Fast-moving business priorities, ever-changing distributed IT landscape (on-premises, cloud, mobile) and an increasingly dispersed workforce, have surfaced challenges with static rule-based IAM solutions. Gurucul Identity Analytics (IdA) provides a risk-based approach for driving IAM processes using dynamic risk profiles derived by advanced machine learning analytics on big data.
Why Choose Gurucul Identity Analytics?
Using big data, Gurucul provides a true 360-degree view of identity, access, privileged access, usage in the cloud, mobile and on-premises, breaking down traditional IAM silos
Reduces rubber-stamping by providing decision makers with risk, access usage and peer group analytics. This can be done seamlessly with your existing access attestation tool or using Gurucul Access Analytics’ mobile enabled certifications.
Provides a user-friendly interface to analyze outlier access with Gurucul’s award-winning machine learning algorithms. Gurucul STUDIO™ enables custom model development without coding and with minimal data science skills. Companies initially reduce access by over 40% and maintain these analytics as part of their on-going governance process.
Enables real-time risk-based access policy enforcement of multi-factor authentication for internal users and customers (CIAM) using risk scores backed by machine learning and behavior analytics on big data platform. Successfully deployed for 8 million customers at a Fortune 50 company.
Enables automated workflow approvals with dynamically generated risk scores by analyzing peer groups, entitlement combinations and application classification in real-time using Gurucul’s award winning machine learning algorithms. Customers reported a 65% reduction in on-boarding time using Gurucul’s risk-based dynamic provisioning.
Discover, risk rank and monitor accounts with privileged access. Identify outlier access and anomalous behavior with Gurucul machine learning. Backdoor access and its misuse will be a thing of the past.
Provides role mining, role consolidation, and role comparison using machine learning algorithms and usage data context. Avoid garbage-in-garbage-out of over-provisioned rubber-stamped access entitlements. Business user, application and attribute RBAC. 58% reduction in business time to review new roles and sign off.
Offers a contextual IAM search using big data to mine linked users, accounts, entitlements,
structured and unstructured data, along with risk score and peer group analytics, which include the capability of saving and exporting results for reporting.
Delivers 100+ Identity Analytics reports available out of the box, with the capability to customize, schedule and automate reports.