By · Last updated 2026-06-30

€4.7B in GDPR Fines to US Financial Firms

Financial Data Protection Across Jurisdictions

Cross-border transactions mean multi-jurisdiction compliance. anonym.legal detects PCI-DSS, GDPR, and CCPA-relevant entities across 48 languages, with reversible encryption for regulatory audits and investigation requests.

€4.7B
GDPR fines to US companies
285+
Financial entity types
48
Languages supported

Related: Browse finance practice areas

과제

금융 기관은 엄격한 데이터 보호 요건에 직면합니다:

  • PCI-DSS는 결제 카드 데이터 보호를 요구합니다
  • 규제 보고는 데이터 최소화를 요구합니다
  • 사기 조사팀은 안전한 데이터 공유가 필요합니다
  • 고객 커뮤니케이션에는 민감한 금융 정보가 포함됩니다

해결책

금융 서비스 데이터를 위한 준수 익명화.

Financial Sector Enforcement Actions

Financial institutions face strict regulations globally. Cross-border data transfers without adequate PII protection lead to significant enforcement actions.

RegulationJurisdictionMax Penaltyanonym.legal Coverage
PCI-DSSGlobal$500K/month + card brand fees
GDPREU/EEA4% global revenue or €20M
CCPA/CPRACalifornia$7,500 per intentional violation
SOXUS Public Companies$5M + 20 years imprisonment

해결책

PCI-DSS 지원

형식 보존 옵션으로 결제 카드 번호를 탐지하고 보호합니다.

규제 준수

규제 보고를 위한 데이터 최소화 요건을 충족합니다.

사기 조사

팀 간 및 당국과 조사 데이터를 안전하게 공유합니다.

암호화 옵션

필요할 때 가역적 익명화를 위한 AES-256-GCM 암호화.

Financial Entity Detection

anonym.legal detects all common financial data types across global formats, ensuring compliance regardless of where your customers are located.

Credit card numbers (all major brands)
IBAN codes (140+ countries)
SWIFT/BIC codes
US bank account numbers
US Social Security numbers
UK National Insurance numbers
German Steuer-ID
Crypto wallet addresses
VAT numbers (EU)
Tax identification numbers
Account holder names
Transaction references

Trusted by financial institutions

ISO 27001 Aligned
Germany (EU) Hosted
AES-256-GCM Encryption
PCI-DSS Entities

오늘 금융 데이터를 보호하세요

금융 서비스 요건을 논의하려면 문의하세요.

Limitations / Important note

  • Using this tool does not by itself satisfy financial-sector regulatory obligations; assess compliance for your jurisdiction.
  • Detection is probabilistic; high-stakes outputs should be human-reviewed. This is not legal advice.

How we measure — our methodology

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.