Risk Based Authentication
Methodology that is designed to prevent enrollment of fraudsters, leverages risk analysis for authentication of genuine callers, meaning risky callers aren’t enrolled for authentication.
Call Risk Analysis
Machine learning derived risk intelligence for every call. Using the risk analysis to guide enrollment, fraud controls, and authentication protocols.
Personalization
The ability to recognize different speaker profiles allows for developers to build customization and personalization features into contact centers, devices, and applications.
Account Risk Analysis
Helping predict what accounts are being actively targeted by criminal rings as early as 60 days before an account takeover attempt.
Device Printing
Recognizing devices that have been encountered before, whether an enrolled user or a potential bad actor that can be quickly spotted.
Demographics Detection
Utilizes Deep Voice® Engine technology to estimate age range, biological gender, and language.
Advanced Model Compression
We take our advanced audio analysis engine and compress the model to fit on embedded chips without compromising accuracy.
Fraud Intelligence (PIN Score)
Measures risk using machine learning combined with insights from suspicious calling patterns and confirmed fraud calls.
Spoof Detection
Call metadata analysis with machine learning to help identify when a number is spoofed.