Employee withholding elections

Detects references to employee withholding elections 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
Data categories: financial
Scope: wide
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Degraded, Netskope: Unsupported

Pattern

(?is)\b(?:employee\s+withholding\s+elections|withholding\s+election|tax\s+withholding|filing\s+status|federal\s+withholding|state\s+withholding|payroll\s+deduction|employee\s+declaration)\b

Corroborative evidence keywords

employee withholding elections, employee, withholding, elections, payroll, tax, operations, benefits, termination, hire date, salary, compensation, 401k, W-2, I-9, superannuation, police check, working with children check, WWCC, Blue Card (+85 more)

Proximity: 300 characters

Should match

employee withholding elections — Primary topic phrase match
withholding election — Case-insensitive topic phrase match
tax withholding — Alternative topic phrase match
filing status — Additional topic phrase match

Should not match

unrelated generic text without domain phrases — No relevant topic phrases present
placeholder value 12345 — Random text should not match topic-specific regex
payroll reimbursement — Generic word pair from old broad template should not match

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.