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Identify and Isolate
Synthetic Identity Risk

Sigma Synthetic Fraud is purpose-built and trained with consortium data from the industry’s largest financial institutions and enterprises to tackle targeted fake, randomized, and synthetic fraud patterns to produce highly accurate, real-time actionable risk scores and reason codes.

The Socure Difference

Utilizing sophisticated machine learning models and trained with consortium data from across the industry, Socure Synthetic Fraud pinpoints synthetic fraud patterns to accurately identify risk - within milliseconds.

Solution Highlights

Diverse Data Sources

Credit Header, Telco, Energy, and Public Records data power Socure’s real-time identity verification and risk detection.

Proprietary Machine Learning

Innovative unsupervised clustering techniques to determine well-labeled synthetics utilizing Socure’s proprietary network of performance data.

Consortium Feedback Data

Network consortium feedback constantly improves model training and management of emerging threats across various industries and channels.

Feature Engineering

Innovative graph-based techniques extracting topological, velocity, and PII interaction features.