Pseudonymising FCA Skilled-Person Reports for Review – UK GDPR-compliant anonymisation per FSMA 2000

Skilled-person reports commissioned under FSMA 2000 contain detailed findings on the firm's systems and controls and may reference named senior managers, named employees, and named customers in their findings sections. anonym.legal pseudonymises those individuals so the firm's legal and compliance teams can analyse report findings and prepare responses without processing named individuals' data in non-essential workflows.

When this applies

This task applies when extracts from a skilled-person report are circulated internally for legal analysis, management response preparation, or remediation planning, and the recipients require sight of the findings and control-gap analysis but have no need to know the identities of the named individuals referenced in the report.

  1. Upload the skilled-person report extract (PDF or DOCX) to anonym.legal.
  2. The engine identifies named senior managers, employees, and customers referenced in findings sections and illustrative case examples.
  3. Each individual is pseudonymised with a distinct, consistent pseudonym; findings descriptions, control gaps, regulatory-standard references, and remediation recommendations are preserved.
  4. Report section structure, page references, and the skilled person's assessment ratings remain in clear text.
  5. A reversible mapping table is produced with UK/EU data residency and access restricted to the legal and compliance team.
  6. Release the pseudonymised extract for internal analysis; restore originals for the FCA response and any regulatory proceedings.

What you provide

  • Skilled-person report extract (findings sections, case examples, and recommendations)
  • Internal management-response draft (if it references named individuals from the report)

Limitations & cautions

  • The full skilled-person report as submitted to or received from the FCA must retain real names; the pseudonymised extract is for internal circulation only.
  • Findings that reference named customers as illustrative case examples are pseudonymised; the control-gap analysis and regulatory breach description are preserved.
  • The tool does not assess the legal adequacy of any management response to the skilled-person's findings.

FAQ

Can I share a pseudonymised report extract with the board without breaching FCA confidentiality obligations?

Pseudonymisation removes personal identifiers but does not address FCA confidentiality obligations that may attach to the report itself. Obtain legal advice on the firm's obligations regarding report confidentiality before sharing any version of the report.

Are case-example customers pseudonymised separately from named employees?

Yes. Each natural person — whether a customer used as a case example or a named employee in a finding — receives a distinct pseudonym, with their category (customer vs employee) preserved as context.

Does the tool handle reports that span multiple years of review?

Yes. Named individuals referenced across multiple sections or years of review receive consistent pseudonyms throughout the document.

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.