Overview

Socure’s Sigma Identity Fraud is an advanced, cloud‑based identity fraud detection and prevention solution. It combines machine learning with a comprehensive identity graph spanning personal data, digital signals, and behavioral patterns to deliver highly accurate risk decisions across the customer lifecycle. The platform empowers organizations to approve more legitimate users while significantly reducing manual reviews and false positives, minimizing overall fraud risk in real time. Sigma leverages consortium data from thousands of clients and hundreds of data sources, providing industry‑leading precision and actionable insights for digital identity verification and fraud prevention. The solution is designed to support onboarding, authentication, and transaction monitoring at scale, helping businesses optimize approval rates, improve operational efficiency, and stay ahead of evolving fraud tactics.

Features and Capabilities

• **Core Identity Risk Scoring: **Provides a unified fraud risk score by analyzing personal, digital, and behavioral identity signals using machine learning models.
• **360‑Degree Identity View: **Combines PII (name, address, SSN, email, phone) with device, velocity, network signals, and behavioral insights to make accurate, real-time identity decisions.
• **High Auto‑Approval Rates: **Increases acceptance of legitimate users with minimal friction while detecting and preventing fraudulent activity early in the onboarding process.
• **Low False Positives & Manual Reviews: **Reduces the number of manual reviews and false positives, improving operational efficiency and customer experience.
• **Advanced Machine Learning Models: **Employs predictive models trained on consortium data from thousands of organizations to continuously improve fraud detection accuracy.
• **Real‑Time Decisions: **Delivers instant fraud classification across onboarding, authentication, and transaction workflows, enabling immediate response to potential threats.
• **Consortium Data Intelligence: **Aggregates feedback and behavioral data across a wide network to enhance predictive accuracy and adapt to emerging fraud patterns.
• **Dynamic Behavioral Signals: **Monitors long-term and evolving behavioral patterns rather than relying solely on static data, improving fraud detection resilience.
• **Comprehensive Coverage: **Protects against identity fraud across digital onboarding, high-risk authentication scenarios, and throughout the entire customer lifecycle.
• **Scalable Integration: **Designed for seamless integration with enterprise systems, supporting large-scale operations and high-volume transaction environments.