PII retention and deletion

The pii retention and deletion requirement (ISO/IEC 27018) means you must keep personal data only as long as your documented retention rules allow, then delete it in a controlled, provable way. To operationalize it fast, publish a retention schedule, map it to systems and third parties, automate deletion where possible, and keep audit-ready evidence of execution ¹.

Key takeaways:

• Document retention periods and deletion triggers for each PII category, then bind them to systems and contracts ¹.
• Treat deletion as an evidenced control: define “delete,” run jobs, validate results, and store logs and approvals ¹.
• Cover the hard parts explicitly: backups, legal holds, shared SaaS platforms, and downstream third parties ¹.

ISO/IEC 27018 is a privacy-focused standard for cloud service providers acting as PII processors. The practical expectation behind the pii retention and deletion requirement is simple: you should be able to show, on demand, that PII is not kept “just because it’s there,” and that deletion is not a hopeful manual step someone remembers to do later ¹.

For a Compliance Officer, CCO, or GRC lead, the fastest path is to convert this requirement into a small set of operating decisions: (1) what PII you hold, (2) why you hold it, (3) how long you’re allowed to hold it, (4) what event ends that justification, and (5) what deletion looks like in each system, including logs, backups, and third-party processors. Auditors tend to focus on evidence of execution, not policy prose. You need a retention schedule that maps to real data stores, and you need proof that deletions happen reliably and are controlled.

This page gives requirement-level implementation guidance you can hand to Legal, Engineering, Security, and Operations and use as an audit script.

Requirement: PII retention and deletion (ISO/IEC 27018)

Plain-English interpretation
You must define retention and deletion rules for PII, document them, apply them consistently, and be able to prove you followed them. “Documented requirements” usually come from contracts, customer instructions, applicable law, and internal policy decisions that translate those obligations into operational rules ¹.

Who it applies to

Entity scope

• Cloud PII processors providing services that store or process customer PII in the cloud ¹.

Operational context (where this breaks in practice)

• Production databases, data lakes, analytics pipelines, logs/telemetry, support tooling, CRM/ticketing attachments, and file stores.
• Developer environments (staging, QA) and “shadow” copies created for debugging.
• Backups, snapshots, archives, and replicated systems.
• Downstream third parties processing PII on your behalf (subprocessors), where deletion requires coordination via contract and technical process.

Regulatory text

Provided excerpt (summary record): “Baseline implementation-intent summary derived from publicly available framework overviews; licensed standard text is not reproduced in this record.”
Implementation-intent summary: “Retain and delete PII according to documented requirements.” ¹

What the operator must do

1. Define documented retention requirements for PII you process, based on customer instructions, contracts, and legal obligations you can substantiate ¹.
2. Implement deletion aligned to those requirements, including controls for exceptions like legal holds and technical constraints ¹.
3. Maintain evidence that retention is controlled and deletion occurs, not just planned ¹.

What you actually need to do (step-by-step)

Use this as an execution checklist.

Step 1: Build a PII retention schedule that engineers can implement

Create a retention schedule table with these minimum columns:

Field	What to decide	Example output
PII category	What type of PII is it?	Customer contact info; end-user identifiers; support attachments
Purpose	Why do you process it?	Account management; security; billing dispute handling
System(s) of record	Where is it stored?	Primary DB, object storage, ticketing system
Retention period / rule	How long can you keep it?	“Until contract termination + defined period” (use your legal basis)
Deletion trigger	What event starts deletion?	Account closure; customer request; contract end; purpose achieved
Deletion method	How is it deleted?	API delete; crypto-shred; lifecycle policy
Exceptions	What pauses deletion?	Legal hold; active investigation; regulatory retention
Evidence	What proves it happened?	Job logs, tickets, audit trail, system report

Write retention rules in implementable language. “Keep only as long as necessary” is not implementable without a concrete trigger and ownership.

Step 2: Map the schedule to data inventories and subprocessors

You need a mapping from each retention rule to:

• Data stores (tables/buckets/indices), including derived copies (analytics) and semi-structured stores (logs).
• Data flows (ETL jobs, message queues, exports).
• Third parties that receive the PII, with contract terms requiring retention alignment and deletion support ¹.

If you don’t already have a data map, start with the highest-risk PII and the highest-volume systems. This requirement fails most often on “unknown copies.”

Step 3: Define “deletion” per system, including backups

Deletion must be defined in a way you can defend in an audit and operate consistently:

• Logical deletion (soft delete) may be acceptable for product needs, but only if it is paired with hard deletion or irreversible anonymization on a defined schedule.
• Backups and archives need an explicit position: deletion may occur by expiration (backup lifecycle) rather than immediate purge, but you must document the method, timeline, and access restrictions until expiration. Align this with customer commitments.
• Encryption key destruction (crypto-erasure) can be a valid deletion method if keys are properly managed and destruction is provable.

Document these decisions in a “Deletion Standard” (one pager works) that engineering and audit both accept.

Step 4: Implement deletion workflows you can prove

Operationalize deletion through controlled workflows:

1. Intake: what starts deletion (customer request, automated trigger, contract end).
2. Authorization: who approves (data owner, legal for holds).
3. Execution: automated job or runbook; include retries and failure alerts.
4. Verification: confirm deletion in primary store and downstream systems; sample checks for large-scale deletions.
5. Closure: store evidence package and link it to the trigger record.

If you must start manually, make it ticket-driven with required fields (PII category, systems, request source, approver, completion evidence). Then automate system-by-system.

Step 5: Handle exceptions without breaking the control

Two exceptions cause most audit friction:

Legal hold / litigation

• Add a legal hold flag and workflow.
• Freeze deletion for scoped records.
• Log who invoked the hold, rationale, and release event.
• Ensure the hold does not expand into “we keep everything forever.”

Security and fraud investigations

• Treat as a time-bound exception with documented approval and periodic review.
• Keep retention and deletion rules for investigative datasets separate from general logs.

Step 6: Contract and third-party alignment

For cloud PII processors, deletion must extend to subprocessors:

• Contract clauses: deletion/return of PII upon instruction; retention limits; deletion timelines; certification or evidence support; backup handling.
• Offboarding checklist: confirm deletion/return; disable access; retrieve encryption keys or confirm destruction where applicable.

Daydream (as a workflow layer) is commonly used here to keep a single control record that ties the retention schedule, subprocessor list, and deletion evidence to an audit-ready narrative, instead of chasing proofs across tickets and cloud logs.

Required evidence and artifacts to retain

Auditors want both design and operating evidence. Keep:

Design artifacts

• PII retention policy and retention schedule (approved, versioned).
• Deletion standard (what “delete” means per system, including backups).
• Data inventory / system map showing where PII resides.
• Subprocessor list and contract templates/clauses relevant to retention and deletion ¹.

Operating artifacts

• Deletion job logs (system-generated), run reports, or lifecycle policy evidence.
• Tickets/records for manual deletions with approvals and completion proof.
• Exception registers: legal holds, investigation holds, and approvals.
• Periodic control testing results (spot checks, sampling outputs, reconciliation reports).
• Offboarding evidence for third parties: attestations, confirmation emails, or portal reports.

Common exam/audit questions and hangups

Expect these questions and prepare your “one-click” evidence:

1. “Show me your retention schedule and where it’s implemented.”
   Hangup: schedule exists, but no system mapping.

2. “Pick a PII type. Prove deletion happened for a closed account.”
   Hangup: deletion occurs in the app DB but not in logs, analytics, or ticket attachments.

3. “How do you delete from backups?”
   Hangup: undocumented backup lifecycle or unclear access controls for “deleted” data still in backups.

4. “How do you ensure subprocessors delete?”
   Hangup: contracts don’t require deletion evidence, or no offboarding workflow exists.

5. “What are your exceptions, and who approves them?”
   Hangup: informal Slack approvals, no time bounds, no review cadence.

Frequent implementation mistakes (and how to avoid them)

• Mistake: Writing retention rules without triggers.
  Fix: every rule needs a trigger event and an owner who can execute it.

• Mistake: Treating soft delete as deletion.
  Fix: define when hard delete/irreversible anonymization occurs, and keep evidence.

• Mistake: Ignoring derived data.
  Fix: inventory pipelines and define deletion propagation (or justify why derived datasets are outside scope, if true).

• Mistake: No position on backups.
  Fix: document backup retention, access controls, and expiration-based deletion; align customer commitments.

• Mistake: Third-party deletion is “assumed.”
  Fix: add contractual terms and an operational offboarding checklist with evidence collection.

Enforcement context and risk implications

No public enforcement cases were provided in the supplied source catalog for this requirement. Even without named cases here, treat this as a material control because retention failures increase breach impact, complicate legal discovery, and create contract noncompliance risk when customers require deletion on termination or instruction ¹.

30/60/90-day execution plan

This plan assumes you need an auditable baseline fast, then maturity.

Days 0–30: Establish the minimum auditable baseline

• Assign ownership: one control owner in GRC, one engineering owner for data stores.
• Draft and approve a retention schedule for top PII categories and top systems.
• Publish a deletion standard covering: production DB, object storage, logs, analytics, backups.
• Stand up a deletion ticket/workflow with required fields and approval gates.
• Identify subprocessors that touch PII and confirm contracts support deletion and retention alignment.

Days 31–60: Implement and prove operations

• Implement automated deletion for at least one high-volume system (account closure or customer request).
• Add verification: post-delete checks and exception handling.
• Build an evidence pack template: schedule + system mapping + sample deletion records + logs.
• Add legal hold workflow and register (even if rare).

Days 61–90: Expand coverage and reduce manual effort

• Expand automation to remaining priority systems (logs/telemetry and analytics are common gaps).
• Operationalize third-party offboarding evidence collection.
• Run an internal audit-style test: select records, trace end-to-end deletion, document gaps, remediate.
• Put monitoring in place: failed deletion jobs, backlog aging, exception review.

Frequently Asked Questions

What counts as “documented requirements” for PII retention and deletion?

Documented requirements are the retention and deletion rules you can point to in contracts, customer instructions, and internal policies that implement those obligations ¹. Auditors expect these rules to be specific enough to execute and test.

Do we need to delete PII immediately everywhere, including backups?

You need a documented, defensible method for backups, commonly expiration-based deletion through backup lifecycle controls. The key is that your approach is documented, consistently applied, and reflected in customer commitments ¹.

Is anonymization acceptable instead of deletion?

It can be, if anonymization is irreversible in practice and you document the method as your deletion mechanism for that system. Keep evidence that the transformation is applied per the retention schedule.

How do we handle PII in logs and telemetry?

First, reduce PII collection in logs through engineering standards and filters. Then apply log retention limits and deletion mechanisms (index lifecycle policies, storage lifecycle rules) and keep configuration evidence plus execution logs.

What evidence do auditors ask for most often?

They ask for a retention schedule mapped to systems, plus proof that deletions occurred for specific records and that exceptions are controlled ¹. System-generated logs and lifecycle configuration exports are stronger than screenshots alone.

How do we ensure third parties delete PII we sent them?

Put deletion and retention obligations in the contract, maintain a subprocessor inventory, and run an offboarding workflow that captures deletion confirmation or reports. Keep those confirmations linked to the termination or deletion trigger record.

Related compliance topics

• 2025 SEC Marketing Rule Examination Focus Areas
• Access and identity controls
• Access Control (AC)
• Access control and identity discipline
• Access control management

Footnotes

1. ISO/IEC 27018 overview