Comprehensive Guide to TrustPath’s Fraud Detection Features

Easy-to-Setup Fraud Detection API

TrustPath’s Fraud Detection API is built for seamless integration, allowing businesses to protect themselves with minimal effort. By analyzing user behavior and transactional data in real time, the API identifies potential threats, enabling businesses to act swiftly.

This API is easy to implement, requiring just a few lines of code. For example:

curl -L 'https://docs.trustpath.io/v1/risk/evaluate' \
-H 'Content-Type: application/json' \
-H 'Accept: application/json' \
--data-raw '{
  "ip": "192.168.1.1",
  "email": "[email protected]",
  "phone": "+1234567890",
  "event_type": "sign_in"
}'

The API delivers detailed risk insights based on the provided data. These include IP analysis to detect suspicious locations or histories, email verification to flag disposable or undeliverable addresses, and device/browser fingerprinting to identify repeat offenders or anomalies. With real-time feedback, businesses can quickly block fraudulent transactions while ensuring a smooth experience for legitimate users.

Threat Signals: The Foundation of Fraud Detection

Threat signals are the backbone of TrustPath’s fraud detection system. They highlight suspicious behaviors or patterns, such as unusual IP activity, mismatched data, or rapid repetitive actions. By monitoring these anomalies, businesses can proactively detect and mitigate fraud.

TrustPath allows businesses to customize their threat signals, tailoring them to specific operational needs. This flexibility ensures accurate detection and minimizes interruptions for legitimate users. By catching fraud early, businesses protect their customers and foster trust.

Default Threat Signals

TrustPath provides pre-configured threat signals to enable immediate fraud protection. These signals cover a wide range of common fraud indicators. For instance, email-related signals can flag disposable or role-based accounts (e.g., [email protected]). IP-related signals can detect Tor exit nodes, proxy servers, and abuse histories. Behavioral signals, such as mismatches between user, billing, and shipping data, also come pre-configured.

These defaults offer immediate protection without additional configuration. Businesses can also modify or expand them as their security needs evolve.

Static Threat Signals: Rule-Based Precision

Static threat signals allow businesses to define specific rules for detecting fraudulent behaviors. These rule-based mechanisms provide granular control, enabling businesses to align their fraud detection strategies with internal security policies.

For example, a business might set a rule to flag transactions exceeding a certain value from unfamiliar IP addresses. With intuitive interfaces, TrustPath makes it simple to implement and adjust these rules as threats evolve.

Relational Threat Signals: Contextual Fraud Detection

Relational threat signals focus on the relationships between data points. They identify inconsistencies or mismatches, such as a billing address that doesn’t align with a shipping address or an IP address that doesn’t match a user’s registered location.

These signals excel at detecting sophisticated fraud attempts that exploit subtle data discrepancies. By analyzing how different data points interact, businesses can catch fraud schemes like triangulation fraud or account takeovers. TrustPath also reduces false positives by considering relationships, ensuring legitimate users are not inconvenienced.

Velocity Threat Signals: Monitoring Activity Rates

Velocity threat signals track the frequency of specific actions, such as login attempts or transaction volumes. These rules are invaluable for detecting abnormal activity patterns that may indicate bot attacks or fraudulent users.

For instance, a velocity rule can flag excessive login attempts from a single IP address within a short timeframe. This helps businesses prevent account takeovers or automated bot attacks. By monitoring activity rates, TrustPath enables businesses to refine security measures without compromising user experience.

Deny List: Blocking Known Threats

The deny list allows businesses to block specific entities, such as IP addresses or email domains, known for fraudulent activity. This feature offers targeted blocking and helps businesses stay ahead of evolving threats.

For example, if an IP address is repeatedly associated with abuse, it can be added to the deny list to prevent further access. TrustPath’s platform streamlines the management of deny lists, making it easy to update entries and protect against bad actors.

Allow List: Enabling Trusted Access

The allow list ensures access is granted only to pre-approved entities, creating a secure “deny all, allow some” environment. This feature enhances security by limiting access to trusted users, devices, or systems.

For instance, businesses can use allow lists to restrict admin tools or sensitive resources to internal IP ranges. By enabling trusted access, allow lists reduce friction for legitimate users while maintaining robust security.

Diverse Threat Signals for Comprehensive Protection

TrustPath enables fraud detection across a wide range of data points, ensuring comprehensive coverage. These include: • User Data: Email, name, address. • Transactional Data: Purchase amount, payment method, shipping details. • Technical Data: IP address, device hash, browser fingerprint.

This multi-dimensional approach allows businesses to detect threats across multiple dimensions of user behavior and transaction data. By configuring rules specific to their needs, businesses can monitor high-value transactions, detect bots, and more.

Conclusion

TrustPath’s fraud detection capabilities provide businesses with a comprehensive and flexible solution to combat online threats. From pre-configured threat signals to advanced customizable rules, TrustPath empowers businesses to protect their operations and maintain customer trust. By leveraging a multi-dimensional approach to fraud detection, businesses can stay ahead of evolving threats, ensuring security and seamless user experiences in an increasingly digital world.

FAQ

What is TrustPath’s Fraud Detection API?

TrustPath’s Fraud Detection API is built for seamless integration, allowing businesses to protect themselves with minimal effort. By analyzing user behavior and transactional data in real time, the API identifies potential threats, enabling businesses to act swiftly.

What are Threat Signals in TrustPath?

Threat signals are the backbone of TrustPath’s fraud detection system. They highlight suspicious behaviors or patterns, such as unusual IP activity, mismatched data, or rapid repetitive actions. By monitoring these anomalies, businesses can proactively detect and mitigate fraud.

What are Static Threat Signals in TrustPath?

Static threat signals allow businesses to define specific rules for detecting fraudulent behaviors. These rule-based mechanisms provide granular control, enabling businesses to align their fraud detection strategies with internal security policies.

What are Relational Threat Signals in TrustPath?

Relational threat signals focus on the relationships between data points. They identify inconsistencies or mismatches, such as a billing address that doesn’t align with a shipping address or an IP address that doesn’t match a user’s registered location.

What are Velocity Threat Signals in TrustPath?

Velocity threat signals track the frequency of specific actions, such as login attempts or transaction volumes. These rules are invaluable for detecting abnormal activity patterns that may indicate bot attacks or fraudulent users.

What is the Deny List in TrustPath?

The deny list allows businesses to block specific entities, such as IP addresses or email domains, known for fraudulent activity. This feature offers targeted blocking and helps businesses stay ahead of evolving threats.

What is the Allow List in TrustPath?

The allow list ensures access is granted only to pre-approved entities, creating a secure “deny all, allow some” environment. This feature enhances security by limiting access to trusted users, devices, or systems.

What data points does TrustPath analyze for fraud detection?

TrustPath enables fraud detection across a wide range of data points, ensuring comprehensive coverage. These include user data (email, name, address), transactional data (purchase amount, payment method, shipping details), and technical data (IP address, device hash, browser fingerprint).

How does TrustPath’s multi-dimensional approach to fraud detection benefit businesses?

TrustPath’s multi-dimensional approach allows businesses to detect threats across multiple dimensions of user behavior and transaction data. By configuring rules specific to their needs, businesses can monitor high-value transactions, detect bots, and more.

How does TrustPath help businesses maintain customer trust while combating fraud?

TrustPath’s fraud detection capabilities provide businesses with a comprehensive and flexible solution to combat online threats. By leveraging a multi-dimensional approach to fraud detection, businesses can stay ahead of evolving threats, ensuring security and seamless user experiences in an increasingly digital world.

How does TrustPath’s fraud detection API work?

TrustPath’s fraud detection API analyzes user behavior and transactional data in real time to identify potential threats. By providing detailed risk insights based on the provided data, the API enables businesses to quickly block fraudulent transactions while ensuring a smooth experience for legitimate users.

How does TrustPath’s Threat Signals feature help businesses detect fraud?

TrustPath’s Threat Signals feature highlights suspicious behaviors or patterns, such as unusual IP activity, mismatched data, or rapid repetitive actions. By monitoring these anomalies, businesses can proactively detect and mitigate fraud.

How does TrustPath’s Static Threat Signals feature help businesses detect fraud?

TrustPath’s Static Threat Signals feature allows businesses to define specific rules for detecting fraudulent behaviors. These rule-based mechanisms provide granular control, enabling businesses to align their fraud detection strategies with internal security policies.

How does TrustPath’s Relational Threat Signals feature help businesses detect fraud?

TrustPath’s Relational Threat Signals feature focuses on the relationships between data points. They identify inconsistencies or mismatches, such as a billing address that doesn’t align with a shipping address or an IP address that doesn’t match a user’s registered location.

How does TrustPath’s Velocity Threat Signals feature help businesses detect fraud?

TrustPath’s Velocity Threat Signals feature tracks the frequency of specific actions, such as login attempts or transaction volumes. These rules are invaluable for detecting abnormal activity patterns that may indicate bot attacks or fraudulent users.

How does TrustPath’s Deny List feature help businesses detect fraud?

TrustPath’s Deny List feature allows businesses to block specific entities, such as IP addresses or email domains, known for fraudulent activity. This feature offers targeted blocking and helps businesses stay ahead of evolving threats.

How does TrustPath’s Allow List feature help businesses detect fraud?

TrustPath’s Allow List feature ensures access is granted only to pre-approved entities, creating a secure “deny all, allow some” environment. This feature enhances security by limiting access to trusted users, devices, or systems.

What are the data points TrustPath analyzes for fraud detection?

TrustPath enables fraud detection across a wide range of data points, ensuring comprehensive coverage. These include user data (email, name, address), transactional data (purchase amount, payment method, shipping details), and technical data (IP address, device hash, browser fingerprint).