Is this legal advice?

No. This is a template for the firm's counsel to adapt. Legal classification of synthetic data is fact-specific (depends on generation methodology, calibration source, residual re-identification risk) and jurisdiction-specific. The template surfaces the structural argument; firm-specific counsel must verify each element applies to the specific corpus and use case.

Why is the GDPR section so short?

Because the analytical answer is short: synthetic data is not personal data within the meaning of Article 4(1) GDPR. The GDPR's regulatory architecture cleanly excludes data not relating to a natural person. UK GDPR, EU GDPR, Swiss FADP, and Canadian PIPEDA all use comparable definitions; the same conclusion follows.

What if our regulator hasn't ruled on synthetic data?

Most haven't ruled definitively. The structural argument here — synthetic data is not personal data because no real person is represented — relies on the foundational definition of personal data, not on a regulator's specific ruling. Firms generally adopt this position with internal-counsel sign-off, monitor for regulatory developments, and refresh the memo annually.

Synthetic-Data License Memo Template (Internal Legal)

Memorandum

To: [MEMO_TO]

From: [MEMO_FROM]

Date: [MEMO_DATE]

Re: Classification of [SYNTHETIC_DATA_VENDOR] synthetic-wealth-data corpus under [FIRM_NAME]'s data and privacy policies

1. Summary

[FIRM_NAME] has procured a synthetic-wealth-data corpus from [SYNTHETIC_DATA_VENDOR] for use in: [USE_CASE]. This memorandum documents the legal classification of that corpus under the firm's data-classification policy, third-party-data policy, and applicable privacy frameworks. The conclusion: the corpus is not customer information and not personal data within the meaning of GLBA, GDPR, CCPA, or comparable frameworks, because no real individual is represented in the data. Accordingly, the firm's customer-data handling controls, the FTC Safeguards Rule's element 314.4(c) requirements as applied to NPI, and HIPAA do not apply to the corpus.

2. Nature of the corpus

[SYNTHETIC_DATA_VENDOR]'s corpus is synthetic in the strict sense: every record is generated by an algorithm against a calibrated benchmark distribution; no record represents an actual individual. [SYNTHETIC_DATA_VENDOR] has provided written attestation, under contractual penalty of default, that the corpus contains no real customer information of any party. The firm has reviewed the attestation and the calibration methodology and concurs.

What goes here in the firm's adaptationguidance — delete before sending

If your firm's privacy or compliance team has additional verification (probabilistic re-identification testing, third-party attestation, audit results), insert the citations here. The stronger this paragraph, the cleaner the downstream classification argument.

3. Classification under firm policy

The corpus is classified as internal-use data, equivalent to firm-developed analytical artifacts. It is not classified as: (a) customer information; (b) third-party data subject to standard third-party data controls; (c) confidential information of any third party (the vendor's license agreement governs separately).

Customer-information controls (encryption-at-rest of customer fields, customer-deletion-on-request, customer-access provision) do not apply to the corpus.
Third-party data controls applicable when ingesting external customer data sets do not apply to the corpus.
Vendor management controls (vendor risk review, BAA where applicable, license management) do apply to the contractual relationship with [SYNTHETIC_DATA_VENDOR].

4. Privacy-framework analysis

GLBA / FTC Safeguards Rule. The Safeguards Rule applies to non-public personal information of customers. Synthetic data containing no personal information of any actual individual is structurally outside the rule's scope.

GDPR / UK GDPR. Personal data is defined as information relating to an identified or identifiable natural person. Synthetic data, by construction, does not relate to any natural person. The GDPR's recital 26 explicitly addresses the comparable case of anonymous information; synthetic data is structurally analogous.

CCPA / CPRA. Personal information is defined as information that 'identifies, relates to, describes, [or] is reasonably capable of being associated with' a particular consumer or household. Synthetic households generated against a benchmark distribution are not 'reasonably capable of being associated with' any actual consumer.

HIPAA. No protected health information is present, and the corpus is not used in connection with health-care operations as defined in 45 CFR 164.501. The Business Associate Agreement framework does not apply.

5. License terms (summary)

[SYNTHETIC_DATA_VENDOR] has granted [FIRM_NAME] a subscription license. Permitted uses include internal evaluation, internal testing, demo / sales support. Prohibited uses include redistribution, sublicensing, productization (re-selling derived corpora), and training of public AI models. The full license terms are filed with the firm's contracts management system.

6. Conclusion

The [SYNTHETIC_DATA_VENDOR] synthetic-wealth-data corpus is appropriately classified as internal-use data under [FIRM_NAME]'s policies. Customer-information controls do not apply. Third-party-data controls do not apply. Vendor management controls do apply. Privacy frameworks do not apply because no real personal information is present.

This memorandum is filed with the firm's privacy / compliance team and refreshed annually or on material change to the corpus, the use case, or the underlying privacy frameworks.

Before sendingguidance — delete before sending

This is a template. Have firm-specific counsel review before relying on it. Privacy-framework applicability is fact-specific, and your firm's data-classification policy may have idiosyncrasies that require adjustments.