First Technology Federal Credit Union

First Tech's existing fraud monitoring system was creating operational inefficiencies and leaving the credit union vulnerable to new, sophisticated fraud threats. As the 12th largest credit union in the US serving over 700,000 members from major tech companies, the institution needed to meet high member expectations for security while managing complex fraud across all payment channels.

First Tech implemented Featurespace's ARIC Risk Hub as an enterprise-wide fraud prevention solution using a phased approach. The initiative began with adaptive rules and transitioned into advanced machine learning models using Adaptive Behavioral Analytics (ABA) to build unique behavioral profiles for each of its 700,000+ members across all payment channels.

The transformation yielded substantial financial savings and enhanced member protection while optimizing fraud management operations. A notable win included catching a major ATM fraud ring, resulting in 32 identified suspects and 7 arrests — protecting First Tech members and other financial institutions from an emerging threat.

• Phased AI adoption (rules → ML models) allows institutions to build internal expertise while progressively improving detection accuracy.
• Behavioral analytics at the individual member level significantly improves signal-to-noise ratio in fraud detection.
• AI-driven fraud prevention can generate law enforcement-quality evidence, enabling real criminal prosecutions beyond just blocking transactions.