This white paper explains how behavioral data enhances fraud detection by identifying user intent through natural interactions like typing, swiping, and device movement. It highlights the shortcomings of traditional fraud detection tools and shows how behavioral biometrics use machine learning to distinguish between humans, bots, and emulators in real time. By analyzing gestures, navigation speed, and session patterns, it detects account takeovers, new account fraud, and synthetic identities early. Behavioral data operates invisibly across the user journey, reducing false positives, friction, and costs while strengthening security and improving customer experience.

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