Topic starter
13/10/2026 1:21 pm
TL;DR: Identity analytics correlates human and non-human identities, entitlements and access activity to surface anomalies, entitlement creep and over-privileged access, while also supporting guided remediation, access reviews and SoD checks, according to Radiant Logic. The governance value is not visibility alone but making access decisions auditable when IAM data is fragmented and manual review cannot keep pace.
Editorial analysis by NHI Mgmt Group, based on content published by Radiant Logic: “What is Identity Analytics? Definition, Use Cases, and Benefits.”.
Key questions
Q: How should security teams handle fragmented identity data across multiple IAM tools?
A: Security teams should treat fragmentation as a governance problem, not a reporting inconvenience.
Q: Why does entitlement creep remain a problem in modern IAM programmes?
A: Entitlement creep persists because identities accumulate permissions faster than teams review and remove them.
Q: What are the warning signs that access reviews are not producing reliable governance outcomes?
A: Look for reviews that are completed but not actioned, inconsistent ownership data, repeated exceptions and poor traceability from entitlement to approver.
Practitioner guidance
- Unify identity sources before expanding analytics Correlate directories, cloud entitlements, application accounts and access activity into a single identity view before asking analytics to drive governance decisions.
- Use analytics to target privilege creep Compare current entitlements against historical patterns and role expectations, then flag accounts whose access has drifted beyond normal usage.
- Treat SoD evidence as a data-quality test Run Segregation of Duties checks only after identity attributes, account ownership and entitlement mappings are validated across source systems.
Bottom line: Identity analytics matters because fragmented identity data makes access governance slower, weaker and harder to audit.
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13/10/2026 1:22 pm
Identity analytics has become a governance control, not a reporting layer. When identity data is fragmented, the organisation cannot reliably answer who has access, why they have it, or whether it still makes sense. That shifts analytics from convenience to control dependency. The practical conclusion is that IGA quality now depends on the completeness and correlation of upstream identity data.
A few things that frame the scale:
- 7% of security leaders admit they do not know how often their AI systems are making autonomous changes to infrastructure, according to the 2026 Infrastructure Identity Survey.
- The average time to mitigate a leaked secret is 36 hours, highlighting the operational burden of manual remediation processes, according to the 2024 State of Secrets Management Survey.
A question worth separating out:
Q: How do identity analytics and Segregation of Duties checks work together?
A: Identity analytics supplies the validated identity and entitlement context that SoD analysis depends on. SoD rules can only identify toxic combinations when accounts, attributes and role mappings are accurate. In practice, analytics should improve the quality of the evidence before SoD decisions are used for certification or remediation.
👉 Read our full editorial: Identity analytics exposes access drift across human and NHI estates