Actuarial Dataset De-Identification with anonym.plus

Turn pricing data into anonymous rows that sit outside GDPR.

Actuarial dataset de-identification is the removal of personal data from a pricing extract. Once it is truly anonymous, it is no longer personal data under GDPR Recital 26 and falls outside the law. anonym.plus does this on an EU device.

When this applies

Pricing and reserving work lean on large extracts of historical rows. Sending those to a cloud tool is a disclosure risk. Local work avoids it.

How anonym.plus handles it

  1. Point anonym.plus at the export folder on your server.
  2. It scans the ID columns and any free-text fields.
  3. Steady aliases keep cohort joins intact.
  4. Turn off the re-link key for true anonymity.
  5. Review the summary and tune the column rules.
  6. Save the clean table on your device.

What you need to provide

PHI entity types detected

Categoryanonym.plus entity typeExample
NamesPERSONinsured_name → [PERSON_n]
Member IDUS_HEALTH_PLAN_BENEFICIARYpolicy_id → [POLICY_n]
DatesDATE_TIMEincept_date → shifted [DATE]
AgeAGEexact age 91 → [AGE_90+]
AddressLOCATIONpostcode → [REGION]
AccountACCOUNT_NUMBERacct field → [ACCOUNT_n]

Compliance achieved

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Limitations & cautions

An exact age above 89 is a re-identification risk and is grouped to 90+. A rare claim outlier in a small region can still narrow identity. Weigh the residual risk and keep no re-link key before you treat the table as anonymous.

Frequently asked questions

Why is age above 89 grouped?

Very high ages point to few people, so they raise re-identification risk. The tool buckets them into a 90+ band to lower that risk.

Can cohorts stay linkable after the swap?

Only with an alias map, which makes the result pseudonymous. For true anonymity, turn the map off so no key remains.

Does modelling still work on the clean table?

Yes. Aliases keep joins steady, so cohort models run while no real identity is left.