One of these solutions is Advanced Authentication which uses a machine learning, biometric data, and non-personalised metadata to identify anomalies and fraudulent activity. This authentication doesn’t require input from the user and keeps tabs on potentially fraudulent activity.
Kaspersky Lab turned to machine learning again for the second solution – Automated Fraud Analytics. This software gathers and analyses depersonalised indicators such as device type and behavioural patterns of a user. This data is then compiled and compared with patterns associated with account takeover, new account fraud, and money laundering.
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