Identity intelligence one step ahead of emerging threats

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AU10TIX Serial Fraud Monitor is an advanced identity intelligence solution designed to detect and prevent sophisticated, coordinated fraud attacks that bypass traditional verification systems. Powered by neural networks and real-time traffic analysis, it identifies subtle fraud patterns, deepfakes, and synthetic identities. The platform offers 24/7 monitoring, predictive modeling, and consortium-based validation to protect businesses from evolving threats and reduce operational costs.

70% of serious fraud cases slip through regular identity verification checks Empty heading Powered by advanced neural networks, AU10TIX’s award-winning Serial Fraud Monitor has identity intelligence designed to combat coordinated traffic-level attacks, helping you to stay ahead of the game and ensure the safety of your business.

Saving organizations an average of $5 billion annually Empty heading Identity intelligent systems save money by automating verification, reducing fraud, and cutting operational costs. Faster, more accurate detection prevents costly breaches, ensures compliance, and streamlines onboarding for efficient scaling. 

• **Advanced Neural Network Technology: **Highly accurate fraud detection, leveraging machine learning and AI mechanisms to recognize even the most sophisticated synthetic fraud.
• **Deepfake Detection: **Detect deepfakes by analyzing behavioral patterns, anomalies, repetitions and conflicts.
• **Traffic-Level Fraud Analysis: **Real-time fast reaction and insights that detect fraudulent activity based on incoming and historical traffic patterns.
• **Consortium Validation: **Reputation scoring and data cross-checking in a consortium, utilizing millions of data points.
• **Comprehensive Data Tracking: **Tracks over 20 visual, data, and non-data vectors, such as background and geolocation, providing robust validation.
• **On-Demand Fraud Detection: **Check existing data blocks to identify fraudulent accounts and prevent existing threats.

Features

• Neural Network-Based Detection: Uses AI to identify synthetic and coordinated fraud attempts with high accuracy.
• Traffic-Level Fraud Analysis: Monitors real-time and historical traffic to detect anomalies and coordinated attacks.
• Deepfake & Synthetic Identity Detection: Analyzes behavioral patterns and inconsistencies to flag fake identities.
• Consortium Validation: Cross-checks data across a shared fraud intelligence network for enhanced accuracy.
• Comprehensive Data Tracking: Evaluates over 20 visual, data, and non-data vectors including geolocation and background.