Anonymize Broker-Dealer Customer Records for BSA Compliance Review – CCPA/HIPAA-compliant de-identification per 31 CFR §1023

Broker-dealer AML programs required under 31 CFR §1023 generate customer account records, risk profiles, and transaction histories that contain extensive personal data on investors. anonym.legal pseudonymizes personal identifiers in broker-dealer customer records so BSA compliance officers and auditors can review AML program adequacy and customer risk-profiling quality without processing actual customer personal data.

When this applies

Use this workflow when broker-dealer customer records — including account applications, investor profiles, and risk-rating records — are reviewed by BSA compliance officers, internal auditors, or external consultants evaluating AML program design and customer risk-rating consistency under 31 CFR §1023 requirements.

  1. Upload broker-dealer customer records — individually or as a batch — to anonym.legal in PDF, CSV, or DOCX format.
  2. The engine identifies customer names, SSNs or Tax IDs, dates of birth, addresses, account numbers, and any named associated persons or beneficial owners.
  3. Each natural person in the customer record is pseudonymized with a consistent placeholder; investment profile fields, risk rating, product holdings, and AML alert history flags are preserved.
  4. Account type classification, customer segment designation, and account-opening date remain in plain text.
  5. A reversible mapping table is encrypted and stored with US data residency.
  6. Export the pseudonymized records for BSA compliance review or audit use; retain originals for the applicable record-retention period under 31 CFR §1023.

What you provide

  • Broker-dealer customer account application and investor profile
  • AML risk-rating decision record
  • Customer transaction history extract (if included in the BSA review file)

Limitations & cautions

  • Regulatory examinations by FINRA, SEC, or FinCEN require re-identified original records; pseudonymized files are for internal BSA compliance review only.
  • The tool does not assess whether the broker-dealer's AML program meets the minimum requirements of 31 CFR §1023.
  • Customer records that include securities-holding data subject to Regulation S-P safeguard requirements benefit from pseudonymization but must also comply with Regulation S-P access controls on original records.
  • State-level blue-sky or money-transmitter requirements applicable to broker-dealers are out of scope; this workflow addresses federal BSA obligations under 31 CFR §1023 only.

FAQ

Are investment product holdings and portfolio balances pseudonymized?

No. Portfolio holdings, account balances, and investment product types are preserved as structural data necessary for AML risk-rating review. Only natural-person identifiers are pseudonymized.

Can pseudonymized broker-dealer customer records be used to benchmark risk-rating models?

Yes. Records pseudonymized to remove customer identities while preserving risk-profile fields, product types, and transaction flag history are suitable for risk-model benchmarking and calibration reviews.

Does this workflow cover customer records for both retail and institutional broker-dealer accounts?

Yes. The workflow applies to retail customer records and institutional client records alike. Named natural persons in institutional client records — such as authorized signers and beneficial owners — are pseudonymized.

Financial Services Compliance

About this page

We update this page when our platform or the law changes.

Read our founder note for how we work.

Each change shows up in the timestamp at the top.

We follow these rules

  • GDPR (EU 2016/679).
  • ISO/IEC 27001:2022.
  • NIS2 (EU 2022/2555).
  • HIPAA safe harbor under 45 CFR § 164.514(b)(2).

Our promise

We do not sell your data.

We do not train models on your text.

We store your files in Germany.

You can delete your account at any time.

You own your work.

Where we run

Our servers live in Falkenstein, Germany.

We use Hetzner. They hold ISO 27001 certification.

All data stays in the EU.

Backups run every day.

Need help?

Email support@anonym.legal.

We reply within one business day.

How we test

We run a full check suite on every release.

Each surface gets its own sweep script and report.

Human reviewers spot-check the output each week.

We track recall and precision on a labelled set.

Bad runs block the deploy.

What we never do

  • We never sell your information to third parties.
  • We never train models on what you upload.
  • We never keep your work after you delete it.
  • We never share keys with any outside firm.
  • We never run ads inside the product.

Plans in plain words

We sell credits, not seats.

One credit covers one short job.

Long jobs use a few credits each.

You can top up at any time.

Unused credits roll over each month.

Read the plans page for current rates.

Who built this

A small team of engineers and lawyers built this.

We ship from Europe and work in the open.

Our founder note spells out why we started.

Where to start

How the parts fit

A browser add-on cleans text inside Chrome.

A Word plug-in handles drafts in Office.

A small desktop tool works on whole folders.

An agent protocol link feeds large models safely.

All four share one core engine and one rule set.

Words from our team

We started this work after a lunch about cookies.

One friend kept getting odd ads on her phone.

We asked why a court file leaked through a draft.

We sketched the first build on a napkin that week.

By month three we had a tiny demo for a friend.

She used it on her first case the next day.

Common questions we hear

Can the tool read scanned PDFs? Yes, with OCR.

Does it work on long files? Yes, in small chunks.

Can I roll my own rule set? Yes, save it as a preset.

Does it run offline? The desktop build runs offline.

Do you keep my files? No, the cloud build wipes after each run.

Will it learn from my work? No, we never train on inputs.

A short tour of the workflow

Upload a file or paste a snippet of prose.

Pick the entities you want gone from the draft.

Choose a method: replace, mask, hash, encrypt, or redact.

Press run and watch the side panel show each hit.

Skim the result and tweak any rule that misfired.

Save the cleaned file or send it to a teammate.