Governance
Cross-app
GRC LEAD

Run access reviews on usage, peer, and HR evidence instead of gut feel on every review line

Summary: 73% of organizations still rely primarily on manual access review processes — resulting in rubber-stamped approvals and recurring audit findings. Oleria Trustfusion, an AI-native identity security platform, replaces gut-feel certification with AI-powered access certification that surfaces three evidence signals — dormancy, peer-group analysis, and HR changes — on every review line, so reviewers make decisions on context, not memory.

Why this is hard without Oleria

73% of organizations rely primarily on manual processes for user access reviews (2025 State of IGA Report, Zilla Security). The result is well-documented: reviewers don't know what their reports actually use, so they approve everything to avoid disrupting work. Reviews complete on time but produce no real narrowing of access. Audit increasingly treats this as a finding because the review isn't doing the control's job.

This isn't a process problem. It's an evidence problem. Most IGA tools surface entitlements but not usage; they ask reviewers to certify access without the data to certify it on. As Mark Carter, CIO & CISO at Vimeo, puts it — "the traditional compliance process might make you compliant, but it doesn't make you secure."

AT A GLANCE

Cycle time
Weeks → days
Per-reviewer effort
30–60 min
Reviewer skill
No IAM training

Oleria AI

Oleria's AI evaluates three signals — Dormant Days, Peer Group Analysis, HR Changes — and proposes Approve, Needs review, or Reject for every line. Reviewers spend their attention on the outliers, not the bulk. Continuous least privilege, powered by deep access intelligence.

How it works

  1. Define scope and reviewers — Quarterly review of standing access for a team, a sensitive app, an admin group, or an entire IdP. Reviewer is the manager, application owner, or governance lead. Configurable per app, per data sensitivity, per identity type, and per employee-attribute slice (department, manager, start date).
  2. Generate review with intelligence — Each line populated with dormant days, peer-group match, HR change flag, and a recommended decision.
  3. Reviewers act — Bulk-accept high-confidence recommendations, examine outliers, override per line. 30–60 minutes per reviewer.
  4. Closeout and audit — Decisions logged, revocations executed, evidence pack assembles continuously for the next audit cycle.

What good looks like

Cycle time Weeks → days

Per-reviewer effort Hours → 30–60 minutes

Access actually narrowed by review From near zero to materially significant

Audit findings on review quality Eliminated

Find out where your access review maturity stands today.

If 73% of organizations run reviews on manual processes, the question isn't whether your program could be better — it's how much risk that gap is creating now. Oleria's Identity Security Maturity Assessment benchmarks your access governance program and shows where evidence-driven reviews can close the gap.

Frequently Asked Questions

What's the realistic adoption pattern?

Start with privileged or regulated-data scope; expand from there. By the fourth cycle, the review just runs.

What frameworks does this support?

SOX, HIPAA, ISO 27001, PCI DSS 4.0, GDPR, FedRAMP, NIST — evidence becomes the audit pack directly.

What about access that's needed but rarely used?

Threshold periods are customizable per organization, feature, and application.

Can I scope a review to a specific employee population?

Yes — by department, manager, or start date for risk-tiered cadences.

How does Oleria's intelligence change the review?

Three signals per line: Dormant Days, Peer Group match, HR Changes — with Approve, Needs review, or Reject recommended.

What's broken about traditional access reviews?

73% run on manual processes. Reviewers certify without evidence and rubber-stamp to avoid disruption.