Invoice and payment history
Identifies documents containing references to invoice and payment history in Australian contexts. This information type is classified as personally identifiable information under applicable data protection regulations.
- 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
- Topic false positive
- Jurisdictions
- global
- Regulations
- Information Privacy Act 2009 (Qld), NDB Scheme (Cth), Privacy Act 1988 (Cth), GDPR
- Frameworks
- ISO 27001, ISO 27701
- Data categories
- pii
- Scope
- wide
- Risk rating
- 8
- Platform compatibility
- Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Degraded, Netskope: Unsupported
Pattern
(?is)\b(?:invoice\s+and\s+payment\s+history|accounts\s+receivable|transaction\s+record)\b
Corroborative evidence keywords
invoice and payment history, invoice, payment, history, customer, commercial, data
Proximity: 300 characters
Should match
invoice and payment history— Primary topic phrase matchaccounts receivable— Case-insensitive topic phrase matchtransaction record— Alternative topic phrase matchInvoice and payment history Payee: Riverbend Supplies Pty Ltd BSB: 064-000 Account number: 12345678 Payment reference: INV-20431— Populated payee/account reaching the 75/85 structure gate
Should not match
unrelated generic text without domain phrases— No relevant topic phrases presentplaceholder value 12345— Random text should not match topic-specific regexinvoice report— Generic word pair from old broad template should not matchInvoice and payment history: Payee: Account name: Account number:— Empty form: the heading and field labels without values must not corroborate themselves (discovery only)Policy guidance: this procedure explains how records about invoice and payment history are handled, who may access them and how long they are kept. It contains no records about any person or system.— Policy guidance naming the topic without any record (discovery only)
Known false positives
- Common words and phrases related to invoice and payment history 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.