/"A stolen account access costs less than $25 on the Darknet, you can even have a package with the associated social security number for $35/" Source: Darknet

Guardian Analytics Fraud Intelligence research into our customers’ digital banking account activity shows:

• Over 20% of online and mobile events are related to IP geolocation changes
• Over 30% of online and mobile events involve money transfers via wire transfer or ACH.

Here are some of the key challenges:
• A user may have multiple IP addresses depending on the location of their home router, office proxy, travel hotspots, etc.
• Should you detect suspicious online and mobile events?
• Should you detect the following suspicious money transfer activities resulting from suspicious online and mobile events?
• Do both?
• Should you block an IP address that comes from an infected device?

Guardian Analytics' machine learning and fraud behavior analysis risk engine monitors hundreds of fraud risk indicators in digital banking in real time, from anomalous login behavior including time of day, day of week, speed of IP address change, to device fingerprinting and configuration changes, unusual changes in remittance recipient, unusual changes in ACH recipient, malware detected on devices…
and calculate a real-time risk score for each digital banking user, enabling financial institutions to detect suspicious digital banking activities.

Advantages:

• Detect suspicious digital banking activities in real time
• Detecting unusual ACH and electronic funds transfers related to digital banking
• Enables real-time intervention in payment channels to prevent illegal money transfers
• Increase operational efficiency by focusing on the highest risk transactions and reducing recalls
• Improve compliance by following FFIEC anomaly detection guidelines

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