Anonymising Form E Financial Statements and Bundles – UK GDPR-compliant anonymisation per Matrimonial Causes Act 1973

A Form E financial statement identifies the party's income, assets, liabilities, pension entitlements, address, and employer details — the most data-intensive document in financial-remedy proceedings under the Matrimonial Causes Act 1973. anonym.legal pseudonymises those personal identifiers while preserving every financial figure so counsel and experts can advise on the settlement without unnecessary personal-data exposure.

When this applies

This task applies when a completed Form E and its supporting bundle — bank statements, payslips, pension valuations, property valuations, and business accounts — are shared with a financial neutral or expert for analysis, and the party wishes to minimise personal-data disclosure to the minimum necessary.

  1. Upload the Form E and all supporting documents (bank statements, payslips, valuation reports, business accounts) in a batch.
  2. The engine identifies the applicant's name, address, date of birth, National Insurance number, employer, and any named dependants across all uploaded documents.
  3. Each natural person (party, dependants, named employer contacts) is pseudonymised consistently across the entire batch.
  4. All financial figures — income, capital assets, pension values, liabilities, income needs, and housing costs — are preserved in clear text.
  5. A consolidated mapping table for the batch is produced with UK data residency.
  6. Release the pseudonymised bundle for adviser review; restore real identities before the First Appointment or any subsequent court hearing.

What you provide

  • Completed Form E
  • Three months' bank statements for all accounts
  • Payslips and P60 for the previous tax year
  • Pension Cash Equivalent Transfer Value (CETV) statements
  • Property valuation or estate-agent letters

Limitations & cautions

  • Bank statements with printed names and sort-code/account combinations require careful post-processing review to confirm all personal identifiers are captured.
  • The tool pseudonymises personal data in supporting documents but cannot verify the accuracy or completeness of the disclosed financial information.
  • Court disclosure obligations require genuine full disclosure; pseudonymisation of the shared copy does not reduce the party's disclosure duties.

FAQ

Does pseudonymising Form E affect my full-and-frank disclosure obligation?

No. Your disclosure obligation runs to the court and opposing party in the proceedings. The pseudonymised copy is for preliminary adviser or expert use. The court copy must bear your real name and all required personal details.

Can I process payslips that contain employer names as well as employee names?

Yes. Both the employee's name and the employer's trading name (if it incorporates a personal name) are detected and pseudonymised. Generic company names not tied to an individual are preserved.

How does the tool handle redacted bank statements provided by the bank?

Statements pre-redacted by the bank (e.g. with account numbers partially obscured) are processed as presented. The tool pseudonymises any remaining personal identifiers visible in the document.

Are pension scheme names pseudonymised?

Pension scheme names are not personal data and are preserved. The policy holder's name is pseudonymised.

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.
  • 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.