Audit Evidence Quality Masterclass: Webinar Recording | GRSee
Webinar recording15 September 2026with Sprinto

Audit Evidence Quality Masterclass

What auditors actually need to see when they review evidence, why a working control can still lead to an audit finding, and how to build a more scalable evidence process. Designed for security, compliance and GRC teams.

  • Yoni BerenyiQSA and Lead Auditor, GRSee Consulting
  • Manas KasliwalLead Auditor, Sprinto
Recording

On 15 September 2026, GRSee and Sprinto hosted the Audit Evidence Quality Masterclass, focused on what auditors actually need to see when reviewing evidence and why a working control can still lead to an audit finding.

Led by Yoni Berenyi, QSA and Lead Auditor at GRSee Consulting, and Manas Kasliwal, Lead Auditor at Sprinto, the session covered credible evidence, common gaps, and how to build a more scalable evidence process.

What we covered

Designed for security, compliance and GRC teams, the webinar covered:

  • Why a working control can still result in a finding
  • The difference between control existence, design and operation
  • What makes evidence complete, accurate, timely and traceable
  • Common evidence gaps across SOC 2 and ISO 27001 audits
  • Why screenshots and other point-in-time evidence can fall short
  • How ownership, evidence reuse, automation and continuous collection can improve audit readiness

Why a working control can still generate an audit finding

Auditors may need evidence to demonstrate three things: that a control exists, that it was designed appropriately, and that it operated consistently during the audit period.

The last point is often where teams struggle.

A screenshot may prove a configuration exists today, but not that it remained in place throughout the period under review. A policy may describe how a process should work without proving that it was followed consistently.

Good evidence needs to prove the control being tested, not simply show that documentation exists.

The evidence gaps auditors see most often

Even when a control works, weak supporting evidence can make it hard to verify. Common gaps include:

Stale evidence
Records fall outside the relevant audit period.
Missing approvals
Required reviews or approvals happened but were not documented.
Incomplete audit trails
It is unclear who acted, when, or whether the process was completed.
Inconsistent sampling
Evidence is available for some items but missing for others.
Unverifiable screenshots
Images lack timestamps, system details, user information or context.

In each case, the issue is the same: the auditor lacks enough reliable information to validate the control.

What makes good audit evidence?

Credible evidence should be:

Complete
It covers the relevant period or population.
Accurate
It directly supports the control or claim being tested.
Timely
It was generated when the control operated.
Traceable
It shows who did what, when, and what happened next.

These qualities turn documentation into evidence an auditor can rely on.

How to make evidence collection more scalable

As organizations add systems, control owners and frameworks, manual evidence collection becomes harder to manage. A more scalable approach includes:

  • Assigning clear owners and evidence sources to controls
  • Collecting evidence closer to when the control operates
  • Using system-generated records where appropriate
  • Reusing evidence across overlapping requirements
  • Applying automation without sacrificing evidence quality
The goal is not to collect more evidence. It is to produce better evidence with less audit friction.

Better evidence, more predictable audits

Incomplete or difficult-to-verify evidence creates more follow-up questions, more manual reconstruction, and more time spent tracking down old records.

A clearer evidence process can reduce that effort and make future assessments easier to manage, especially as the organization adopts additional frameworks.

Questions from the session.

Can a control be working correctly and still result in an audit finding?

Yes. A control may exist and be appropriately designed, but the evidence may not show that it operated as expected during the audit period. That is why auditors look beyond whether a control exists.

What makes audit evidence credible?

Credible evidence is complete, accurate, timely and traceable: it covers the relevant period or population, directly supports the control being tested, reflects when the control operated, and shows who did what, when, and the outcome.

Are screenshots enough for audit evidence?

Sometimes. A screenshot helps when it clearly shows the system, configuration, date, user or activity. Without that context it may only show a point-in-time condition, not that a control operated throughout the audit period.

Why do policies alone not prove that a control is operating?

A policy describes how a process should work, not that it was followed. For ongoing controls, auditors may need approvals, system logs, review results, tickets or other records showing the process was carried out.

Can the same evidence be reused across multiple frameworks?

Yes, where the same underlying control supports requirements across frameworks, for example access control evidence for SOC 2, ISO 27001 or HIPAA. It still needs enough context to show how it supports each requirement.

How can organizations reduce manual evidence collection?

Assign clear evidence owners, identify reliable evidence sources, and use system-generated records where appropriate. Automation helps with recurring evidence, but automated evidence must still be complete, accurate, timely and traceable.

What should teams review before their next audit?

That controls have clear owners, evidence sources are known, records cover the audit period, approvals are documented, and audit trails give enough context to verify what happened. Also look for recurring evidence you can generate continuously.

Turn it into action

Make your next audit more predictable.

If that’s ISO certification, penetration tests or any other ongoing services, they are super professional and always helping with a smile. Ori Tzimber, VP R&D, Octopai
  • Wix
  • Cato Networks
  • Lemonade

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