Bank routing numbers

Detects references to bank routing numbers in financial and compliance documents. Commonly found in international regulatory filings, transaction records, and audit documentation.

Type

regex

Engine

boost_regex

Confidence

medium

Confidence justification

identifier/document-structure anchored regex with constrained context replaces phrase-only detection. Added context gating and exclusion rules improve precision and reduce incidental matches.

Detection quality

Mixed

Jurisdictions

global

Regulations

GDPR, PCI-DSS

Data categories

financial

Scope

wide

Platform compatibility

Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Degraded, Netskope: Unsupported

Pattern

(?is)\b(?:bank\s+routing\s+numbers)\b\s{0,80}\b[A-Z0-9][A-Z0-9\-/ ]{4,24}\b

Corroborative evidence keywords

bank routing numbers, bank, routing, numbers, financial, accounts, payments, bank account, account number, account no, BSB, routing number, sort code, IBAN, SWIFT, BIC, ID, identifier, number, reference (+25 more)

Proximity: 300 characters

Should match

• Bank routing numbers — Exact phrase marker match
• bank routing numbers — Case-insensitive phrase match
• Bank routing numbers — Normalized whitespace phrase
• structured record with identifier and contextual anchors — Structural anchor sample

Should not match

• unrelated generic text — No relevant phrase context
• placeholder value 12345 — Random text should not match phrase marker
• generic narrative without identifier/document anchors — Should not match plain mention
• template example placeholder record identifier — Template/sample context should be excluded even when anchor words are present

Known false positives

• Financial terminology appearing in published reports, accounting textbooks, regulatory guidance, or template documents without actual transaction data. Mitigation: Require corroborative evidence keywords within the proximity window. Cross-reference with structured financial identifiers to confirm actual sensitive data.
• In English (as the primary international business language), standard business terminology overlapping with financial detection keywords in routine correspondence and documentation. Mitigation: Increase confidence threshold when scanning business correspondence. Layer with transaction-specific patterns for higher precision.