Anonymising Transaction Monitoring Alert Files for Audit – UK GDPR-compliant anonymisation per FCA SYSC 6

Transaction monitoring alert investigation files record the triggered alert parameters, the analyst's investigation rationale, the disposition decision, and any resulting SAR or exit action for a specific customer account. anonym.legal pseudonymises the customer identifiers in these files so audit and oversight teams can review alert-management quality and disposition consistency without processing account-holder personal data.

When this applies

This task applies when transaction monitoring investigation files are reviewed by second-line compliance, internal audit, or external assurance teams assessing the adequacy of the firm's transaction monitoring framework under FCA SYSC 6, and those reviewers require the investigative methodology rather than the specific customer's identity.

  1. Upload the alert investigation file, including the alert parameters, transaction summary, and analyst investigation notes.
  2. The engine identifies the customer's name, account references, transaction counterparty names, and any other personal identifiers in the file.
  3. Each individual and account identifier is pseudonymised consistently; alert parameters, transaction amounts and categories, investigation rationale, and disposition outcome are preserved.
  4. Escalation records, SAR-referral notes, and exit-decision documentation remain in clear text.
  5. A reversible mapping table is produced with UK/EU data residency.
  6. Release the pseudonymised file for audit review; restore originals before any regulatory inspection or SAR submission.

What you provide

  • Transaction monitoring alert record
  • Analyst investigation notes
  • Disposition decision and escalation record
  • Transaction summary extract (if separate from the alert record)

Limitations & cautions

  • The tool does not assess whether the alert parameters, investigation methodology, or disposition decision meet the standards expected by the FCA under SYSC 6.
  • Where an alert results in a SAR, the SAR must be processed separately and must not be pseudonymised for regulatory submission.
  • Transaction counterparty names that are corporate names rather than natural-person names are preserved unless you flag them for pseudonymisation.

FAQ

Are transaction amounts and alert thresholds preserved in the pseudonymised file?

Yes. Transaction amounts, alert rule parameters, and threshold values are preserved in clear text. Only natural-person identifiers are pseudonymised.

Can I batch-process a cohort of alert files for a thematic alert-quality review?

Yes. Upload multiple alert files in a batch. The engine applies consistent pseudonyms to individuals who appear in multiple files.

Does the tool handle alerts generated by automated transaction monitoring systems?

Yes. Files generated by automated systems — including rule-based and machine-learning-based alert outputs — are processed in the same way as manually prepared investigation notes.

Financial Services Compliance

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.