Risk Intelligence:
The Signals behind Smarter Trust.

Fraud today is fast, adaptive, and invisible to traditional checks. Static KYC just isn’t enough. That’s why IDnow’s Risk Intelligence surfaces the subtle signals that reveal real risk – empowering businesses to make smarter, faster, and more confident decisions without adding friction.

Our layered signal analysis helps detect identity fraud, synthetic identities, deepfakes and more – in real time and across the customer journey.

Smarter by design.

Risk Intelligence works quietly in the background, analyzing behavioral, contextual, and technical signals to separate good users from bad actors. Instead of relying on a single data point, we evaluate numerous signals in parallel — building a holistic picture of risk at onboarding, during login, or even mid-session.

Whether you use IDnow standalone or alongside your own fraud stack, our signals are modular, real-time, and designed to enhance both security and experience.

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What we analyze

Explore the signals powering our real-time fraud prevention

Our solutions continuously cross-reference data across the identity verification lifecycle to spot patterns and prevent repeat attacks. We can detect synthetic identities and coordinated fraud rings by identifying suspicious reuse of faces, templates, devices, and data—even when the individual signals appear legitimate. This intelligence is updated constantly, helping you stop identity theft before it happens and reduce downstream fraud.

Reality Check: Fraud in Action

A user uploads a valid-looking ID photo — but behind the scenes, that same image has appeared across multiple onboarding attempts with different names and birthdates. In other sessions, a reused ID number pops up again, subtly altered or tied to a different document template. 360 Signals connects these fragments across sessions.

Our technology inspects device behavior, configuration, and integrity to uncover signs of spoofing, automation, or tampering. By analyzing numerous technical indicators, we help you detect emulators, rooted devices, and other high-risk environments — without impacting legitimate users.

Reality Check: Fraud in Action

A user signs up from a mobile device — but it turns out to be an emulator with identical device attributes to five previous high-risk sessions. Or a jailbroken phone accesses an onboarding flow that’s typically used only by corporate clients. Device Intelligence spots these red flags in real time, identifying risk before a transaction is approved or an account is opened.

We use geolocation, IP, and network metadata to detect evasion tactics like VPNs, spoofing tools, and mismatched geographies. When location doesn’t match the claimed identity or behavior, our tools raise the alert — without interrupting trusted user flows.

Reality Check: Fraud in Action

A user applies for an EU-regulated product but is logging in via a TOR network routed through Southeast Asia — far outside the registered address. Or an IP flagged for mass registration attempts suddenly appears under a different user ID. These inconsistencies reveal location manipulation that often signals account farming or organized fraud.

An email address can reveal a lot about its user. We assess reputation, age, and usage history to determine how trustworthy an address is — identifying throwaway accounts, bot signups, or synthetic identities. This lightweight layer of intelligence helps you weed out risk early in the funnel, without adding friction.

Reality Check: Fraud in Action

A user registers with an email address created just hours earlier — using a disposable domain known for spam and fraud. Or multiple signups use different addresses, but all resolve to the same IP and show near-identical interaction patterns. Email Risk flags these low-trust accounts instantly, stopping them before they move further down the funnel.

Phone numbers are often used as a trust signal — but they’re not all equal. Our analysis looks at tenure, carrier type, SIM swap activity and number behavior to identify high-risk or compromised numbers, helping you add context to SMS-based authentication or use as a standalone signal for identity trust scoring.

Reality Check: Fraud in Action

A phone number is provided for 2FA, but it’s linked to a SIM swap just 24 hours earlier – a known tactic in account takeover fraud. Or the number is registered with a VoIP provider used in hundreds of previous scam attempts. Phone Number Risk catches these subtle patterns, helping you break the chain before it starts.

Continuous Trust:
Protection that evolves with your users.

Trust isn’t static — a verified user today could become a compromised account tomorrow. IDnow’s signals are designed not just for onboarding, but for ongoing monitoring and behavioural change detection across the customer lifecycle.

Spot social engineering, synthetic identities, deepfakes and other emerging typologies before it leads to loss.

Learn more about how we solve fraud prevention and security

Designed to fit your stack.

Whether you use IDnow’s full identity flow or integrate our signals into your own risk engine, we deliver:

Modular signal access via API

Scalable performance across regions

Privacy-compliant data enrichment

Seamless orchestration via the IDnow Hub

AI-Driven Detection – built to stay ahead.

Our signals don’t just run — they learn. IDnow applies machine learning to detect emerging fraud typologies, refine decisioning, and reduce false positives over time.We train continuously on diverse threat data to ensure your risk controls evolve as fast as the fraud.

Ready to outsmart fraud in real time?

Discover how IDnow Risk Intelligence can help you stop fraud before it starts – and protect trust as it grows.

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