The solution uses in-session behavioural data collected from digital channels in real time. As there is no historical information to accurately determine if an applicant is genuine or a criminal, digital customer onboarding presents a significant challenge for banks, insurers, and other financial institutions. In addition, these organisations are also bombarded with new threats to existing customers, including malware, account takeover, and man-in-the-middle and phishing attacks.
Adaptive Behavioral Biometrics models are available through the ARIC Fraud Hub, and track user-specific features collected ahead of a transaction. The models self-learn from each interaction, aiming to produce a unique session fingerprint that indicates an individual users usual or unusual behaviour. It also provides fraud analysts with an easy-to-understand visual profile, which detects phishing and malware activity generated by genuine customers.
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