"A stolen account credential cost less than $25 on the darknet, you can even have a bundle for $35 with the associated social security number" Source: Darknet
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Guardian Analytics Fraud Intelligence research on our customer’s Digital Banking accounts activities shows:
• Over 20% of Online & Mobile events are IP geolocation changes related
• Over 30% of Online & Mobile events are associated with money transfers via Wire or ACH
Here are some key challenges:
• A user can have multiple IP address depending on their home router, office proxy, traveling hotspot location…
• Should you detect suspicious Online and Mobile events?
• Should you detect the subsequent suspicious money transfer activities resulting from suspicious Online and Mobile events?
• Do both?
• Should you block an IP address coming from an infected device?
Guardian Analytics machine learning and fraud behavioral analytics risk engine monitors in real-time hundreds of digital banking fraud risk indicators from anomalous login behavior including time of day, day of week, IP address change velocity, to device fingerprinting and configuration changes, wire recipient unusual changes, ACH recipient unusual changes, malware detected on devices…
and calculate a real time risk score for every digital banking user enabling Financial Institutions to detect digital banking suspicious activities.
• Detect suspicious digital banking activities in real-time
• Detection unusual digital banking related ACH and Wire money transfers
• Enables real-time intervention on payment channel to avoid illicit funds transfers
• Increase operational efficiency by focusing on the highest risk transactions and reducing callbacks
• Enhance compliance by meeting FFIEC guidelines for anomaly detection