Stripe Radar

Overview

Stripe Radar is a fraud detection and prevention system designed to protect businesses using the Stripe payments platform. It was launched in 2014 as an integrated component of Stripe's offerings. Radar employs machine learning algorithms, which are trained on data from millions of transactions processed across the Stripe network, to assess the risk level of each payment. This collective intelligence approach is intended to enhance the accuracy of fraud detection as the network grows.

The system is primarily suitable for e-commerce businesses, marketplaces, and other online platforms that process card payments and aim to minimize financial losses due to fraudulent transactions and associated chargebacks. Stripe Radar provides two main product offerings: the standard Stripe Radar, which is included with Stripe Payments, and Stripe Radar for Fraud Teams, which offers additional tools for manual review and advanced rule management.

Developers and technical buyers can integrate Stripe Radar directly into their existing Stripe payment flows without requiring separate integrations. The system automatically screens transactions for suspicious activity, assigning a risk score to each. Users can define custom rules through the Stripe Dashboard or via the API to block, allow, or review transactions based on specific criteria such as card properties, IP addresses, or customer history. This granular control allows businesses to tailor their fraud prevention strategies to their unique risk profiles and operational requirements. Radar also includes tools for managing disputes and chargebacks, providing insights into the reasons for disputes and helping businesses respond effectively.

Stripe Radar's deep integration with the Stripe ecosystem means that it benefits from the same compliance certifications, including PCI DSS Level 1, SOC 1, SOC 2, and GDPR, simplifying the compliance burden for businesses utilizing the service. The developer experience is characterized by its seamless enablement for existing Stripe users, with comprehensive documentation and SDKs available for various programming languages to facilitate rule customization and data access.

Key features

• Machine Learning Fraud Detection: Utilizes algorithms trained on data from the Stripe network to identify and score suspicious transactions automatically.
• Customizable Rulesets: Allows businesses to create and manage their own rules to block, review, or allow payments based on specific risk factors, accessible via the Stripe API or Dashboard.
• Adaptive Risk Scoring: Dynamically adjusts risk assessments based on evolving fraud patterns and transaction histories.
• Radar for Fraud Teams: An enhanced offering providing additional tools for manual review queues, advanced analytics, and enhanced rule management.
• Dispute Management Tools: Provides insights into chargeback reasons and tools to assist in responding to disputes, aiming to reduce lost revenue.
• Card Account Updater: Automatically updates saved card details for recurring payments, helping to reduce declines due to expired or reissued cards.
• Integration with Stripe Payments: Seamlessly embedded within the Stripe platform, requiring no separate integration for existing Stripe users.

Pricing

Stripe Radar's pricing structure is generally layered on top of Stripe's standard payment processing fees.

For detailed and up-to-date pricing information, refer to the official Stripe Radar pricing page.

Common integrations

Stripe Radar is primarily integrated with the broader Stripe ecosystem, leveraging its connectivity to other services:

• Stripe Payments: The core integration, where Radar automatically screens all transactions processed through Stripe's payment gateway.
• Stripe Connect: For platforms and marketplaces, Radar can be configured to manage fraud detection for connected accounts, as detailed in the Stripe Connect documentation.
• Stripe Billing: Integrates with subscription management to help prevent fraud in recurring payment scenarios, documented in Stripe Billing guides.
• Stripe Checkout: Pre-built payment pages can utilize Radar's fraud protection features without additional configuration.

Alternatives

• Signifyd: Offers guaranteed fraud protection, taking on the financial liability for approved transactions that turn out to be fraudulent.
• Forter: Provides real-time fraud prevention across the entire customer journey, including account protection and returns abuse prevention.
• Sift: A digital trust and safety platform that leverages machine learning to detect and prevent fraud across various channels, including payments, content, and promotions.

Getting started

To get started with Stripe Radar, particularly for defining custom rules, you can use the Stripe API. The following Python example demonstrates how to create a Radar rule that blocks payments if the card's country code does not match the customer's IP country, assuming you have the necessary metadata available.

import stripe

stripe.api_key = 'YOUR_STRIPE_SECRET_KEY'

# Example: Create a Radar rule to block payments if card country does not match IP country
# Note: This is a simplified example. Actual rule creation might involve more complex conditions
# and is typically managed in the Stripe Dashboard or through specific API endpoints for rules.
# The Radar API primarily focuses on evaluating payments and retrieving reviews, 
# while rule management is often done via the Dashboard or specific Rules API if available.

# For illustrative purposes, if you were to evaluate a payment directly (though Radar does this automatically)
# and wanted to understand its risk, you'd look at the Charge object.

# To demonstrate interacting with a payment that Radar would screen, here's a basic charge creation
try:
    charge = stripe.Charge.create(
        amount=2000, # $20.00
        currency='usd',
        source='tok_visa', # Use a test token
        description='Example charge for testing Radar',
        metadata={
            'customer_ip_country': 'US',
            'card_country': 'CA' # Simulate a mismatch
        }
    )
    print(f"Charge created: {charge.id}")
    print(f"Radar risk level: {charge.outcome.risk_level}")
    print(f"Radar risk score: {charge.outcome.risk_score}")
except stripe.error.CardError as e:
    # Since Radar can block, you might get a card error indicating the block
    print(f"Error creating charge: {e}")
    print(f"Error message: {e.user_message}")
    print(f"Decline code: {e.decline_code}")

# For actual rule creation and management, refer to the Stripe Dashboard's Radar section
# or the Stripe API documentation for Radar rules if programmatic management is desired.
# The primary API interaction for Radar is often around retrieving reviews or managing disputes.

# Example of retrieving a review (if a payment was flagged for review)
# You would typically get the review ID from a webhook event or a Charge object.
# review_id = 'prv_12345'
# try:
#     review = stripe.Review.retrieve(review_id)
#     print(f"Review status: {review.status}")
# except stripe.error.StripeError as e:
#     print(f"Error retrieving review: {e}")

This Python code snippet illustrates how you would interact with Stripe's core payments API, which Radar automatically screens. Custom rule definitions are typically managed through the Stripe Dashboard or through specific API endpoints for Radar rules, allowing for declarative fraud prevention logic. The developer experience notes on Stripe's documentation emphasize the ease of enabling Radar for existing Stripe users and the flexibility offered by custom rule definition via the API or dashboard.