Anonymizing UCC-1 Financing Statements Before Lien-Search Disclosure – CCPA/HIPAA-compliant de-identification per UCC §9-310

A UCC-1 financing statement filed to perfect a security interest under UCC §9-308 and §9-310 identifies the debtor by name and mailing address as required by UCC §9-503. anonym.legal anonymizes the debtor's personal identifiers in copies shared with third parties during due diligence, preserving the collateral description, filing date, and secured-party information needed to assess lien priority.

When this applies

This task applies when UCC-1 financing statement copies or lien-search results are shared with acquisition advisers, lenders, or investors during due diligence, and those parties need to assess the collateral description and lien priority without accessing the full personal-data content of each filing.

  1. Upload the UCC-1 financing statement copies or lien-search results export to anonym.legal.
  2. The engine identifies debtor names, mailing addresses, and any individual guarantor names listed in the filing.
  3. Each named individual is anonymized consistently across all filings in the batch.
  4. Collateral descriptions, filing dates, secured-party names, and file numbers are preserved for lien-priority analysis.
  5. A mapping table is generated with US data residency.
  6. Release the anonymized lien-search results for due-diligence review; restore originals before any formal lien-priority opinion is issued.

What you provide

  • UCC-1 financing statement copies or lien-search results
  • Continuation or amendment statements for the same debtor
  • Termination statements if relevant to the lien-search scope

Limitations & cautions

  • UCC-1 filings are public records and debtor names are required by UCC §9-503 for search purposes. Anonymization is appropriate for preliminary due-diligence review only; formal lien-priority opinions require the original filing data.
  • The tool does not assess lien priority, attachment, or perfection under UCC Article 9 — obtain qualified legal advice.
  • Collateral descriptions using defined-term references to the debtor's name may require manual review after anonymization.

FAQ

Why anonymize a UCC-1 filing if it is a public record?

Even though UCC-1 filings are searchable public records, circulating copies in due-diligence packages still processes the debtor's personal data within the meaning of applicable data-protection obligations. Anonymizing the review copy limits unnecessary data exposure during preliminary assessment.

Does anonymizing the debtor name affect the collateral description?

Collateral descriptions that reference the debtor by name (e.g., 'all assets of [Debtor Name]') will have the name component anonymized. Verify the collateral description in the anonymized copy before using it for lien-priority analysis.

Can I process a full lien-search results package covering multiple debtors?

Yes. Upload the full package in a batch. Each debtor is tracked as a distinct entity and receives a unique pseudonym, preserving the structure of the results across multiple filings.

Commercial Contracts

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.
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Plans in plain words

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One credit covers one short job.

Long jobs use a few credits each.

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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.