GRC trends show why fragmented controls are raising audit risk

At a glance

What this is: OneTrust’s article says GRC is being reshaped by third-party exposure, data fragmentation, automation demand, and tighter alignment between compliance and enterprise risk.

Why it matters: For IAM, PAM, NHI, and broader governance teams, the message is that control ownership and evidence collection now have to work across identities, systems, and vendors rather than inside isolated programmes.

By the numbers:

• The total software market for governance, risk, and compliance is projected to reach $134.86 billion by 2030.
• OneTrust says its Compliance Automation can reduce the cost of compliance up to 60%.
• OneTrust says organisations can obtain certifications 50% faster through Compliance Automation.

👉 Read OneTrust's blog on 10 GRC trends shaping governance, risk, and compliance

Context

Governance, risk, and compliance fails when controls, evidence, and accountability are spread across disconnected systems. In this article, OneTrust argues that the real pressure on GRC programmes comes from third-party dependence, fragmented internal data, and the need to automate compliance work at enterprise scale.

The identity connection is indirect but real. Vendor access, shared evidence, and cross-system policy mapping all depend on knowing which human and non-human identities can reach which systems, when access changes, and who owns the control. That makes GRC a governance layer that increasingly overlaps with IAM, PAM, and NHI lifecycle management.

Key questions

Q: How should organisations reduce audit fatigue in fragmented GRC programmes?

A: Start by consolidating control ownership, evidence sources, and exception tracking into a single operating model. Audit fatigue usually comes from repeated manual collection across teams and frameworks. A better approach is to standardise the evidence pipeline, reuse controls where possible, and reserve human review for exceptions and material changes.

Q: Why does third-party risk matter so much in GRC programmes?

A: Third-party risk matters because external services expand the organisation’s control boundary without fully handing over accountability. Vendors, integrators, and managed services can introduce access, data, and compliance exposure that is easy to approve and hard to continuously govern. Strong GRC programmes therefore treat supplier oversight as an ongoing control process, not a one-time questionnaire.

Q: What do security teams get wrong about automated compliance workflows?

A: They often assume the workflow itself is the control. In practice, the control is the combination of entitlement data, review logic, exception handling, and documented follow-through. If any of those pieces are weak, automation only accelerates the production of incomplete evidence.

Q: Why do code injection flaws matter to IAM and NHI governance?

A: They matter because injected code often runs under a trusted application or pipeline identity. That can expose API keys, tokens, certificates, and deployment privileges even when user authentication is strong. IAM and NHI teams should therefore govern the identities behind applications, not only the people who use them.

Technical breakdown

Interconnected GRC architecture and evidence mapping

GRC platforms no longer function as static repositories for policies and assessments. Interconnected architecture means risk, control, asset, and evidence data must move across cloud, application, vendor, and internal systems so that compliance is not rebuilt manually for every framework. The operational shift is from periodic point-in-time collection to continuous mapping between obligations and controls. That matters because fragmented data creates duplicate controls, inconsistent attestation, and audit drag that masks real risk.

Practical implication: consolidate evidence sources and map controls once across frameworks, rather than rebuilding each compliance exercise from scratch.

Third-party risk as a governance and access problem

The article treats third-party risk as a GRC trend, but the security reality is that third parties often expand the identity surface. Vendor services, hosted tools, and outsourced functions bring their own access paths, credentials, and responsibility gaps. When organisations lack visibility into those relationships, they cannot reliably answer who can access what, under which contract, and with which review cadence. That makes third-party risk management inseparable from identity governance, especially where service accounts, integrations, and delegated access exist.

Practical implication: inventory third-party access paths alongside contractual risk reviews so governance includes credentials, privileges, and offboarding.

Automation changes the economics of compliance operations

Manual compliance work scales poorly because every framework change, control request, and audit cycle pulls people back into ad hoc evidence gathering. Automation changes the economics by standardising scoping, linking controls to evidence, and reducing duplicate collection across audit, privacy, security, and risk teams. The important technical point is not that automation removes judgement. It is that it removes repetitive control assembly so practitioners can focus on exceptions, control design, and actual remediation.

Practical implication: automate repetitive evidence and control mapping tasks first, then reserve human review for exceptions, gaps, and control ownership.

NHI Mgmt Group analysis

Fragmented control evidence is now a governance risk, not just an audit inconvenience. When controls live in separate systems, organisations overcompensate with duplicate processes and inconsistent reporting. That weakens the reliability of assurance across IAM, cloud, and third-party programmes, especially when evidence must be reused across multiple frameworks. The practical conclusion is that governance teams should treat evidence fragmentation as a control failure mode, not a back-office nuisance.

Third-party risk increasingly behaves like identity sprawl at the enterprise boundary. Outsourced services, managed platforms, and partner integrations create access relationships that are easy to approve and hard to retire. That makes the governance question less about whether a supplier is trusted in principle and more about whether its access, credentials, and evidence trail are actually lifecycle-managed. Practitioners should align vendor oversight with identity lifecycle controls, not just procurement checkpoints.

Compliance automation is becoming a prerequisite for framework convergence. As regulatory and internal obligations expand, manual assembly of evidence cannot keep pace with the number of systems and stakeholders involved. The article points toward a future where GRC programmes must connect policies, controls, and reporting across domains instead of maintaining separate compliance islands. Practitioners should expect the strongest programmes to centralise control mapping and exception handling.

GRC is shifting from after-the-fact reporting to continuous operating discipline. The article’s emphasis on interconnected architecture and business engagement reflects a broader change in how security accountability is expected to work. Compliance teams are being asked to show live control health, not retrospective snapshots. For practitioners, that means risk ownership, evidence pipelines, and escalation paths need to be designed into operations from the start.

What this signals

Fragmented GRC programmes tend to hide identity risk inside process language. When access review, supplier oversight, and evidence collection are managed separately, the programme may look mature while still missing who can actually act. Teams should expect GRC maturity to be judged less by the number of frameworks covered and more by whether those controls can be tied back to identities, privileges, and ownership.

Control convergence will matter more than tool count. As enterprises add more systems, the winning governance model is likely to be the one that reduces duplicated evidence, aligns control mapping, and makes exceptions visible early. For identity leaders, that means linking GRC workflows to IAM, PAM, and NHI lifecycle checkpoints rather than treating them as downstream reporting tasks.

For practitioners

• Map control ownership across domains Create a single view of which teams own policy, evidence, exceptions, and remediation for cloud, third-party, privacy, and identity controls. This avoids duplicate attestations and makes audit requests easier to satisfy.
• Inventory third-party access paths Track vendor and partner access separately from procurement records, including shared credentials, service accounts, and offboarding steps. That gives governance teams visibility into access that often disappears after approval.
• Automate evidence collection before the next audit cycle Prioritise integrations that pull control evidence from existing systems of record, then define which items still require human validation. The goal is to reduce duplicate collection and shorten audit preparation.
• Align compliance workflows with identity lifecycle reviews Add access review, credential expiry, and offboarding checkpoints to vendor and internal control testing so governance captures who can still act, not just who was approved.

Key takeaways

• Fragmented GRC control and evidence models create audit drag, inconsistent assurance, and avoidable operational risk.
• Third-party exposure is also an identity governance issue because external services often expand access boundaries without clear lifecycle control.
• The practical response is to centralise evidence, automate repeatable compliance work, and connect GRC workflows to access and ownership data.

Key terms

• Governance, Risk, and Compliance: Governance, risk, and compliance is the discipline that connects decision rights, threat management, and regulatory obligations into one operating model. In identity programmes, it determines who owns access, how exposure is prioritised, and what evidence proves controls are working across human and non-human identities.
• Third-party risk management: Third-party risk management is the process of identifying, assessing, monitoring, and reducing risk introduced by external vendors and service providers. In identity terms, it governs who outside the organisation can reach systems or data, how that access is approved, and when it must be removed.
• Compliance Automation: Compliance automation is the use of software to collect evidence, track controls, and keep audit workflows moving with less manual effort. It helps organisations document compliance more efficiently, but it does not automatically prove that access decisions are correct or that identities have been governed properly.
• Control Mapping: Control mapping is the process of linking internal policies and technical controls to external requirements such as NIST or ISO 27001. For identity programmes, it turns access reviews, rotation, and offboarding into evidence that can be tested, reported, and audited.

What's in the full article

OneTrust's full blog covers the operational detail this post intentionally leaves for the source:

• The 10-driver and 10-trend framework used to organise GRC programme change
• The compliance automation capabilities OneTrust describes for evidence reuse and scoping
• The infographic content that maps future GRC priorities into a visual reference
• The examples of how third-party risk and mobile GRC engagement are positioned in the source

👉 The full OneTrust article expands the trend list, automation angle, and third-party risk context.

Deepen your knowledge

NHI Foundation Level course, the industry's only accredited NHI security programme, covers NHI governance, machine identity security, and secrets management. It helps security and identity practitioners connect lifecycle controls to broader governance programmes.