Kount Ecommerce Fraud Prevention Logo

Kount Ecommerce Fraud Prevention

Real-time ecommerce fraud detection and prevention using ML-based risk scoring.

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Kount Ecommerce Fraud Prevention Description

Kount Ecommerce Fraud Prevention is a fraud detection and prevention platform designed for online merchants. It analyzes transactions in real time by collecting data points such as email address, billing/shipping address, IP address, and device ID, then applies machine learning to assess risk and make automated decisions on whether to approve, decline, or flag transactions for manual review. The platform uses two forms of machine learning — supervised and unsupervised — to detect patterns and anomalies across transactions. Merchants can configure custom policies to control how transactions are handled based on risk scores. Key fraud types addressed include: - Promo and loyalty abuse (new account fraud, affiliate abuse) - Account takeover and phishing attacks - Unauthorized transactions (card testing, triangulation fraud, e-gift card fraud) - Friendly fraud and invalid chargebacks - Emerging threats such as refund fraud and elder financial exploitation The product also includes chargeback management capabilities, allowing merchants to dispute false fraud claims and recover lost revenue. Kount maintains direct partnerships with Visa and Mastercard and leverages consumer data through its parent company Equifax. Expert consultation and managed services are available for fraud strategy, policy configuration, and operational outsourcing. The platform offers pre-built integrations with major ecommerce platforms, enabling quick deployment without custom development work.

Kount Ecommerce Fraud Prevention FAQ

Common questions about Kount Ecommerce Fraud Prevention including features, pricing, alternatives, and user reviews.

Kount Ecommerce Fraud Prevention is Real-time ecommerce fraud detection and prevention using ML-based risk scoring. developed by Kount. It is a GRC solution designed to help security teams with Fraud Detection, Anti Fraud, Machine Learning.

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