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    AI Agent Approve

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    Sold by: Riskified 
    Deployed on AWS
    Riskified's proven fraud and abuse protection, adapted for the age of AI shopping agents. AI Agent Approve raises approval rates, boosts authorization rates, slashes returns abuse, and stops promo abuse, now adapted to a world of agentic shoppers. This product delivers clear approve/decline/friction responses via MCP protocols, enabling both merchant-built and third-party agents to receive structured decisions and navigate verification workflows programmatically. The same Riskified value that protects billions in human transactions now ensures legitimate shopping agents thrive while blocking malicious automation.
    4.4

    Overview

    The e-commerce landscape is undergoing a sea change as the use of AI shopping agents becomes mainstream. From merchant-built assistants to third-party agents from OpenAI, Perplexity, and others, automated shopping is transforming how consumers interact with online stores. But with this transformation comes new challenges: How do you distinguish between legitimate AI agents helping real customers and malicious bots exploiting your systems? How do you apply fraud protection without breaking the automated workflows these agents depend on?

    AI Agent Approve solves these challenges by adapting Riskified's battle-tested fraud and abuse protection for the world of AI agents. For over a decade, Riskified has protected the world's largest merchants from fraud, policy abuse, and chargebacks. Now, that same sophisticated risk assessment engine has been reimagined for agentic commerce.

    How It Works: The system communicates through structured MCP (Model Context Protocol) standards, delivering clear merchant guidance when AI agents interact with your store:

    • Approve: Transactions proceed immediately, maintaining smooth automated flows
    • Decline: Transactions are blocked with clear, interpretable reasoning
    • Friction: Identity verification workflows like SMS confirmation to authorize agent shopping
    • Custom Response Trees: For claims and returns, merchants configure auto-approve/deny logic with intelligent escalation to human agents for borderline cases

    What makes AI Agent Approve uniquely effective is Riskified's massive data foundation and multi-layered intelligence. AI-Based Performance Segmentation continuously evolves to combat emerging threats:

    • Uses AI to dynamically segment the agent population in real-time
    • Automatically adjusts risk thresholds to contain new fraud patterns while minimizing false positives
    • Continuously creates and tests new segments while deprecating outdated ones, ensuring consistent performance as the threat landscape shifts

    Dynamic Multi-Layered Abuse Detection adapts faster than any static rule system:

    • Network-wide graph analyzes patterns across millions of transactions and agent behaviors
    • ML-driven identity resolution connects seemingly unrelated agents to expose coordinated attacks
    • Dynamic risk evaluation adjusts to each merchant's unique risk profile and agent ecosystem
    • Merchants can layer custom logic on top, ensuring flexible protection that evolves with every threat.

    This sophisticated infrastructure, processing hundreds of billions in transactions, now powers real-time decisions for the age of AI commerce.

    Transformative Benefits for Merchants:

    • Higher Approval Rates: Our ML models leverage the full network effect to distinguish helpful shopping assistants from harmful bots, maximizing revenue from legitimate automated transactions while maintaining industry-leading fraud prevention.
    • Boosted Authorization Rates: Pre-authorization filtering removes bad orders before they reach card issuers, improving your reputation with banks and raising the risk threshold at which they'll authorize your transactions - a compound benefit that grows over time.
    • Comprehensive Abuse Prevention: The system identifies and blocks multiple attack vectors:
      • Serial returners exploiting refund policies through automated agents
      • Coordinated promo abuse from agent farms draining promotional budgets
      • Reseller bots using sophisticated patterns to hoard inventory
      • Cross-channel abuse patterns invisible when viewing transactions in isolation
    • Seamless Verification at Scale: When additional verification is needed, programmatic workflows like SMS confirmation maintain security without breaking automation: legitimate users quickly verify while unauthorized agents are stopped.
    • Full Merchant Control: Every decision comes with clear reasoning and data insights. Use Riskified's Decision Studio to adjust risk rules, understand attack patterns, and refine policies with complete visibility into your fraud prevention strategy.

    Built on Riskified's proven infrastructure, AI Agent Approve is a fundamental rethinking of fraud prevention for when your customers are algorithms, not humans.

    The same intelligent decisioning that has protected billions in human transactions now ensures legitimate shopping agents thrive while malicious automation is systematically blocked.

    Highlights

    • Instant Decisioning on AI Agent Actions via MCP: Deliver real-time approve/decline/friction/escalate responses to shopping agents via MCP. Our ML models leverage Riskified's massive network to distinguish legitimate AI assistants from malicious bots, ensuring smooth automated commerce while blocking threats."
    • Dynamic Multi-Layered Protection: Stop evolving agent abuse with AI-powered segmentation that adapts in real-time. Detect coordinated attacks, reseller bots, promo abuse, and returns fraud across network-wide patterns that static rules miss.
    • Boost Approval & Authorization Rates: Maximize revenue by approving more good agents while filtering bad actors before bank authorization. Pre-authorization screening improves issuer relationships, raising approval thresholds and creating compound benefits over time.

    Details

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    Delivery method

    Integration protocol

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    Deployed on AWS
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    Pricing

    AI Agent Approve

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    Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    12-month contract (1)

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    Dimension
    Cost/12 months
    Transaction Fraud Review
    $0.01

    AI Insights

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    Dimensions summary

    This listing uses a single pricing dimension: Transaction Fraud Review, billed by unit. You buy under a contract commitment rather than paying by the hour. Pricing scales with the volume of transactions reviewed for fraud. Each unit covers the review of a transaction, so your cost tracks the number of orders you send for screening. There are no separate tiers or instance sizes to choose from. As your reviewed transaction volume grows, your total cost changes with the number of units consumed.

    Top-of-mind questions for buyers

    One unit covers the review of a single transaction you send for fraud screening. Machine-learning models analyze each order and return an approve or decline decision. Your unit count equals the number of orders submitted for review, so cost tracks the volume of transactions screened.
    Cost scales with the number of transactions you submit for fraud review. Each reviewed order consumes one unit, so more orders means more units billed. There are no separate tiers or instance sizes. Your total tracks the units consumed under your contract.
    The unit meters the fraud review itself, not the outcome. The platform generates an approve or decline decision for each transaction submitted. Because billing is per Transaction Fraud Review unit, review of declined orders consumes units the same way approved orders do. Confirm exact metering details with the vendor.
    www.riskified.com
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    Usage information

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    Delivery details

    API-Based Agents & Tools

    API-Based Agents and Tools integrate through standard web protocols. Your applications can make API calls to access agent capabilities and receive responses.

    Additional details

    Usage instructions

    Riskified MCP Server Usage Guide

    Guide for external users to connect to the Riskified MCP server using mcp-remote for fraud detection.

    📚 Official API Reference: Riskified API Documentation 

    🔗 Quick Setup

    MCP Configuration

    Add to your MCP client configuration:

    { "mcpServers": { "riskified-mcp-server": { "command": "npx", "args": [ "-y", "mcp-remote", "https://api.riskified.com/mcp" ] } } }

    🛠️ Available Tools (9 total)

    Pre-Authorization (3)

    • riskified_decide_pre_auth - Analyze orders before payment
    • riskified_checkout_denied_pre_auth - Report pre-auth denials
    • riskified_get_decision - Retrieve existing decisions

    Post-Authorization (3)

    • riskified_decide_post_auth - Enhanced analysis with AVS/CVV
    • riskified_create_order - Async order creation
    • riskified_checkout_denied_post_auth - Report post-auth denials

    Lifecycle Management (3)

    • riskified_fulfill_order - Report order fulfillment
    • riskified_cancel_order - Report cancellations
    • riskified_refund_order - Process refunds

    📋 Usage Example

    please use the riskified-mcp-server mcp tool and cancel this request:

    { "id": "123e4567-e89b-12d3-a456-426614174000", "cancel_reason": "test", "shop_domain": "your-shop.myshopify.com", "hmac_signature": "generated_hmac_here" }

    🔒 Authentication

    Generate HMAC-SHA256 signatures using your secret key and request body. See the official API authentication docs  for implementation details.

    import hashlib, hmac, json def generate_hmac(order_data, secret_key): body = json.dumps({"order": order_data}, separators=(',', ':')) return hmac.new(secret_key.encode(), body.encode(), hashlib.sha256).hexdigest() input_json = {'id': '123e4567-e89b-12d3-a456-426614174000', 'cancel_reason': 'test'} hmac_signature = generate_hmac(input_json, secret_key) print(hmac_signature)

    Required fields:

    • shop_domain - Your shop domain
    • hmac_signature - HMAC-SHA256 signature of the request body

    ⚡ Response Format

    { "success": true, "decision": "approve|decline|transfer|error", "order_id": "order-12345", "reason": "Low risk profile", "score": 0.15 }

    Decision Values:

    • approve - Low fraud risk, proceed
    • decline - High fraud risk, reject
    • transfer - Manual review required
    • error - Processing error

    🚨 Error Examples

    Authentication Error:

    {"success": false, "decision": "error", "error": "Invalid HMAC signature"}

    Missing Fields:

    {"success": false, "decision": "error", "error": "Order ID is required"}

    🎯 Integration Flow

    1. Pre-Auth - Check fraud risk before payment
    2. Payment - Process with your payment provider
    3. Post-Auth - Enhanced analysis with payment data
    4. Fulfillment - Report shipping details
    5. Lifecycle - Handle cancels/refunds/chargebacks

    🔧 Troubleshooting

    Health Check:

    curl <https://your-riskified-mcp-server.com/health>

    API Test:

    curl -X POST <https://api.riskified.com/api/decide> \ -H "Content-Type: application/json" \ -H "X-RISKIFIED-SHOP-DOMAIN: your-shop.myshopify.com" \ -d '{"order":{"id":"test-123"}}'

    ⚙️ Production Setup

    1. Use <https://api.riskified.com/api> (not staging)
    2. Implement proper HMAC signature generation
    3. Add retry logic for API errors
    4. Set up monitoring and health checks
    5. Configure load balancing for scale

    📚 Resources

    All 9 fraud detection tools follow consistent authentication and response patterns for seamless integration.

    Support

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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    Customer reviews

    Ratings and reviews

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    4.4
    232 ratings
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    4 star
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    1 star
    64%
    33%
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    0 AWS reviews
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    232 external reviews
    External reviews are from G2 .
    Airlines/Aviation

    Good solution for fraud management and prevention

    Reviewed on Sep 17, 2026
    Review provided by G2
    What do you like best about the product?
    What I like most about Riskified is the ability to automate risk assessment and make real-time decisions without adding too much friction to the purchasing process. I also value the visibility it offers to analyze transactions and behavior patterns, which facilitates fraud management and continuous optimization of risk strategies.
    What do you dislike about the product?
    What I like least about Riskified is that, in some cases, the visibility into the reasons behind a risk decision can be limited. For Risk & Fraud teams, having greater transparency and granularity on the signals, rules, and factors influencing a decision would help conduct deeper analyses, optimize strategies, and better understand specific cases.
    What problems is the product solving and how is that benefiting you?
    Riskified helps reduce the risk of fraud in transactions by automating risk assessment and enabling faster decisions on which operations to approve or reject. This benefits the business by reducing fraud losses, decreasing manual review, and potentially improving the approval rate of legitimate transactions without unnecessarily increasing user friction.
    Gambling & Casinos

    Fewer False Declines with Fast, Transparent Real-Time Fraud Decisions

    Reviewed on Sep 16, 2026
    Review provided by G2
    What do you like best about the product?
    Fewer false declines, meaning fewer legitimate customers wrongly blocked. Real-time decisioning doesn't slow down checkout/customer experience and automation frees up internal fraud/risk teams for edge cases. Visibility into decisions, trends, and false positive/negative rates. Ease of implementation, API quality, responsiveness of their account/support team
    What do you dislike about the product?
    Not the easiest to customize rules to the risk tolerance compared to running an in-house or more configurable fraud engine. When orders are routed to "review" status, turnaround time can sometimes be slower than desired, delaying order fulfillment and frustrating customers.
    What problems is the product solving and how is that benefiting you?
    Real-time risk scoring using device fingerprinting, behavioral signals, and network-wide fraud pattern data to catch fraudulent orders before they're fulfilled.
    Anonymous

    Effective Fraud Detection with UI Improvements Needed

    Reviewed on Sep 15, 2026
    Review provided by G2
    What do you like best about the product?
    I like that Riskified has precise email information collection, making it clear whether an account is cold or has a legit history. This feature is particularly helpful whenever carding or single fraud cases arise since fraudsters often create new emails for purchases, and Riskified helps me determine how cold the emails are or whether they have a legit history.
    What do you dislike about the product?
    I find the inter-customer connections in Riskified aren't flagged as obviously as they could be in the UI. This makes it less intuitive, and I think it could be improved with more visible flags on the transaction main page to show potential interconnections. Plus, the machine learning part could be enhanced to suggest more useful rules based on these interconnections. Another thing is the onboarding process, which wasn't as smooth as I'd hoped, though I understand it's done to maximize efficiency and prevent false flagging of transactions.
    What problems is the product solving and how is that benefiting you?
    Riskified helps me verify customers and solve issues like single fraud, fraud bands, carding, and smurfing. It precisely collects email information, helping determine whether an account is newly created by fraudsters or has a legitimate history.
    Banking

    End-to-End Fraud Prevention Peace of Mind, but Less Control for Internal Risk Teams

    Reviewed on Sep 15, 2026
    Review provided by G2
    What do you like best about the product?
    Organizations that do not consider fraud prevention a core competency, can outsource and have peace of mind. They take end to end ownership and free the client to focus on what matters
    What do you dislike about the product?
    Riskified is taking away risk management. That would take decisions away from internal experts who may have better context to make business optimal decisions
    What problems is the product solving and how is that benefiting you?
    They manage fraud for my company which frees resources to focus on building capabilities that my customers expect and add the most value to me and to them
    Airlines/Aviation

    Intuitive AI Fraud Detection with Strong Automation and Support

    Reviewed on Aug 26, 2026
    Review provided by G2
    What do you like best about the product?
    What I like most about Riskified is how effectively it combines AI-driven fraud detection with a simple, intuitive user experience. The platform provides actionable insights without adding unnecessary complexity to the workflow, while its integrations make it easy to fit into existing processes. Its strong performance and automation reduce manual effort and improve operational efficiency, and the AI-driven intelligence supports faster, more informed decisions. I also value the onboarding and support experience, which makes implementation smoother and provides useful guidance when questions or issues arise. Overall, the combination of usability, intelligence, support, and automation delivers clear operational value and ROI.
    What do you dislike about the product?
    The main area for improvement is the level of customization and flexibility available in some workflows. While the UI is generally intuitive, certain configurations and integrations can require additional effort, which may increase implementation time for more complex use cases. Pricing can also become a consideration as usage scales, so clearer visibility into ROI and pricing structure would be helpful. The AI-driven insights are valuable, but providing more transparency into how certain decisions or recommendations are generated could further improve user confidence. Onboarding and support are generally helpful, although more detailed documentation and self-service resources for advanced configurations would make troubleshooting and adoption even more efficient.
    What problems is the product solving and how is that benefiting you?
    Before using Riskified, we struggled with manual fraud review, inconsistent decision-making, and the operational effort required to manage transactions at scale. Riskified helps automate these decisions using AI-driven intelligence, allowing us to identify risky transactions faster while reducing unnecessary manual intervention. Its integrations fit well into existing workflows, and the intuitive interface makes monitoring performance and reviewing insights straightforward. This has improved operational efficiency, reduced review effort, and helped us make faster, more consistent decisions. The onboarding and support also made adoption easier, contributing to a stronger overall ROI from the platform.
    View all reviews