Adaptive Behavorial Risk Models Automatically Protect Consumers

Fraud and financial crime continue to increase during societal changes. Data has altered due to a dramatic shift in consumer spending patterns. Machine learning models traditionally created on historic data need re-training to learn new consumer behaviors and be effective at identifying fraud and financial crime and optimizing payment flow.

Featurespace’s customers are protected during these changes by our invention – Adaptive Behavioral Analytics – using self-learning risk models that automatically respond in real-time to changing consumer and criminal behavior to optimize acceptance rates on behalf of customers.

Dave Excell, Featurespace Founder, comments:  “During the shift in fraud and financial crime rates during these challenging times, Featurespace’s self-learning risk models have responded autonomously and continue to deliver optimal, market-leading acceptance rates.

“Listening to our global customers, we know they value risk models which update automatically, so they can focus on the important task of prioritizing financial crime investigations and protecting their own customers.”

Featurespace’s market-leading models for the detection and prevention of fraud and money laundering are delivered via the ARIC™ Risk Hub, which uses real-time machine learning and unique Adaptive Behavioral Analytics to spot individual anomalies in behavior.

By focusing on understanding ‘good’ customer behavior, Featurespace’s ARIC Risk Hub dramatically reduces the volume of ‘good’ transactions that are blocked to stop fraud and suspicious activity (known as ‘false positives’) – typically by over 70%, improving customer experience.

To discover the full features and functionality of the ARIC Risk Hub, visit the Featurespace website and request your exclusive access.

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Author: Laimis Bilys

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