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Device Intelligence

Real-Time Fraud Detection for Web & Mobile

SEON’s Device Intelligence solution offers comprehensive real-time device monitoring and risk assessment to prevent fraud. It integrates seamlessly across web and mobile platforms, providing deep insights into user devices and behavior. With SEON’s Device Intelligence, you can uniquely identify every device that interacts with your system, ensuring you detect fraud before it impacts your business.

 

Why SEON Device Intelligence?

SEON’s Device Intelligence solution allows businesses to:

  • Identify devices in real-time using unique fingerprints across web and mobile platforms.
  • Uncover fake locations, including VPNs, proxies, and simulated location tools, ensuring more accurate data collection.
  • Detect suspicious behavior by analyzing device characteristics, user interactions, network data, and supporting behavioral biometrics to identify bot automation, phishing/vhising, and remote access activity.
  • Ensure device integrity by identifying rooted devices, emulators, and app cloning attempts, which are often used in fraudulent activities.
  • Seamlessly integrate with web, mobile, and cross-platform applications, ensuring robust protection across all user touchpoints and compliance with Google Play and Apple Store requirements.

 

SEON Device Intelligence Capabilities

1. Device Identification

SEON uses device fingerprinting to generate unique IDs for every device that interacts with your platform, even across different environments (browsers, mobile apps, etc.). This fingerprint helps you track device activity over time, detect recurring patterns, and spot potential fraud.

  • Track unique devices across web and mobile platforms, linking activity across multiple sessions.
  • Prevent multi-accounting and identify devices attempting to exploit your system.
  • Detect device spoofing through detailed fingerprinting and behavioral analysis to identify untrustful devices.

For detailed guidance on device identification please visit our dedicated knowledge base: Understanding Hashes 

2. Device Safety and Security Checks

SEON provides advanced device safety insights, allowing you to verify the security status of a device before allowing access to your platform. This ensures that your users are legitimate and not using compromised devices.

  • Private browsing detection: Flags incognito mode or private browsing.
  • Jailbreak/root detection: Identifies mobile devices that are jailbroken or rooted, a common signal of fraud.
  • Emulator detection: Flags emulators or virtual machines.
  • Biometric & passcode verification: Confirms security features on mobile devices.

3. Real-Time Location Tracking

SEON’s device intelligence tracks the real-time location of users, allowing you to ensure that their geolocation matches expected behavior. This is essential for spotting suspicious access attempts or potential fraud.

  • Geolocation matching: Monitors the device's geographic location from multiple datapoints.
  • Simulated location detection: Detects fake or spoofed locations.

For detailed guidance on behavior signals please visit our dedicated knowledge base: Understanding geolocation data with Device Fingerprinting

4. Network and Connection Monitoring

Monitoring the user's network and connection details provides additional layers of defense. SEON tracks various network-related data points to identify suspicious activity and prevent fraud.

  • IP address & DNS tracking: Ensures consistency in network data.
  • Proxy & VPN detection: Identifies users hiding behind anonymizing services.

For more details on network analysis please visit our dedicated knowledge base: Residential proxy and VPN detection

5. Analyzing Software, Hardware Environment, and Screen Data

SEON’s Device Intelligence solution goes beyond basic device fingerprinting by thoroughly analyzing the software, hardware, and screen data of each user device. These checks help you verify the authenticity of devices and detect potential tampering or manipulation, ensuring a more secure user environment.

  • Software Environment Analysis: SEON monitors the operating system, browser, and installed software versions to detect inconsistencies or unapproved modifications. Devices with outdated, suspicious, or manipulated software environments may be flagged for additional scrutiny, as these can indicate compromised systems or attempts to bypass security protocols.
  • Hardware Configuration Checks: SEON collects data on key hardware components such as CPU, RAM, and device models. It compares this information with expected configurations to detect anomalies that could signal the use of emulators, virtual machines, or tampered hardware. This ensures that only legitimate, unaltered devices are granted access to your platform.
  • Screen and Display Analysis: By analyzing screen resolution, pixel density, and window size, SEON can detect unusual display setups that are often associated with bots or automated systems. Non-standard resolutions or suspicious window behaviors may indicate that a device is operating in a virtual machine or being used for fraudulent purposes.

5. Behavioral & Environmental Analysis

SEON’s SDKs for web, Android, and iOS use a multi-layered approach to detect fraud by analyzing a combination of user interactions, input patterns, sensor data, and device characteristics. These signals allow SEON to monitor user behavior in real-time and flag deviations that could indicate fraudulent or automated activities. The SDKs continuously collect and process this data during sessions, providing valuable insights into potential security risks.

  • Interaction Analysis: Monitoring user actions (mouse movements, touch gestures) and form completion. Erratic patterns or rapid input may indicate automation.
  • Input Analysis: Examining typing and tapping behaviors to detect bots, with a focus on irregularities in keystrokes or autofill use.
  • Sensor Analysis: Tracking motion sensors, and environmental data to identify unusual device handling or device farms.
  • Device Characteristics: Analyzing device metadata and environment details to spot signs of fraud, like proxies or emulators.

For detailed guidance on behavior signals please visit our dedicated knowledge base: Understanding behavioral data signals with device intelligence

6. Geofencing for Location-Based Regulation Compliance (iGaming)

SEON’s geofencing integrates with real-time location tracking to validate that transactions align with local regulations, ensuring compliance while blocking suspicious attempts to manipulate location data.

For industries like iGaming, where geographic restrictions are critical due to local laws and regulations, SEON’s geofencing capabilities provide essential oversight:

  • Transaction management based on real location data: SEON ensures that transactions are initiated from approved geographic regions, preventing users from bypassing location-based restrictions with VPNs or spoofed locations.
  • Regulatory compliance for location-based laws: In industries like iGaming, users are often subject to specific regulations based on their physical location. SEON’s geofencing tools monitor whether users remain within legally approved regions for betting or gambling, blocking transactions when users attempt to bypass these rules.

For detailed guidance on geofencing with SEON Device Intelligence: Geolocation API for iGaming

 

How SEON Device Intelligence Works

SEON’s Device Intelligence integrates seamlessly into critical stages of your platform’s user journey—whether for web or mobile applications—to monitor interactions, detect suspicious behavior, and prevent fraud in real time. By tracking unique devices and analyzing patterns, SEON helps identify and block fraudulent activities at key points like registration, login, checkout, and general usage. It also incorporates behavior signals and geofencing for deeper security insights.

Easy Integration Across Platforms

SEON’s lightweight JavaScript SDK for web applications and native SDKs for iOS and Android make it easy to integrate device fingerprinting into any platform. This ensures seamless fraud detection across both web and mobile environments, with full support for tracking behavioral signals and enforcing geofencing rules.

SDK integration

  • JavaScript SDK for web applications: SEON’s lightweight JavaScript SDK integrates effortlessly into your web platform, allowing you to capture real-time device data as users interact with your site.
  • Native SDKs for iOS and Android: Deep integration with mobile applications via native SDKs ensures comprehensive device data collection, including geolocation, hardware details, and sensor information, without impacting app performance.
  • React Native & Flutter Plugins: SEON offers React Native and Flutter plugins to support cross-platform mobile applications. These plugins provide seamless integration, enabling device fingerprinting in hybrid mobile environments, ensuring that both iOS and Android apps are covered under one implementation.

Data Collection

Collecting device intelligence and network data

  • Device identifiers collecting unique data points and generating different unique identifiers and hashes
  • Network data including IP address, ISP, connection type, and geolocation.
  • Device characteristics like the operating system, browser type, screen resolution, fonts, and advanced identifiers like WebGL and Canvas fingerprints.
  • Behavior data collection for interaction analysis
  • Geolocation data collection for geofencing and true location based decision-making
  • Device and application integrity identifying mobile devices that are jailbroken or rooted, and deep analysis of environment to detect modified and cloned applications 

Collecting behavioral data with SDK

  • For web environments, integrate the JavaScript SDK on high-interaction pages (login, registration, checkout) using seon.init() on page load and getSession() on form submission to capture sufficient data. Without this setup, incomplete analysis may affect fraud detection accuracy. You can also customize data collection by targeting specific UI elements via the behavioralDataCollection option.
  • For Android applications (version 6.5.0+), use startBehaviourMonitoring and stopBehaviourMonitoring within key user flows (login, registration, payment) to ensure proper monitoring. If stopBehaviourMonitoring is called without 

Data Transfer and Server-Side Analysis

After data collection, the encrypted session containing the device fingerprint and all associated metrics is sent to SEON’s Fraud API for server-side analysis. Here, SEON’s system processes the data in real time, flagging potential fraud indicators such as:

  • Browser privacy tools (incognito mode or manipulated browser settings).
  • Rooted or emulated devices, which suggest tampered environments.
  • VPNs and proxies, which attempt to mask the true geolocation.
  • Automation or bot activity, identified through unusual navigation patterns and non-human interaction with forms.

These fraud indicators are automatically flagged for further assessment using SEON’s device intelligence analysis and sophisticated algorithms embedded in our fraud prevention platform. These flags are crucial in identifying abnormal activities that deviate from typical user behavior, allowing businesses to respond proactively to fraud attempts. By leveraging these flags, clients can prevent fraudulent transactions and improve decision-making based on real-time data.

Risk Identification and Scoring Engine

SEON’s Scoring Engine then evaluates the collected data against customized fraud prevention rules set by the client. It generates a risk score that assesses whether the activity is suspicious or legitimate. Based on this score, SEON can make real-time decisions at critical points such as registration, login, transaction, or checkout. For instance:

  • At registration, the system can flag users creating multiple accounts from the same device or using a VPN.
  • At login, if a suspicious or unfamiliar device is detected, SEON can trigger additional authentication measures.
  • At checkout, mismatches between the user’s geolocation, IP address, and billing/shipping details may raise alerts, preventing fraudulent transactions.

Real-Time Response and Prevention

Clients receive the system’s real-time response, which includes risk scores and any associated fraud flags. Based on this feedback, the system can decide to:

  • Approve legitimate transactions.
  • Request additional verification (such as multi-factor authentication).
  • Block suspicious activity outright.

This ensures immediate fraud prevention at critical interaction points, minimizing risk while ensuring a smooth experience for legitimate users.

Accessing Results on the Admin Panel

After the analysis, clients can access detailed results via SEON’s Admin Panel. The device widget provides a comprehensive view of each session or transaction, allowing clients to:

  • Track historical device data and monitor device activity across multiple accounts.
  • Visualize geolocation data and network connections for each device.
  • Apply filters to identify patterns, such as recurring VPN or proxy use, or suspicious device behaviors, helping further optimize fraud prevention.

Continuous Fraud Detection Optimization

The Admin Panel also allows clients to fine-tune their fraud detection strategy by adjusting rules based on evolving fraud patterns. For example, geofencing rules can be adapted to restrict or monitor transactions from high-risk regions, and automated interactions can be more finely detected, further refining how fraud is identified and blocked.

By integrating SEON’s device intelligence, clients benefit from robust, real-time fraud detection across the entire user journey, including registration, login, checkout, and transaction monitoring. This comprehensive system enables precise detection and mitigation of fraud, while maintaining a seamless experience for trustworthy users.

 

SEON Scoring Engine: Automating Risk Assessment

The Scoring Engine automates fraud detection by generating risk scores based on device data, user behavior, and network insights. It simplifies decision-making and provides real-time risk assessments for every user interaction.

How It Works

SEON’s Scoring Engine evaluates data points collected from devices, user activity, and network behavior. It applies customizable rules to generate a risk score that reflects the likelihood of fraudulent behavior. Higher risk scores trigger automated actions such as additional verification or transaction blocking.

Key Benefits

  • Customizable fraud rules: Tailor risk thresholds and fraud detection settings.
  • Real-time decisions: Automatically approve, deny, or flag actions based on risk scores.
  • Dynamic risk scoring: Scores adjust as new data is collected, ensuring accuracy.

 

Use Cases for SEON Device Intelligence Engine

SEON’s Device Intelligence and Scoring Engine work together to protect your platform from a variety of fraud tactics by leveraging real-time device data and behavioral analysis.

1. Account Takeover (ATO) Prevention

SEON helps prevent unauthorized access by monitoring login attempts and detecting unusual behaviors:

  • Device fingerprinting checks if the device is familiar or new to the account.
  • Behavioral analysis monitors abnormal interactions, such as sudden changes in login location or erratic usage patterns, triggering multi-factor authentication (MFA) or account lockout for suspicious logins.

2. Multi-Accounting Detection

SEON identifies when users attempt to create multiple accounts to exploit offers or evade bans:

  • Cross-device tracking flags devices being reused to create multiple accounts.
  • Behavioral signals analyze interactions during registration, identifying automated patterns or bots often used to create bulk accounts. This prevents abuse of promotional offers or gaming systems.

3. Transaction Fraud Prevention

SEON ensures real-time protection during high-risk transactions:

  • Transaction risk scoring evaluates each transaction based on the device’s risk profile, including location, network connection, and user behavior.
  • Real-time alerts flag transactions from untrusted devices or high-risk locations, allowing businesses to pause or review before completing the payment.

4. Synthetic Identity Fraud Detection

SEON helps prevent fake identity fraud by combining device intelligence with other verification methods:

  • Device tracking identifies if a device is tied to multiple suspicious accounts.
  • Behavior analysis flags inconsistencies in user behavior and interaction speed, which may indicate the use of fake identities or automated scripts during the signup process.