Anonymising Schedule 1 CA 1989 Financial Applications – UK GDPR-compliant anonymisation per Children Act 1989

A Schedule 1 Children Act 1989 application is a financial-provision application for a child born outside marriage, requiring full disclosure of both parents' income, assets, earning capacity, and housing requirements. Around 248,000 family cases were started in 2023 (MoJ). anonym.legal pseudonymises parents' personal details and child identifiers while preserving every financial figure for expert and legal review.

When this applies

This task applies when a Schedule 1 Children Act 1989 application and supporting financial disclosure are shared with a forensic accountant, pension actuary, or specialist family-finance solicitor who requires the CA 1989 Sch.1 financial detail but not the parties' real identities at the instruction stage.

  1. Upload the Schedule 1 application and all supporting financial evidence in a batch.
  2. The engine identifies the applicant parent, respondent parent, and child across all documents.
  3. Each individual receives a consistent pseudonym; income, capital, housing costs, earning capacity, and the financial provision sought are preserved in clear text.
  4. Business-ownership interests and trust structures referenced in the disclosure are preserved; named beneficiaries subject to the proceedings are pseudonymised.
  5. A reversible mapping table is produced with UK data residency.
  6. Release the pseudonymised bundle for expert review; restore real identities before court filing.

What you provide

  • Schedule 1 Children Act 1989 application
  • Both parties' financial disclosure statements
  • Business accounts or trust documentation (if relevant to the asset base)

Limitations & cautions

  • CA 1989 Sch.1 proceedings involve both child-welfare (CA 1989 s.1) and financial considerations — the tool pseudonymises personal data but does not assess the appropriateness or quantum of the financial provision sought.
  • Trust structures naming beneficiaries other than the parties and child may require bespoke entity-detection configuration — contact support for complex trust cases.
  • The court-bound version must re-identify all parties before submission under FPR 2010.

FAQ

Are the child's living costs and needs preserved in the pseudonymised document?

Yes. The child's living costs, housing needs, and education requirements are preserved in full. Only the child's name and any identifying personal details are pseudonymised.

How does the tool handle a respondent who has significant offshore assets?

Offshore asset descriptions, jurisdiction, and estimated values are preserved in clear text. Named trustees or account holders are pseudonymised where they are natural persons.

Can I use this workflow for a Schedule 1 case involving a cohabiting couple?

Yes. Schedule 1 applies regardless of whether the parents were married; the tool processes the financial application identically in both cases.

What data-protection obligations apply to Schedule 1 financial disclosure?

Schedule 1 applications under the Children Act 1989 often involve child-related data — which qualifies as Article 9 special-category data under UK GDPR when combined with health or welfare information. Business accounts and trust documentation shared with forensic experts must be kept to the minimum necessary. UK GDPR fines can reach £17.5 million or 4% of global annual turnover under Data Protection Act 2018 s.157. Pseudonymising parents' and child's identifiers before expert instruction demonstrates compliance with Article 5(1)(c) data-minimisation obligations.

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 company HQ is in Saarbrücken, Germany. Our servers run in Hetzner's Falkenstein datacenter.

Hetzner holds 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.