SailPoint Technologies Holdings, Inc., a leader in enterprise identity governance, today announced that the company has received initial approval for a new U.S. patent, covering SailPoint's application of Artificial Intelligence (AI) and Machine Learning (ML) to peer group analysis. The pending patent is titled "System and Method for Peer Group Detection, Visualization and Analysis in Identity Management Artificial Intelligence Systems Using Cluster-Based Analysis of Network Identity Graphs."

AI and ML, when applied to identity data, speeds the discovery, visualization and analysis of peer groups, delivering highly-accurate, relevant and scalable results. The patent-pending technology is a key component of SailPoint Predictive Identity, the intelligent cloud identity platform of the future.

"Peer groups enable enterprises to leverage the notion that identities with strongly similar attributes should be assigned similar, if not identical, access," said Paul Trulove, Chief Product Officer for SailPoint. "By leveraging AI and ML, we can greatly speed up the time it typically takes to discover peer groups among a set of hundreds, if not thousands, of peers, and identify outlier identities that do not adhere to the intended access profile of their job function."

Trulove continued, "Further, the ability to assign a similarity to a group of peers informs important governance recommendations. For example, should a certain user within a peer group retain access to a sensitive application or set of data that the rest of his or her peers does not have access to? With AI and ML, identity teams can quickly sift through these users whose access may be out of the norm or pose more risk. As a result, identity teams can drive more efficient and effective identity governance decisions."