Riskified

Analyzes thousands of data points from incoming transactions in real-time to determine fraud probability and risk score. Uses machine learning models trained on historical transaction patterns to identify suspicious activity while distinguishing legitimate high-risk transactions.

Identifies and approves legitimate transactions that traditional rule-based fraud systems would incorrectly reject. Recovers lost revenue by distinguishing between genuine fraud and legitimate high-risk behavior patterns.

Provides a centralized dashboard for merchants to monitor fraud metrics, transaction decisions, and system performance. Enables real-time visibility into fraud prevention activities and key performance indicators.

Provides financial protection by guaranteeing chargeback liability for approved transactions. Shifts the financial risk of fraudulent chargebacks from the merchant to Riskified, covering losses when approved transactions result in chargebacks.

Automatically approves, declines, or flags transactions for manual review based on learned risk patterns. Reduces manual review workload by handling routine decisions while escalating edge cases for human review.

Provides pre-built connectors and seamless integration with major e-commerce platforms including Shopify, WooCommerce, and Magento. Enables quick deployment with minimal technical setup required.

Augments incoming transaction data with additional context and behavioral signals to improve fraud detection accuracy. Combines merchant data with external data sources to create comprehensive transaction profiles.

Develops machine learning models customized to each merchant's specific transaction patterns, customer base, and fraud characteristics. Learns from historical data to optimize decision-making for individual business verticals.

Provides detailed analytics and reporting on chargeback patterns, trends, and root causes. Helps merchants understand chargeback drivers and identify opportunities to reduce future chargebacks.

Monitors transactions across multiple geographies and currencies to detect fraud patterns and manage risk at a global scale. Handles region-specific fraud characteristics and compliance requirements.

Analyzes transaction velocity, frequency patterns, and behavioral anomalies to detect fraud rings and organized fraud attempts. Identifies unusual patterns that deviate from normal customer behavior.