Most organizations still run identity governance like it’s 2015: nightly feeds, periodic reconciliations, yearly access reviews, and manual exceptions piled on top of already-fragile processes.

That model breaks in modern environments because identity isn’t static anymore. People change roles faster. Affiliations overlap. Contractors come and go. Students become employees. Researchers become clinicians. Vendors get time-bound access. Cloud entitlements multiply quietly. And the risk isn’t theoretical: the gap between what’s true and what’s granted is where breaches and audit findings live.

That’s the core reason Continuous Identity has become the direction of travel for the IAM/IGA market.

And it’s also why we are comfortable saying this plainly:

Fischer Identity has been delivering Continuous Identity outcomes since 2005, long before the term was popular.

What Continuous Identity Actually Means

Continuous Identity is not “we ingest identity data frequently.”

That’s streaming.

Continuous Identity is a closed-loop control system for identity:

Signals change → identity state recalculates → policies re-evaluate → enforcement happens → evidence is recorded.

It’s identity as a continuously computed state, not a periodically refreshed snapshot.

If a platform can’t reliably enforce outcomes based on computed policy decisions—and prove it with audit-grade evidence—it’s not Continuous Identity. It’s data movement.

Why the Old Model Fails (Even When It Looks Fine on Paper)

Traditional IGA tends to be built around time-based governance:

• “We’ll catch it in the next reconciliation.”
• “The next access review will clean it up.”
• “The ticket will get approved and handled.”

But risk doesn’t wait for schedules.

When a termination happens, when an affiliation changes, when a privileged entitlement drifts, when a source record gets corrected, organizations need identity governance that responds as reality changes, not weeks later.

The Five Capabilities That Separate “Streaming” from “Continuous”

A practical way to draw the line:

1) Signal ingestion

• Authoritative sources (HR/SIS/ERP) plus operational sources (directories, apps, ITSM, etc.).

2) Identity resolution

• Matching, de-duplication, correlation, and precedence so the platform knows who is who, consistently.

3) Continuous computation

• Policies compute the effective identity posture: eligibility, roles, entitlements, exceptions, SoD posture.

4) Continuous enforcement

• Provisioning/deprovisioning, entitlement changes, access removal, license changes, workflow triggers are all based on computed outcomes.

5) Audit-grade evidence

• A clear trail of: what changed, when, why, and which policy drove the result.

If you only have one or two of these, you have streaming.
If you have all five, you have Continuous Identity.

Where Fischer Identity Fits (And Why “Since 2005” Matters)

Fischer Identity didn’t arrive at Continuous Identity as a rebrand. It’s been the operating philosophy since 2005:

Policy-driven identity lifecycle automation that continuously keeps access aligned to identity reality—at scale, and without customization-heavy fragility.

This matters because the hardest environments aren’t neat enterprise directories. The hardest environments are ecosystems with shifting populations, overlapping roles, and overlapping lifecycle states, exactly where Fischer has long been proven:

• Many identity types (employees, students, affiliates, researchers, contractors, vendors, etc.)
• Many lifecycle transitions (sometimes multiple in a year, overlapping, for the same person)
• Many downstream systems (cloud + on-prem + hybrid)
• Many exceptions (that still need to be governed, not ignored)

In other words: Continuous Identity isn’t a marketing claim when it’s the thing you’ve had to do to survive real production complexity.

What “Continuous” Looks Like in Real Life

Here are three scenarios that quickly expose whether a platform is truly continuous:

Scenario 1: The mover event

• A person changes department, job, affiliation, or eligibility.
• Continuous outcome: identity state recomputes, policies re-evaluate, entitlements adjust automatically, audit evidence is recorded.

Scenario 2: The leaver event

• A separation occurs—planned or immediate.
• Continuous outcome: deprovisioning is enforced quickly and consistently across targets, not “eventually,” with proof.

Scenario 3: The data correction

• A source system fixes a bad record (it happens constantly).
• Continuous outcome: identity resolution updates, policies recompute, downstream access remediates, and the chain of causality is visible.

If those outcomes depend on nightly jobs, manual clean-up, or “we’ll catch it in the review,” that’s not Continuous Identity.

The Underrated Differentiator: Sustainability

A hard truth: Continuous Identity collapses if it requires brittle customization.

When identity governance depends on heavy custom code, every source change, app change, or organizational shift becomes a mini-project. That’s how “continuous” slowly turns into “stagnant.”

Fischer’s edge has always been delivering these lifecycle outcomes code-free through configurable policy and workflow, so the system stays durable as organizations evolve.

That’s also why Fischer has remained a quiet leader: the investment has gone into product capability and customer outcomes, not marketing spectacle.

A Straightforward Definition You Can Hold Us To

If you want one sentence:

Continuous Identity is continuously computing identity state from signals and continuously enforcing governance outcomes with audit-grade evidence.

That’s the bar. And Fischer has been clearing it since 2005.

Identity governance is moving from periodic administration to continuous control. That shift is inevitable because organizations don’t run on schedules anymore.

If your IGA program still assumes that “later” is safe, you’re accumulating risk, quietly.

Continuous Identity is how you close the gap.