Insurance Audit Dataset De-Identification with anonym.plus

Clear IDs from the sample pull while the reviewed fields stay.

In simple terms, PII redaction is the on-device process of finding and masking personally identifiable information in a document before it is shared.

Insurance audit dataset de-identification is the removal of UK GDPR Art. 9 identifiers from a sampled pull. The pull exists to test billing accuracy against the record-keeping standard the FCA's SYSC 9 sets, and UK GDPR Art. 5(1)(e) separately limits how long the underlying rows may be kept once the audit purpose is served. anonym.plus runs on your device. The reviewed fields stay clear, but the rows no longer name anyone.

When this applies

A pull samples many records to test billing accuracy against the FCA's own record-keeping requirements. Sending that to a cloud tool is a disclosure risk on top of the storage-limitation question Art. 5(1)(e) already raises for how long the sample itself should be kept. Local work clears the IDs and keeps the sample.

How anonym.plus handles it

  1. Point anonym.plus at the export on your server.
  2. It scans the ID columns and the free-text fields.
  3. Steady aliases keep links across sampled rows.
  4. Keep the sampled fields and the error flags.
  5. Replace each ID with a steady alias, or redact it.
  6. Save the clean pull on your device.

What you need to provide

Patient data entity types detected

Categoryanonym.plus entity typeExample
NamesPERSONpatient_name → [PATIENT_n]
Member IDUK_HEALTH_INSURANCE_MEMBERmbr_id → [MEMBER_ID_n]
AccountACCOUNT_NUMBERacct field → [ACCOUNT_n]
DatesDATE_TIMEservice_date → shifted [DATE]
Record IDsMEDICAL_RECORD_NUMBERmrn field → [MRN_n]
Free textPERSON / LOCATIONinline names → aliases

Compliance achieved

Anonymise audit datasets offline — see plans & start free →

Limitations & cautions

These pulls mix tidy columns with messy free text. Column rules handle the first well. Free-text fields need the same review as any note. Test a sample before a full run, and check that date-shifting keeps the gaps your review needs.

Frequently asked questions

Can sampled rows stay linked to each other after the swap?

Yes. A steady alias map swaps each ID the same way, so sampled rows for one person still join for the audit while no real identity is left in the pull.

Do the sampled fields survive the swap?

Yes. The reviewed fields and error flags stay untouched. Only the IDs change, so the pull is still useful for the SYSC 9 record-keeping review it supports.

How long should an audit sample itself be kept?

No longer than the audit purpose needs, since UK GDPR Art. 5(1)(e) limits retention once that purpose is served. De-identifying the sample as soon as the review is complete is one way to reduce that storage-limitation exposure without waiting for a separate deletion process.