signal Fraud Scoring

Biometric, document, device, behavioural, and cross-session signals are scored together. A synthetic identity that passes a static texture check rarely matches the behavioural signature, the device fingerprint, and the cross-session history at the same time.

Request A Demo

Multi-mode waterfall mockup — connected verification steps with auto-escalation.

Real-Time, Not Forensic After the Fact

Every signal is scored at capture time and aggregated before the verification decision returns. Coordinated rings, mule networks, and serial spoofers are identified in seconds, not after the loss has cleared the account.

Request A Demo

Privacy architecture mockup — on-device biometric processing with GDPR/EDPB alignment.

Adaptive Models, Customer-Side Forensics

Detection models retrain against false negatives. New deepfake patterns and injection methods feed back into the model within weeks. A forensic audit engine running inside the customer's own AWS account can re-examine past sessions for spoof, replay, and injection.

Request A Demo

Layered defenses mockup — liveness, face match, and document authenticity signals.

Beyond Single-Signal Detection

Single-signal fraud checks miss coordinated attacks across biometric, document, device, and behavioural layers.Shufti aggregates every signal into one real-time risk score, with cross-session clustering and forensic re-analysis inside the customer’s AWS environment.It is not a fraud filter, it is a multi-signal fraud intelligence layer.

Request A Demo

Proprietary stack mockup — unified, in-house, single accountable verification architecture.

Built Into the Platform

The Fraud Signals Behind Every Risk Decision

Biometric Spoof Detection

Active and passive liveness across 56+ attack vectors. Texture, frequency-domain (DCT), and 3D depth analysis catch print attacks, replay attacks, screen attacks, and AI-generated face media.

Unified Risk Score

Every signal feeds a single risk score with contributing-signal breakdown and model version. Risk thresholds are configurable per onboarding journey and per market without an SDK update.

Document Tamper Detection

Hologram, UV, MRZ, and font-geometry checks catch physical and digital tampering. AI-generated document forgeries and template substitution are flagged at OCR time.

Behavioural Biometrics

Micro-expressions, blinking cadence, pupil movement, and gaze are scored on every capture. Typing rhythm and interaction patterns identify session anomalies before submission.

Deepfake Detection

Multi-stream RGB and frequency analysis detect AI-generated and manipulated media. Behavioral signals catch synthetic inputs that pass static checks.

Replay & Synthetic Detection

Tamper-evident capture signals flag screenshots, screen recordings, and injected video streams. Generator-style artefacts and synthetic patterns are caught before they progress into the verification record.

From Capture to Risk Score in Under Three Seconds

Four parallel signal streams in one pipeline

STEP 01

Capture

Collect biometric, document, device, IP, and session signals through the SDK.

STEP 02

Analyse

Run deepfake, spoof, tamper, behavioural, and device-risk models in parallel.

STEP 03

Score Risk

Aggregate signals into a unified risk score with configured decision thresholds.

STEP 04

Decide & Audit

Return explainable decisions with forensic re-examination inside the customer AWS environment.

Book Personalized Demo

Trust, built-in. From first verification to every future interaction

One Platform. Full Identity Lifecycle

Request Demo

User Verification

Onboard and authenticate legitimate users in seconds

Business Onboarding

Perform global KYB and due diligence with confidence

Authentication

Detect and block fraud at every touchpoint

monitoring & Compliance

Proactively manage risk and maintain regulatory compliance

User Verification

Onboard and authenticate legitimate users in seconds.

Face Verification

Confirm user identity and prevent spoofing with advanced 3D liveness detection and face verification.

Address Verification

Instantly confirm a user's address from utility bills, bank statements, and other documents against global database.

Document Verification

Instantly verify government-issued identity documents from over 230 countries and territories.

Age Verification

Reliably verify user age to meet regulatory requirements and protect your platform.

VideoIdent

Conduct real-time, agent-led identity verification through live video interviews for high-assurance KYC.

Fast ID

Achieve near-instant identity verification for low-risk users using minimal data points.

eIDV

Confirm user details against trusted government and financial data sources for added confidence.

NFC Verification

Read the secure chip in a passport with a simple phone tap for the highest identity assurance.

Consent Verification

Capture clear proof that your users agree to be verified, building trust and ensuring compliance.

Business Onboarding

Perform global KYB and due diligence with confidence

Business Verification

Automate the verification of business entities by checking data from global corporate registries.

Due Diligence

Streamline your enhanced due diligence process with customizable risk assessment and data collection.

Investor Verification

Securely verify the identity and accreditation status of investors for your platform.

E-Signature

Finalise agreements and sign up new users with secure, legally binding e-signatures.

Authentication

Detect and block fraud at every touchpoint.

Behavioural Biometrics

Silently confirm it’s your user based on their unique interaction patterns.

Device Intelligence

Identify devices in real-time by analysing unique attributes to block fraud.

Multi-Factor Authentication

Add a critical layer of security to user logins and high-risk actions.

monitoring & Compliance

Proactively manage risk and maintain regulatory compliance with continuous user and transaction monitoring.

AML Screening

Screen users and businesses against global sanctions, PEPs, and adverse media watchlists in real-time.

User Risk Assessment

Generate dynamic risk scores for every user based on their profile, behavior, and transaction history.

Transaction Screening

Monitor financial transactions in real-time to detect and block illicit or fraudulent activity.

Request Demo

Industry Playbook

Bonus Abuse hits every sector differently

Trusted Sellers, Repeat Fraud Blocked

Verify the seller is real at onboarding, then prevent re-joins with duplicate detection and optional 1:N matching across the marketplace.

Explore More Try Now

Don't just take our word for it, hear from our customers

The Confidence Our Clients Share

The future of digital identity is defined by trust, interoperability, and regulatory alignment, so our partnership with Shufti reinforces DevCode Identity's commitment to supporting our global customers with the most secure, best-in-class, complaints identity verification solutions available today.

Combining our Conversion Driven Compliance Orchestration Platform with Shufti's global KYC and IDV capabilities allows our customers not only to navigate complex regulatory demands but also to maintain a seamless customer onboarding experience with the highest achievable conversion rates.

Mark Knighton

Chief Global Development Officer - Global Alliances, DevCode

Trusted. Verified. Awarded

Industry Recognition & Awards

Frequently Asked Questions

What fraud signals are scored in real time?

Biometric spoof, deepfake, document tamper, device fingerprint, behavioural biometric, cross-session ring, and replay or injection signals. All scored at capture time and aggregated into a unified risk score.

How is deepfake fraud detected?

Multi-stream RGB and frequency-domain (DCT) analysis identifies AI-generated faces and manipulated media. Behavioral signatures cross-check synthetic media that passes static texture tests. Detection holds up after compression, screenshots, and re-uploads.

What does device fingerprinting actually capture?

Browser, OS, screen resolution, plugins, GPU, CPU, battery profile, IP, geolocation, and time zone. Inconsistent IP-to-device patterns and emulator, proxy, and VPN masking are flagged in real time.

How are coordinated fraud rings detected?

AI-driven clustering across sessions identifies shared device fingerprints, recycled biometric templates, and serial document reuse. Coordinated activity is surfaced as linked-account rings within seconds rather than isolated alerts.

Are risk thresholds configurable per journey?

Yes. Risk thresholds are configurable per onboarding journey and per market from the back office. Changes apply without an SDK update or a code release.

How does the model adapt to new attack patterns?

False negatives feed a retrain cycle. The deepfake and synthetic-identity models improve within weeks of a new attack vector reaching scale. Release notes accompany every update.

Can past sessions be re-examined when a new threat is identified?

Yes. A forensic audit engine running inside the customer's own AWS account re-examines past liveness sessions and document submissions for spoof, replay, and injection patterns.

Stop Fraud Hidden in Single Signals

Detect coordinated attacks with real-time multi-signal intelligence across biometric, device, document, and behavioural layers.

Book Personalised Demo Contact us