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23/06/2026 7:00 pm
TL;DR: Periodic audits create a false sense of control because data environments change faster than evidence can be gathered, according to Collibra. Continuous compliance monitoring replaces snapshots with persistent control signals, which changes how regulators, boards, and practitioners assess risk and remediation.
NHIMG editorial — based on content published by Collibra: Continuous compliance monitoring: Moving from reactive audits to proactive control
By the numbers:
- 72% of organisations have experienced or suspect they have experienced a breach of non-human identities, 46% confirmed and 26% suspected.
Questions worth separating out
Q: How should security teams replace periodic audits with continuous compliance monitoring?
A: Start by identifying the controls that change fastest and carry the highest regulatory or business impact.
Q: Why do periodic compliance audits fail in dynamic data environments?
A: Periodic audits fail because they describe a past state, while modern data estates keep changing through new pipelines, access drift, schema updates, and policy exceptions.
Q: How do teams know whether continuous compliance monitoring is actually working?
A: It is working when control failures are detected as they happen, not after the next scheduled review.
Practitioner guidance
- Replace quarterly proof collection with live control evidence Instrument your highest-risk data controls so evidence is generated continuously and retained automatically.
- Encode policies as computable controls Move critical data and access policies out of static documents and into machine-readable rules that monitoring tools can evaluate against datasets, fields, and pipelines.
- Tie lineage updates to pipeline change events Require lineage maps to update when pipelines change, not when someone manually refreshes documentation.
What's in the full article
Collibra's full blog post covers the operational detail this post intentionally leaves for the source:
- How Control Tower aggregates data quality, lineage, policy adherence, and access monitoring into a unified compliance view
- The mechanics of mapping BCBS 239, Solvency II, and EU AI Act expectations to persistent control oversight
- Operational detail on how data quality and observability signals feed the monitoring layer
- The article's internal ROI framing for audit preparation reduction and material weakness prevention
👉 Read Collibra's analysis of continuous compliance monitoring and proactive control →
Continuous compliance monitoring: is your audit model keeping up?
Explore further
25/06/2026 2:46 am
Continuous compliance monitoring exposes the audit cycle as a weak governance assumption, not a process gap. The old model assumes controls can be sampled, reported, and trusted in between reviews. That assumption fails in dynamic environments where access rights drift, lineage changes, and policy enforcement can break silently after the evidence pack is assembled. The implication is that compliance programmes must be designed around live control state, not periodic proof.
A few things that frame the scale:
- 72% of organisations have experienced or suspect they have experienced a breach of non-human identities, 46% confirmed and 26% suspected, according to The 2024 ESG Report: Managing Non-Human Identities.
- Enterprises that have experienced a compromised NHI averaged 2.7 separate incidents in the past 12 months, according to the same report.
A question worth separating out:
Q: Who is accountable when continuous compliance evidence is incomplete?
A: Accountability sits with the control owner, data owner, and governance function together. If evidence is incomplete, the issue is usually not a single tool failure but a design failure in ownership, signal quality, or escalation. Frameworks such as the NIST Cybersecurity Framework 2.0 expect clear governance around control monitoring and response.
👉 Read our full editorial: Continuous compliance monitoring shifts compliance from snapshots to signals
