Intelligence Engine

We know that the Monday person is different to the Friday person. What makes Callsign technology so effective is that it’s intelligent enough to tell the two apart.

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Organizations are facing an identity paradox, balancing the need to keep data safe with meeting compliance standards and delivering frictionless user experiences. The need for an identity solution to help them achieve that is clear, but key to that solution is: intelligence.

What Intelligence means for Identification

The Callsign Intelligence Engine is what enables us to deliver a seamless, secure identity solution for customers or employees. By working out how likely it is that someone is who they say they are, based on behavioral, device, location and telecoms data, the engine means we can remove friction and rely on thousands of data points to confirm identity.

Our Intelligence Engine is API-driven and cloud-hosted, so implementation is quick, easy and hassle-free. It can integrate with multiple data sources and it’s designed to learn over time as more information becomes available. Helping Callsign users stay ahead of the identification curve.

How the Intelligence Engine works

At the core of Callsign’s intelligence-driven identity technology is, of course, our Intelligence Engine. Its job is to create a confidence score, which feeds into the policy engine to determine an appropriate level of authentication based on real-time factors.

Intelligence puts an end to unneeded identification friction, informing a solution that works for everyone. All while increasing security, whether for an organization’s customers or employees. It means being able to contextually validate that someone is who they say they are, removing the need for blanket authentication, so a user doesn’t have to go through clunky authentication steps when they’re behaving as they normally would. This is because authentication is only stepped up if a low confidence score is generated.

The confidence score is determined in two phases:

Recognition

First up, the Intelligence Engine is looking for recognized characteristics across device, location and behavior. The idea being that these characteristics should be consistent with the known user identity profile. The engine is asking questions like: Is this the device the user normally uses? Is the transaction being attempted within a regular vicinity? Do the keystrokes fit within the user’s normal pattern? And so on.

Trust

The Intelligence Engine then looks at how trustworthy this information is, conducting ongoing passive analysis across various data points, learning the detailed nuances of each user profile. Meaning our technology can account for typical differences at certain times of the day or days of the week. To do this, it looks for threats like malware, as well as location or device inconsistencies (or anomalies). It considers how many characteristics across device, location and behavior are recognizable – and to what to degree?

Taking all of this information, the Intelligence Engine determines – using statistical modeling, advanced machine learning and deep learning techniques – how likely it is that someone is who they say they are, and creates a confidence score. This level of intelligence is all about enabling passive authentication as safely as possible – and only calling for active authentication when appropriate or required.