Transaction Fraud Detection & Prevention Solutions

Transaction fraud solution analyzes transaction data in real-time using machine learning models and rules to detect suspicious patterns. It evaluates factors like user behavior, transaction amount, and leverages inbound and outbound transfers. When high-risk activity is identified, the system triggers alerts or blocks the transaction to prevent fraud before transaction.

Feedzai’s solution is omnichannel, meaning that it detects transaction fraud in real-time across multiple payment channels by using machine learning models that analyze customer behavior, transaction history, and device data. It integrates data from all channels to create a unified risk profile.

Feedzai’s AI leverages transactional, biometric, and other data to build a 360-degree baseline of each customer’s banking behavior, enabling the most accurate identification of anomalies. Feedzai also offers Feedzai IQ TrustScore, an AI-powered risk score that leverages real-time, network-wide intelligence to assess fraud.

Feedzai seamlessly integrates with existing fraud infrastructure, ingesting data from various sources including databases, transaction systems and third-party tools. It enhances decision engines with custom rules or third-party scoring and supports importing/exporting machine learning models, offering flexible and powerful fraud prevention.

Feedzai stands out with real-time machine learning, “segment-of-one” and omnichannel risk profiling, and explainable AI. Its scalable, cloud-native platform offers low latency, high accuracy, and analyst-friendly tools. Integrated case management, regulatory compliance, and global fraud intelligence make it a top choice for transaction fraud detection.