Anonymize executive compensation disclosure documents for benchmarking – CCPA/HIPAA-compliant de-identification per 17 CFR §229.402

Reg S-K §229.402 mandates detailed disclosure of named executive officer compensation in proxy statements and annual reports, linking individual names to salary, bonus, equity awards, and perquisite totals. anonym.legal pseudonymizes these named-individual pay records so compensation consultants, remuneration advisers, and peer-benchmarking teams can analyze pay structures without processing individually identified compensation data.

When this applies

Use this workflow when executive compensation schedules, tally sheets, or Reg S-K §229.402 disclosure drafts are shared with external compensation consultants, remuneration committees, or governance advisers for benchmarking where the executive's identity is not required.

  1. Upload executive compensation schedules, pay tally sheets, or draft §229.402 disclosure tables in PDF, XLSX, or DOCX format.
  2. The engine identifies named executive officers across all compensation tables: Summary Compensation, Grants of Plan-Based Awards, Outstanding Equity Awards, Option Exercises, Pension Benefits, and Nonqualified Deferred Compensation.
  3. Each named executive is pseudonymized consistently across every compensation table in the document set.
  4. Pay figures, equity award values, vesting schedules, and performance metrics are retained as structural analytical content.
  5. Narrative CD&A sections referencing executives by name are pseudonymized at every name occurrence while preserving compensation-philosophy and benchmarking-methodology descriptions.
  6. The reversible mapping is stored encrypted; re-identification is available when the final proxy draft must be prepared.
  7. The pseudonymized output is exported for distribution to compensation consultants and committee advisers.

What you provide

  • Executive compensation tally sheets and draft §229.402 tables in PDF, XLSX, or DOCX format
  • CD&A narrative sections in DOCX format
  • List of named executive officers to be pseudonymized

Limitations & cautions

  • anonym.legal does not assess whether the compensation program satisfies say-on-pay advisory vote requirements or Reg S-K §229.402 disclosure adequacy; those determinations require compensation counsel.
  • CD&A narratives that describe an executive's role or tenure in highly specific terms may retain indirect identifiability even after name pseudonymization.
  • Peer-benchmarking comparisons that reference external public-company proxy data are not processed by this tool; only uploaded documents are pseudonymized.
  • The tool does not calculate tally sheet figures or validate pay-disclosure arithmetic.

FAQ

Can the tool pseudonymize executives across all six Reg S-K §229.402 compensation tables simultaneously?

Yes. All six required tables are processed in a single pass with consistent pseudonym assignments, so the same executive's identity is replaced by the same placeholder in every table.

Will performance metrics and goal targets be preserved for benchmarking?

Yes. Performance metrics, EBITDA targets, TSR percentiles, and vesting conditions are structural content and are preserved in plain text. Only the names of the executives to whom those targets apply are pseudonymized.

Can this workflow be used for pay-ratio disclosure analysis under §229.402(u)?

Yes. The CEO's compensation figure used in the pay-ratio calculation is linked to the named CEO and can be pseudonymized for consultants reviewing the ratio methodology without disclosing the specific executive's identity.

Securities & Corporate Disclosure

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.