As online transactions grow, so does the need for intelligent defense. Advanced threat protection acts as a 24/7 guardian, offering real-time protection against account takeover and fraudulent account creation.
Real-Time Behavior Analysis and Risk Scoring
Using a mix of AI, machine learning, and self-learning models, advanced threat protection evaluates user behavior from the very start of a session, not just at login. It generates a dynamic "risk score" for every interaction. High-risk users face additional verification challenges, while low-risk users enjoy a frictionless shopping experience.
Advanced Threat Protection Use Cases in Action
Here's how intelligent risk scoring works in practice across common fraud scenarios.
Unexpected Locations: When Sarah, a US-based shopper, suddenly logs in from Italy, the system triggers a high-risk alert and challenges the login with a push notification, stopping potential access until verified.
Suspicious IP Patterns: If a new user like John creates an account, and five minutes later multiple other accounts originate from the same IP, the system flags this as potential NAF and freezes the accounts for verification.
Abnormal Device Behavior: When Emily's account shows bot-like mobile behavior (unnatural swipes or typing speeds) and orders to multiple addresses, the system detects the anomaly and suspends the shipping process for review.
Device Fingerprint Mismatches: If Alex usually uses an iPhone but his account suddenly sees login attempts from Windows and Android devices in a short span, the system prompts him to confirm the activity, locking the account if he denies it.
Integrated Mitigation Across the Customer Journey
Detection is only half the battle. With no-code journey orchestration, you can coordinate the response based on risk levels. This allows you to apply dynamic friction (like adaptive MFA or identity verification) only when necessary, ensuring security never comes at the expense of customer experience.