Pseudonymising Care Proceedings Social Work Statements – UK GDPR-compliant anonymisation per Children Act 1989

A care proceedings social work statement is a formal evidential document filed under Children Act 1989 s.31 setting out threshold criteria, the child's developmental history, and parenting-capacity evidence. Around 18,000 children entered care proceedings in 2023 (Cafcass). anonym.legal pseudonymises all personal identifiers while preserving the factual chronology and risk analysis for instructed experts.

When this applies

This task applies when a local authority social work statement or connected evidence (including threshold criteria particulars under CA 1989 s.31) is shared with a jointly-instructed independent social worker, a parenting assessor, or legal-aid oversight for quality review, and the recipient requires the substantive welfare and risk narrative rather than the named parties' personal data.

  1. Upload the social work statement (and any connected chronology or genogram) to anonym.legal.
  2. The engine identifies the child, parents, extended family members, social workers, health visitors, teachers, and any other professionals named in the statement.
  3. Each individual receives a consistent pseudonym; role labels (e.g. 'Allocated Social Worker', 'Maternal Grandmother') are preserved.
  4. Factual chronology, risk-assessment conclusions, parenting-capacity analysis, and threshold criteria facts remain in clear text.
  5. A reversible mapping table is produced with UK data residency.
  6. Release the pseudonymised statement to the expert or reviewer; restore real identities before court filing or service on parties.

What you provide

  • Social work statement (initial and any updating statements)
  • Chronology of significant events (if filed separately)
  • Genogram or family composition schedule

Limitations & cautions

  • Social work statements contain special-category data (health, racial or ethnic origin of the child and family) under UK GDPR Art. 9 — the mapping table must be stored with heightened security and processed under DPA 2018 Sch.1 Part 2 substantial public interest.
  • Genograms containing named individuals in graphical format require OCR conversion to text before entity detection can operate fully.
  • anonym.legal does not assess the evidential sufficiency of the CA 1989 s.31 threshold criteria — obtain specialist public-family-law advice.

FAQ

Are the threshold criteria facts pseudonymised or preserved in the statement?

The factual threshold criteria (e.g. dates, types of harm, and risk indicators) are preserved in clear text. Only the names of the individuals to whom those facts relate are pseudonymised.

Can the pseudonymised statement be shared with the parents' legal representatives?

Disclosure to parties' legal representatives within proceedings is governed by FPR 2010 and the court's disclosure orders — the pseudonymised version is for expert instruction only. Real versions are disclosed to parties in the normal way.

How does the engine handle siblings named in a statement about one child?

Each sibling is treated as a distinct data subject and pseudonymised individually, preserving the sibling group context within the statement.

Does the tool process local authority safeguarding records appended to the statement?

Yes. Supporting safeguarding records uploaded in the same batch are processed with the same entity registry, ensuring consistent pseudonyms across all documents.

What are the data-protection obligations for care proceedings statements?

Care proceedings statements contain Article 9 special-category data — health histories, ethnic origin, and criminal-record disclosures. UK GDPR requires a Schedule 1 DPA 2018 condition to process this data, and breaches risk ICO fines of up to £17.5 million or 4% of global annual turnover. According to MoJ Family Court Statistics, around 248,000 family cases were started in England and Wales in 2023, with care proceedings representing roughly 18,000 to 19,000 children per year (Cafcass 2023). Pseudonymising before expert instruction provides a documented data-minimisation measure.

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.