Credit scores
Detects references to credit scores 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
- Not detected
- Jurisdictions
- global
- Regulations
- GDPR
- Frameworks
- ISO 27001, ISO 27701
- Data categories
- financial
- Scope
- wide
- Risk rating
- 7
- Platform compatibility
- Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Degraded, Netskope: Unsupported
Pattern
(?is)\b(?:credit\s+score|FICO\s+score|credit\s+rating|credit\s+assessment|risk\s+score|credit\s+bureau|score\s+range|credit\s+evaluation|credit\s+band|scoring\s+model)\bCorroborative evidence keywords
credit scores, credit, scores, lending, insurance, financial, fiscal, monetary, accounting, treasury, audit, revenue, expenditure, budget, ledger, accounts payable, accounts receivable, balance sheet, profit and loss, cash flow (+24 more)
Proximity: 300 characters
Should match
credit score— Primary topic phrase matchfico score— Case-insensitive topic phrase matchcredit rating— Alternative topic phrase matchcredit assessment— Additional topic phrase match
Should not match
unrelated generic text without domain phrases— No relevant topic phrases presentplaceholder value 12345— Random text should not match topic-specific regexcredit premium— 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.