Riskified
E-commerce fraud protection software
Fraud detection software
Web security software
E-commerce software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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- Retail and wholesale
- Accommodation and food services
- Arts, entertainment, and recreation
What is Riskified
Riskified is an e-commerce fraud protection platform focused on assessing online order risk and helping merchants reduce fraud-related chargebacks. It is used by digital commerce teams, fraud/risk operations, and payments stakeholders to automate decisioning for card-not-present transactions and manage post-purchase disputes. The product combines machine-learning risk scoring with merchant workflows and integrations to e-commerce and payments ecosystems. It is commonly positioned around improving approval rates while controlling fraud exposure through policy controls and performance reporting.
Specialized for e-commerce orders
Riskified is designed around the online order lifecycle, including pre-authorization decisioning and post-purchase outcomes such as chargebacks. This focus aligns well with merchants that need order-level decisions rather than only account-level monitoring. It supports common e-commerce patterns such as guest checkout, promotions, and high-velocity order flows. The product’s feature set maps closely to operational needs of fraud analysts and e-commerce operations teams.
Workflow and dispute tooling
The platform includes tools to support fraud operations workflows, including review/decision processes and reporting tied to order outcomes. It also addresses dispute/chargeback management as part of the fraud program, which helps teams connect decisions to downstream financial results. This can reduce reliance on separate tooling for parts of the fraud lifecycle. Centralizing these functions can simplify day-to-day operations for lean fraud teams.
Integrations with commerce stack
Riskified provides integrations and APIs intended to connect with e-commerce platforms, payment service providers, and order management systems. This helps merchants operationalize fraud decisions in checkout and fulfillment flows. Integration options can reduce custom engineering compared with building a fully bespoke fraud decisioning layer. For organizations with multiple storefronts or regions, consistent integration patterns can support standardization.
Primarily e-commerce focused scope
Riskified is centered on e-commerce order fraud and chargebacks, so it may be less suitable for broader enterprise fraud programs spanning banking, P2P transfers, or non-commerce payment types. Organizations seeking a single platform for multiple fraud domains may need additional tools. This can increase vendor count and integration effort. Fit can be weaker where the primary need is account takeover monitoring across many digital channels rather than order risk.
Model transparency and control
As with many ML-driven fraud platforms, merchants may have limited visibility into model features and decision rationale beyond provided explanations and reporting. Teams with strict governance requirements may want more granular control over scoring logic and rule execution. Tuning decisions to niche business policies can require vendor involvement or careful configuration. This can slow iteration for highly customized risk strategies.
Implementation and data dependency
Decision quality depends on clean, consistent order, payment, device, and customer data being available at decision time. Merchants with fragmented commerce stacks or inconsistent identifiers may need additional data engineering to reach expected performance. Implementation typically requires coordination across fraud, payments, and engineering teams. Time-to-value can vary based on integration complexity and the maturity of existing fraud operations.
Seller details
Riskified Ltd.
New York, NY, USA
2013
Public
https://www.riskified.com/
https://x.com/Riskified
https://www.linkedin.com/company/riskified/
