Loyalty program balances

Detects loyalty programme balance records: a loyalty programme / points balance / frequent flyer phrase combined with populated member data - rows keyed by a member identifier, labelled points balances, status credits or tiers, or labelled membership numbers. Phrase-only mentions (programme terms, marketing) stay discovery-only.

Type
regex
Engine
boost_regex
Confidence
medium
Confidence justification
Enforce tiers require populated dataset structure (a data row keyed by a customer/record identifier, a labelled value or a labelled identifier) beside the topic phrase; a column header on its own only counts toward 85, so blank extracts stay at 65. Help pages, policies, product copy and news that only name the topic stay at 65. Medium because internal analytics documentation with worked examples can still reach 75.
Detection quality
Topic false positive
Jurisdictions
global
Regulations
Privacy Act 1988 (Cth), Information Privacy Act 2009 (Qld), NDB Scheme (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

(?i)\b(?:loyalty\s+program(?:me)?s?(?:\s+balances?)?|points\s+balances?|frequent\s+flyer(?:\s+(?:account|statement|number|program(?:me)?))?|loyalty\s+(?:card|account|member(?:ship)?)s?|rewards?\s+points|accrued\s+points|status\s+credits|membership\s+tier)\b

Corroborative evidence keywords

redemption, points expiry, tier review, partner earn, statement period, points transfer, fraudulent redemption, lounge access, bonus points

Proximity: 300 characters

Should match

Should not match

Known false positives

References