When should organisations prioritise data risk assessments in an M&A programme?

Organisations should prioritise data risk assessments as early as possible, ideally during initial deal evaluation and before integration planning begins. Early assessment helps teams understand the scale of known and unknown data, estimate residual risk, and decide whether a transaction can proceed safely. It also supports divestiture planning by identifying what data must be removed or isolated.

Why This Matters for Security Teams

In an M&A programme, data risk cannot be treated as a downstream cleanup task. The earlier teams assess where data lives, who can reach it, and how it is protected, the sooner they can quantify exposure, identify regulatory friction, and decide whether integration, isolation, or remediation is required before close. That matters because deal momentum often outpaces security visibility.

NHIMG research shows why this is not a theoretical concern: in the Ultimate Guide to NHIs — Key Research and Survey Results, 79% of organisations reported secrets leaks and 77% of those incidents caused tangible damage. In transactions, those leaks are often embedded in source code, CI/CD systems, shared storage, and third-party connections that are easy to miss during a fast diligence cycle. Current guidance from the NIST Cybersecurity Framework 2.0 supports this kind of early risk discovery because governance, identification, and protection must be in place before assets are combined. In practice, many security teams encounter data exposure only after integration work has already widened the blast radius.

How It Works in Practice

Effective data risk assessment in M&A starts with scoping, not scanning. Teams should first map the target’s critical data categories, retention obligations, jurisdictions, and systems of record, then identify where sensitive data is replicated, exported, or exposed through integrations. That includes cloud storage, SaaS tenants, backup systems, analytics platforms, source repositories, and any non-human identities that can move or read data on behalf of applications or operators. The Top 10 NHI Issues is useful here because NHI sprawl and excessive privilege often determine how far data can travel inside the environment.

A practical assessment usually blends legal, privacy, and security workstreams:

• Classify data by sensitivity, residency, and deal impact.
• Identify privileged accounts, service accounts, API keys, and automation paths that can access high-value data.
• Test whether data can be segregated, revoked, or encrypted without breaking business operations.
• Confirm logging, retention, and deletion requirements before any system merger.
• Determine whether the deal needs a clean-room, phased integration, or delayed data migration.

For organisations dealing with complex identity and secrets exposure, the Ultimate Guide to NHIs highlights why this matters: many environments still lack full visibility into service accounts and many secrets remain valid long after notice of compromise. Those realities make early diligence essential, because post-close remediation is slower, more expensive, and more likely to disrupt operations. These controls tend to break down when the target has fragmented data ownership across multiple business units because no single team can confirm what data exists or where it is replicated.

Common Variations and Edge Cases

Tighter data review often increases transaction friction, requiring organisations to balance deal speed against compliance, integration cost, and confidentiality constraints. That tradeoff becomes sharper in carve-outs, cross-border deals, distressed acquisitions, and heavily regulated sectors where data can be the value driver and the liability at the same time.

Best practice is evolving, but current guidance suggests three common exceptions. First, in a carve-out, the priority is often not full enterprise mapping but identifying what must be removed, masked, or logically isolated so the divested business can operate independently. Second, in an acquisition with limited access during diligence, teams may need a staged assessment: high-level risk indicators before signing, followed by deeper validation in the confirmatory phase. Third, where the target relies heavily on automation, data risk assessment should include non-human identities because access may be enforced through workloads rather than people. That is where identity and data risk intersect most strongly.

Organisations should also be careful not to assume that a clean legal contract means a clean technical estate. Data may still be retained in backups, logs, and shadow IT systems even after formal deletion commitments. The The 2024 ESG Report: Managing Non-Human Identities shows that 72% of organisations have experienced or suspect an NHI breach, which reinforces why transaction teams should treat machine access as part of the data-risk surface, not an afterthought.

Related resources from NHI Mgmt Group

• When should organisations prioritise SCIM support in an access governance programme?
• When should organisations treat an NHI as a high-priority risk?
• Should organisations prioritise external exposure or internal credential governance first?
• Should organisations prioritise inline blocking or forensic visibility for AI data risk?