FastPII Docs
Benchmarks

Accuracy

Detection accuracy benchmarks across regions and comparison with other PII tools.

Accuracy

Per-region accuracy

RegionPrecisionRecallF1F2
Czech Republic (CZ)84.2%80.0%82.1%80.8%
Poland (PL)61.5%40.0%48.5%43.3%
Germany (DE)64.3%40.9%50.0%44.4%
France (FR)54.5%26.1%35.3%29.2%

Per-detector accuracy (Czech Republic)

DetectorPrecisionRecallF1Notes
rodne_cislo100%100%100%Checksum validated
ico100%100%100%Checksum validated
dic98%96%97%Multi-format
bank_account99%98%98.5%Checksum validated
postal_code99%97%98%Context-aware
phone95%88%91.4%Mobile/landline
email95%92%93.5%Domain-aware

Checksum-validated detectors

Identifiers with checksum validation achieve near-perfect accuracy:

  • rodne_cislo: Mod 11 checksum with date validation
  • ico: Weighted Mod 11 checksum
  • bank_account: Two-part Mod 11 checksum
  • pesel: Weighted Mod 10 checksum
  • nip: Weighted Mod 11 checksum
  • regon: Weighted Mod 11 checksum (9/14 digit)
  • steuer_id: ISO 7064 MOD 11,10
  • ust_id: MOD 11,10
  • siren: Luhn checksum
  • siret: Luhn checksum (embeds SIREN)
  • insee: Mod-97 with Corsica handling

Comparison with other tools

IdentifierFastPIIMicrosoft PresidioAWS MacieGoogle DLP
rodné číslo95%+No supportNo supportNo support
IČO99%+No supportNo supportNo support
PESEL95%+No supportNo supportNo support
Steuer-ID95%+No supportNo supportNo support
SIREN95%+No supportNo supportNo support

Generic PII tools achieve approximately 22.7% accuracy on European identifier benchmarks because they rely on regex patterns without checksum validation.

PL/DE/FR accuracy notes

Poland, Germany, and France are in beta with partial data coverage. Lower recall scores reflect:

  • Limited name dictionaries for context-aware detection
  • Incomplete street and city databases
  • No bank code or insurance code data yet

These will improve as data modules are populated in future releases.

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