Reducing fraud is an ongoing process, especially in today’s environment of online crime, and it can be difficult to keep up with the quick pace of fraud trends and criminal activity. This device reputation database has been enhanced with several new features to help enterprise security executives get ahead of fraud trends and reduce risk to the enterprise.

Through this system, you can add sophisticated rule combinations to leverage users’ current and past device behavior intelligence to stop fraud. For example, if a customer fails multiple log-ins on an unfamiliar device, that would send a red flag signal through the system that a fraudster could be attempting to break into that customer’s account from an unknown computer. But, as no two enterprises are completely alike, users have the ability to set their own red flags – checking for PCs masquerading as mobile devices, new device attempts to access an existing account, counting transactions that occur at specific customer touch points (login and account creation), or different considerations for IP addresses and associated geolocation information. Combined rules are also a possibility – such as more closely reviewing transactions that originate from outside the U.S. and are accessing an existing account from a new device – and they help to home in on specific threats.

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