NDIS Participant Number

Detects NDIS Participant Number patterns. A 9-digit number starting with the prefix 43.

Type: regex
Engine: universal
Confidence: low
Confidence justification: Low confidence: a 9-digit number starting with 43 is a relatively short pattern that can match phone numbers and other numeric sequences. Corroborative evidence keywords such as NDIS, NDIA, or participant number are essential for reliable detection.
Detection quality: Verified
Jurisdictions: au
Regulations: HRIPA (Cth), IPA 2009 (Qld), My Health Records Act 2012 (Cth), NDB Scheme (Cth), Privacy Act 1988 (Cth)
Frameworks: ISO 27001, ISO 27701, SOC 2
Data categories: pii, government-id
Scope: wide
Risk rating: 7
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Compatible, Netskope: Compatible

Pattern

\b43\d{7}\b

Corroborative evidence keywords

NDIS, national disability, disability insurance, participant number, Centrelink, CRN, 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

430000001 — NDIS number starting with 43
431234567 — Standard NDIS participant number
439999999 — Upper range NDIS number

Should not match

440000001 — Wrong prefix (44 instead of 43)
42000001 — Wrong prefix (42 instead of 43) and too few digits
4312345678 — Too many digits (10 instead of 9)

Known false positives

Common words and phrases related to ndis participant 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.