As the antics of these clever tricksters become increasingly complex, the need for concrete clues - in the form of real-time identity and engagement data, grows. Advanced capabilities like comprehensive identity resolution, behavioral biometrics, and anomaly detection provide a more complete picture of the fraud - and the fraudster. And, when captured in true real-time, the comprehensive data story enables brands to catch the fraud before it happens rather than scrambling to manage it after the fact.
The data story begins with establishing a consistent picture of identity. Proper identity resolution builds a sophisticated map of someone’s online presence and activity – an identity graph. And that starts with personally identifiable information (PII) and interaction data. Simply capturing and ingesting this information is important; but persisting identity across device and session is vital. Identifiers such as relevant ID numbers (i.e., account numbers or driver registration identifiers), login information, location, and IP address create the foundation for accurate authentication.
Layering advanced behavioral biometrics data takes identity resolution a step further. Just like a fingerprint or tone of voice, everyone has a unique set of behavioral characteristics that define the way they engage and can be used to verify their identity. The pressure of a keystroke on a digital cellphone screen, the direction in which a device is typically held, and the way an individual swipes and scrolls - these behaviors can be analyzed and used to augment and complete digital user profiles. Enhancing identity with behavioral biometrics provides an extra layer of security that's nearly impossible to fake.
If you know how someone behaves - and more importantly how they don't - you'll have a much better idea of whether they're who they say they are.
But what happens when something doesn't look quite right? The simple answer: it probably isn't. Anomaly detection further enriches fraud detection by using machine learning to identify patterns in data that deviate from the norm. Multiple accounts that utilize the same fraudulent payer, a high incidence of insignificant transfers, or an inexplainable number of questionable purchases and returns, these suspicious events raise major red flags. Anomaly detection runs in the background, carefully assessing all transactions and data to spot potential fraud before it happens. When combined with other data points, these alerts can be used to lower false positives by confirming or denying suspicions.
Combining the clues in the data allows you to win the fraud game before it begins. By understanding the complete picture of someone's digital activity, you can catch fraudsters in the act and prevent them from causing any damage. Don't be fooled by their tricks - with access to the right data, you'll always be one step ahead.