Device & Behavioral Intelligence — dEdge

Know who—and what—is behind every interaction

See beyond credentials and transaction data with native device and behavioral intelligence combining fingerprinting, risk assessment, behavior analytics, and edge computing across Android, iOS, and web. dEdge helps teams identify risky environments, connected activity, and abnormal behavior early enough to change the decision.

See dEdge in action →

100+ device signals across Android, iOS, and web

Fraud & Risk Platform/Device & Behavioral Intelligence — dEdge
Solution Pillars

Build a richer device risk profile

Evaluate device, browser, and behavioral signals together to see what static identity and transaction data alone cannot show.

See the device

Build a richer device risk profile

Evaluate device and browser attributes including user agent, browser type and plugins, current URL/referrer, OS and timezone, language settings, screen dimensions/resolution/color depth/pixel ratio, cookies and storage support, CPU and memory, graphics information, device type, and integrity indicators such as incognito mode, WebDriver, ad blocking, and suspicious browser or OS changes.

Device & browser fingerprinting · integrity indicators
See the behavior

Recognize when the interaction itself looks wrong

Use behavioral biometrics like typing speed, paste, autofill, mouse movement, click timing, page duration, navigation, and session-switching behavior to add context that static identity or transaction fields cannot provide alone.

Behavioral biometrics · session analytics
See automation and tampering

Surface environments designed to evade controls

Detect specific automation indicators like bot patterns, browser automation, WebDriver, emulator/cloud-phone, app-cloning, hooking, tampering, and other integrity indicators before they blend into downstream activity.

Bot & automation detection · anti-tampering
Connect activity across entities

Turn a device into network intelligence

Produce persistent device IDs that can be used with account and entity identifiers to link devices, accounts, identities, IPs, and other entities to reveal shared infrastructure and coordinated behavior across seemingly separate users and sessions.

Persistent device IDs · cross-entity linkage
Product Proof

Show the signals behind the risk

Use an actual device profile, behavioral signal view, and linked-device graph to make the intelligence tangible — from SDK/event collection, through device and behavior signals, to a risk score and downstream action.

SDK telemetry
→
Device ID
+ risk
→
Behavioral
signals
→
Rules · ML ·
Graph
→
Decision +
linkage
Illustrative signal-flow diagram — pair with a real device-profile / signal-taxonomy / linked-entity graph screenshot when available (see the FY26 dEdge Master Deck, internal).
How It Works

From session telemetry to a real-time risk signal

1

SDK collects device, browser, OS, hardware, network/IP, geolocation, integrity, and session-behavior data.

2

SDK initialization and token generation are followed by device-ID, device-risk, and behavioral-signal generation.

3

The customer backend sends the token to DataVisor; returned device and behavioral risk signals feed rules, models, and actioning.

4

Persistent device IDs and shared device/account context support linkage across sessions and accounts.

Device intelligence connected to the fraud platform

Give every signal more context

dEdge combines device fingerprinting, behavioral intelligence, risk assessment, and edge computing in one native layer for mobile and web. It becomes more powerful when evaluated alongside transaction history, identity signals, unsupervised ML, and Knowledge Graph relationships in the same risk decision.

Put It To Work

Apply device and behavior intelligence where identity can be manipulated

Strengthen specific use cases using linked devices, shared infrastructure, and coordinated behavior — catching risk earlier in the journey.

Account Opening Application Fraud Account Takeover Credential Stuffing Fraud Ring Detection Mule Detection
Proof & Outcomes

Prove the lift from richer context

Detection & friction metrics pending — do not publish as-is
100+
Device signals available across Android, iOS, and web

Lead with the available device-signal count. Specific detection, false-positive, or customer-friction improvement metrics are pending and should be added here once approved.

Built To Defend The Signal

Protect the integrity of client-side intelligence

dEdge is designed to keep device and behavioral intelligence trustworthy from collection through decisioning, even in adversarial environments.

  • Encrypted and signed tokens
  • HTTPS transport security
  • Key-based authentication or IP allowlisting
  • Per-device encryption keys
  • Anti-spoofing, anti-tampering, and obfuscation / reverse-engineering protection
FAQ

Common questions

What signals does dEdge collect?

dEdge supports a broad set of device, browser, network, integrity, automation, and behavioral signals. Approved product materials describe more than 100 device signals.

Can dEdge detect bots, emulators, or tampered environments?

dEdge includes supported indicators for automation and device integrity, including signals associated with emulators, webdriver activity, app cloning, hooking, rooting, and tampering.

How is dEdge used in a fraud decision?

dEdge risk signals can be evaluated alongside rules, machine learning, identity, transaction, and graph intelligence within DataVisor's real-time decisioning layer. To implement, integrate mobile SDKs for Android/iOS or a JavaScript SDK for web, and send the generated token from the customer backend to DataVisor.

See What A Transaction Alone Can't Tell You

Explore the device and behavior behind the event

Walk through a live risk scenario and see how dEdge surfaces device, behavioral, and relationship signals before the decision.

Request a dEdge demo →