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Machine Learning Device Model

Predict every transaction’s risk.

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Machine Learning Device Model features

Here’s what you can do with Machine Learning Device Model

Supervised machine learning algorithms predict outcomes and deliver risk scores in real time by pulling from billions of global transactions and over 80 million detailed fraud and abuse reports.

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Adapt to changing fraud patterns

As fraud risks evolve, our machine learning algorithm continually adjusts to new threats based on insights from confirmed fraud reports.

Simple integration

Our machine learning solution complements our Device Risk technology without the need for coding or special requirements, and easily integrates with third-party platforms.

Models to fit all business needs

Industry-agnostic algorithms adapt to global fraud trends, while specific models are refined to the fraud trends of your particular industry.

Reduce consumer friction

Confidently identify consumers, apply step-up authentication when needed, and continuously provide relevant, friction-right experiences with predictive risk scoring.

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