AI / ML Behavioral Risk Modeling

Most authentication solutions rely on outdated, rule-based risk engines that can’t keep up with evolving threats. Static models miss sophisticated fraud patterns, leaving gaps that attackers exploit. Worse, they create unnecessary friction for legitimate users, leading to churn and frustration.

SecureAuth’s AI-driven risk engine goes beyond static rules. It continuously learns, adapts, and refines risk assessment in real time—analyzing hundreds of behavioral and contextual factors before, during, and after authentication. Unlike rigid, legacy solutions, it dynamically blends machine learning with rule-based controls, giving you precision without sacrificing control.

If your CIAM can’t evolve, it’s holding you back. Upgrade to SecureAuth and get risk-based authentication that’s actually built for today’s threats.

Traditional authentication forces users through unnecessary steps, creating friction that kills conversions and frustrates customers. But skipping security checks blindly leaves your business exposed.

SecureAuth’s AI-driven Dynamic Level of Assurance (DLOA) gets it right—every time. By analyzing real-time risk signals, our risk engine intelligently adapts authentication requirements based on behavior, access level, and potential threats. This means seamless logins for trusted users and step-up authentication only when truly needed.

Built on NIST standards, DLOA ensures that security isn’t just strong—it’s smart, dynamic, and invisible until necessary.
Because security should protect, not frustrate.

Risk doesn’t exist in a vacuum—and neither should your risk analysis. SecureAuth delivers industry-leading threat detection, with the option to integrate third-party intelligence solutions like PAM, SIEM, IGA, and UEBA for even deeper risk insights.

By incorporating external risk signals, our risk engine enhances adaptive authentication in real time, strengthening security without unnecessary friction.

Because better data means better protection.

• Advanced Threat Detection: AI / ML algorithms analyze vast amounts of data to detect and predict unusual patterns or behaviors that may indicate security threats. This approach helps identify threats early, reducing the likelihood of security breaches.
• Dynamic Security & Superior Experiences: AI / ML dynamically adjusts authentication requirements based on real-time risk assessments. Customers only face additional security measures only when their behavior or context raises suspicion, improving security without compromising user experience.