Pseudonymising Financial Remedies Applications (Form A) – UK GDPR-compliant anonymisation per Matrimonial Causes Act 1973

A Form A financial-remedies application names both parties, their solicitors, and references children's details in income-needs calculations under the Matrimonial Causes Act 1973. anonym.legal pseudonymises those personal identifiers — preserving asset schedules, income figures, and the relief sought — so the application can be shared with financial experts without exposing the parties' identities.

When this applies

This task applies when a Form A and accompanying schedules are circulated to forensic accountants, property valuers, or pension actuaries who need to assess the financial picture but have no legitimate need to know the parties' real identities at the preliminary expert-instruction stage.

  1. Upload the Form A and any accompanying asset schedule or narrative statement.
  2. The engine identifies both parties' names, solicitors' details, and children's names across all sections.
  3. Each natural person receives a consistent pseudonym; asset values, income figures, pension transfer values, and relief-sought particulars are preserved in clear text.
  4. Pension details, property addresses (if included), and business valuations remain accessible for the expert's review.
  5. A reversible mapping table is produced with UK data residency.
  6. Release the pseudonymised application to the expert; restore real identities before any court submission or order.

What you provide

  • Form A (notice of intention to proceed with application for financial remedies)
  • Schedule of assets and income if attached
  • Expert instruction letter naming the referring solicitor (optional, to pseudonymise if required)

Limitations & cautions

  • Court-bound documents must re-identify all parties before submission; the pseudonymised version is for expert or adviser instruction only.
  • Property addresses are pseudonymised if they appear as personal data tied to an individual; standalone postcodes used for valuation zones are preserved.
  • anonym.legal does not advise on the adequacy of the s.25 Matrimonial Causes Act 1973 factors disclosure — obtain specialist family-finance legal advice.

FAQ

Can I pseudonymise a Form A at the same time as a Form E financial statement?

Yes. Upload both documents in the same batch so individuals named in both receive consistent pseudonyms across the entire document set.

Are pension policy numbers pseudonymised?

Pension policy numbers are not personal data in isolation under UK GDPR and are preserved. The policy holder's name is pseudonymised.

What if a business owned by one party is named after that party?

Company names that incorporate an individual's personal name (e.g. 'Smith Consulting Ltd') are treated as quasi-identifiers and pseudonymised to prevent indirect identification.

How does the tool handle jointly held assets listed in the application?

Jointly held assets are preserved in clear text with pseudonymised owner names. The joint-ownership structure is maintained so the expert can assess the ownership split.

Family Law

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.
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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.