Navigating the AI Frontier in CIAM and Fraud Prevention
This e-book provides a comprehensive roadmap for organizations facing a new generation of identity-based threats.
As artificial intelligence (AI) democratizes advanced cybercrime, traditional “assumed trust” models are failing against hyper-personalized phishing, deepfake deceptions, and synthetic identity fraud. This piece details how to pivot from a reactive security posture to a predictive, “Verified Trust” framework by leveraging the synergy of AI and cloud-scale defense.
You will learn how practical applications like behavioral biometrics and anomaly detection create “invisible security” that stops sophisticated attackers in real-time without frustrating your customers.
- The AI-Accelerated Threat Landscape: Understand how AI acts as a force multiplier for fraud, enabling even low-skilled criminals to launch high-velocity attacks that overwhelm human-led defenses.
- The Move to Verified Trust: Learn why digital identity is the new primary battleground and why trust must become an active, continuous, and contextually verified state.
- The Defender’s Edge: Discover how AI and cloud-native platforms provide the necessary data and compute power to move from reactive detection to proactive protection.
- Practical AI in Action: Explore tactical implementations such as keystroke dynamics, gait analysis, and risk-based authentication to distinguish legitimate users from bots and fraudsters.
- Unifying Siloed Defenses: Gain insights into the OpenID Shared Signals Framework (SSF), an essential standard for creating a collaborative security ecosystem that responds to threats in milliseconds.
- Balancing Security and Experience: Resolve the CIAM dilemma by replacing “bad friction” with intelligent, risk-based challenges that preserve a seamless customer journey.
- Strategic Future Vision: Prepare for the age of “Agentic Automation” and learn how your security team can transition from manual investigators to proactive AI trainers.
Nicolas Seigneur
Directeur technique
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