The partnership focuses on monitoring behavioral signals—such as navigation patterns and device interaction—to distinguish between legitimate account holders and bad actors. Each session receives a risk score, allowing institutions to intervene automatically if activity deviates from established baselines. This approach aims to secure accounts without adding friction for the user.

Individual success stories highlight the scale of these protections. Gate City Bank reported a 97% capture rate for account takeover attempts, preventing $650,000 in losses over a six-month period. Similarly, Raiz Federal Credit Union utilized the layered security integration to stop $286,000 in fraudulent activity within its first year of deployment. According to Brad Cranford, director of product management at Alkami, these results demonstrate how session-level signals allow institutions to act before a threat escalates into a completed theft.