Anonymising Children Act 1989 Welfare Reports (Section 7) – UK GDPR-compliant anonymisation per Children Act 1989

A section 7 welfare report under the Children Act 1989 records the child's home circumstances, health, school performance, and both parents' views alongside full names, addresses, and professionals' identities. anonym.legal pseudonymises those identifiers while preserving the welfare analysis — parenting capacity, risk factors, and recommendations — so the report can be shared with instructed experts without unnecessary personal exposure.

When this applies

This task applies when a completed s.7 welfare report is shared with a jointly-instructed psychologist, an independent social worker, or a reviewing Guardian ad litem, and those professionals require the welfare narrative but do not need the parties' real identities at the instruction stage.

  1. Upload the s.7 welfare report (PDF or DOCX) to anonym.legal.
  2. The engine identifies all named individuals: child, both parents, wider family members, school contacts, health professionals, and the reporting officer.
  3. Each person receives a unique, consistent pseudonym; role labels (e.g. 'Mother', 'Teacher at School A') are preserved to maintain the narrative.
  4. Welfare analysis — parenting observations, risk indicators, contact recommendations, and the child's ascertainable wishes — remains in clear text.
  5. A reversible mapping table is produced with UK data residency.
  6. Release the pseudonymised report to the instructed expert; restore real identities before filing with the court.

What you provide

  • Section 7 welfare report (final or draft)
  • Any annexes (school reports, GP letters) filed with the welfare report
  • Instruction letter naming the CAFCASS officer or independent social worker (if relevant)

Limitations & cautions

  • Welfare reports contain special-category data (health, ethnic origin, religious beliefs of the child) within the meaning of UK GDPR Art. 9; additional care is required to ensure the mapping table is stored securely.
  • The tool pseudonymises personal data but does not assess the welfare conclusions or recommendations — obtain specialist family-law or social-work advice.
  • Re-identification must occur before any court hearing at which the report is relied upon.

FAQ

Is a section 7 welfare report subject to Family Procedure Rules confidentiality?

Yes. Documents filed in children proceedings are subject to confidentiality restrictions under FPR 2010. Using the pseudonymised copy for permissible expert instruction is compatible with those rules, but confirm with your instructing solicitor before sharing externally.

Can the child's own views be pseudonymised while preserving the substance?

Yes. Quotations from the child that are sufficiently distinctive to identify the child are pseudonymised at the name level. The substantive views and wishes are preserved.

Does the engine handle reports that use codenames for the child already?

Yes. If CAFCASS has already applied an initial or codename, the engine detects it as an entity and pseudonymises it consistently to prevent indirect identification.

How are multiple siblings in the same welfare report handled?

Each sibling is treated as a distinct data subject and assigned a unique pseudonym, preserving the sibling group structure within the report.

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.