Riskified for E-commerce Fraud Prevention and Chargeback Guarantee

Overview

Riskified provides an AI-driven platform for e-commerce fraud prevention, focusing on mitigating financial losses and improving customer experience. The platform analyzes various data points during online transactions to distinguish legitimate customers from fraudsters. This analysis helps merchants approve more orders that might otherwise be mistakenly declined, thereby increasing conversion rates and revenue.

Riskified's core offering includes a chargeback guarantee, where the company assumes liability for any fraudulent chargebacks on orders it approves. This shifts the financial risk from the merchant to Riskified, providing a predictable cost structure for fraud management. The technology employs machine learning models that continuously adapt to new fraud patterns, aiming to provide real-time decisioning on transaction legitimacy.

Beyond transaction fraud, Riskified also addresses challenges such as account takeover (ATO) and policy abuse. Account takeover protection involves monitoring user behavior and login attempts to identify and block unauthorized access to customer accounts. Policy abuse detection targets behaviors like coupon misuse, promotional abuse, or returns abuse, helping merchants enforce their terms and conditions more effectively. The platform is designed for large-scale e-commerce operations, aiming to integrate with existing order management and payment systems. Merchants seeking to offload fraud liability and optimize their order approval rates are the primary audience for Riskified's services. For example, similar fraud detection mechanisms are also offered by competitors such as Signifyd's fraud protection guarantee, which also provides chargeback protection.

Key features

• Fraud Prevention: Utilizes machine learning to analyze transaction data and identify fraudulent orders in real-time.
• Chargeback Guarantee: Assumes financial liability for fraudulent chargebacks on approved orders, protecting merchants from losses.
• Account Protection: Detects and prevents account takeover attempts, safeguarding customer accounts from unauthorized access.
• Policy Abuse Detection: Identifies and mitigates various forms of policy abuse, such as promotional fraud, returns abuse, and reseller abuse.
• Adaptive AI Models: Continuously updates its machine learning algorithms to adapt to evolving fraud tactics and patterns.
• Real-time Decisioning: Provides immediate decisions on transaction legitimacy, enabling faster order fulfillment.
• Customizable Rules: Allows merchants to define specific rules and thresholds to complement the AI models.
• Integration Capabilities: Offers APIs for integration with e-commerce platforms, payment gateways, and order management systems.

Pricing

Riskified operates on a custom enterprise pricing model. Specific pricing details are not publicly disclosed and are typically provided to prospective clients after an initial consultation to assess their specific needs and transaction volumes. This model allows for tailored solutions based on the merchant's industry, risk profile, and desired service level.

For more information, prospective customers are directed to the Riskified contact page.

Common integrations

Riskified offers API integrations designed to connect with various e-commerce platforms, payment gateways, and order management systems. While specific public documentation is typically provided post-sales engagement, their platform is built to integrate with common e-commerce ecosystems.

• E-commerce Platforms: Integration with platforms like Shopify, Magento, Salesforce Commerce Cloud, and others to intercept orders for fraud analysis.
• Payment Gateways: Connectivity with payment processors such as Stripe, PayPal, and Adyen to enhance transaction security.
• Order Management Systems (OMS): Integration to streamline the flow of order data and fraud decisions within a merchant's existing operational workflows.
• Customer Relationship Management (CRM) Systems: Potential for data exchange with CRM platforms to enrich customer profiles and fraud detection.
• Warehouse and Fulfillment Systems: Integration to ensure that only legitimate orders are sent for processing and shipping.

Alternatives

• Signifyd: Offers fraud protection and a chargeback guarantee for e-commerce merchants, similar to Riskified's core offering.
• Forter: Provides a fraud prevention platform that leverages identity-based fraud prevention across the customer journey.
• Sift: Delivers a Digital Trust & Safety platform that includes fraud prevention, account protection, and content moderation.

Getting started

While Riskified's API documentation is typically provided after an initial sales engagement, the integration process generally involves sending order data to Riskified for analysis and receiving a decision. Below is a conceptual Python example demonstrating how an e-commerce platform might interact with a hypothetical Riskified-like API endpoint to submit an order for fraud screening.

import requests
import json

# --- Configuration (replace with actual values) ---
RISKIFIED_API_URL = "https://api.riskified.com/v1/orders"
RISKIFIED_API_KEY = "YOUR_RISKIFIED_API_KEY"
MERCHANT_ID = "YOUR_MERCHANT_ID"

# --- Sample Order Data ---
order_data = {
    "order": {
        "id": "ORDER-12345",
        "customer": {
            "email": "[email protected]",
            "first_name": "John",
            "last_name": "Doe",
            "ip_address": "203.0.113.45",
            "created_at": "2026-05-28T10:00:00Z"
        },
        "shipping_address": {
            "address1": "123 Main St",
            ""city": "Anytown",
            "province": "CA",
            "country": "US",
            "zip_code": "90210"
        },
        "billing_address": {
            "address1": "123 Main St",
            "city": "Anytown",
            "province": "CA",
            "country": "US",
            "zip_code": "90210"
        },
        "line_items": [
            {
                "product_id": "PROD-001",
                "variant_id": "VAR-001",
                "name": "Widget A",
                "price": 50.00,
                "quantity": 1
            }
        ],
        "total_price": 55.00,
        "currency": "USD",
        "gateway": "stripe",
        "payment_details": {
            "credit_card_bin": "411111",
            "credit_card_last4": "1111",
            "card_brand": "Visa"
        },
        "created_at": "2026-05-28T10:05:00Z"
    }
}

# --- API Request Headers ---
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {RISKIFIED_API_KEY}",
    "X-Riskified-Merchant-Id": MERCHANT_ID
}

# --- Send Order to Riskified ---
try:
    response = requests.post(RISKIFIED_API_URL, data=json.dumps(order_data), headers=headers)
    response.raise_for_status() # Raise an exception for HTTP errors

    decision = response.json()
    print("Riskified Decision:")
    print(json.dumps(decision, indent=2))

    if decision.get("order", {}).get("status") == "approved":
        print("Order approved by Riskified. Proceed with fulfillment.")
    else:
        print("Order declined or challenged by Riskified. Review manually or cancel.")

except requests.exceptions.RequestException as e:
    print(f"API request failed: {e}")
except json.JSONDecodeError:
    print(f"Failed to decode JSON response: {response.text}")

This Python snippet illustrates sending an order object, including customer, shipping, billing, and payment details, to a hypothetical Riskified API endpoint. The API would then return a decision (e.g., 'approved', 'declined', 'challenged') along with additional insights. Merchants would integrate this into their order processing workflow, typically after payment authorization but before fulfillment, to make decisions based on Riskified's fraud assessment.