Centrelink Customer Reference Number

Detects Centrelink Customer Reference Number (CRN) patterns consisting of 9 digits followed by a letter.

Type: regex
Engine: universal
Confidence: low
Confidence justification: Low confidence: the 9-digit-plus-letter pattern is generic and may match unrelated alphanumeric sequences. Corroborative evidence keywords such as Centrelink, CRN, or Services Australia are essential for reliable detection.
Jurisdictions: au
Regulations: AML/CTF Act (Cth), IPA 2009 (Qld), NDB Scheme (Cth), Privacy Act 1988 (Cth)
Frameworks: ISO 27001
Data categories: pii, government-id
Scope: wide
Risk rating: 8
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Compatible, Netskope: Compatible

Pattern

\b\d{9}[A-Za-z]\b

Corroborative evidence keywords

Centrelink, CRN, Customer Reference Number, customer reference number, DVA, Department of Veterans Affairs, pensioner concession, seniors card, healthcare card, DVA card, concession card, DVA gold card, DVA white card, Commonwealth Seniors Health Card, Services Australia

Proximity: 300 characters

Should match

123456789A — 9 digits followed by a letter
987654321Z — Alternate digit sequence with letter suffix
111222333B — Grouped digit pattern with letter

Should not match

12345678A — Only 8 digits instead of 9 before letter
1234567890A — 10 digits instead of 9 before letter
123456789 — Missing trailing letter

Known false positives

Common words and phrases related to centrelink customer reference number appearing in policy documents, training materials, HR templates, or compliance guidelines without actual personal data. Mitigation: Require corroborative evidence keywords within the proximity window to confirm sensitive data context rather than general discussion.
In Australian English, similar terminology used in formal or administrative contexts (education, professional documentation) that does not constitute sensitive data collection. Mitigation: Layer with additional contextual signals such as structured identifiers, form fields, or database column headers to distinguish sensitive records from general references.
High-frequency pattern matches in large document corpora due to broad regex anchors. Expected match rate is significantly higher than specific identifier patterns. Mitigation: Tune confidence thresholds for bulk scanning. Consider using this pattern primarily as a pre-filter with secondary validation.