These are the specific frameworks and obligations relevant to your sector, not a generic GDPR checklist. Each one has a direct implication for how you govern AI use and data handling.
Cardholder data in AI prompts creates PCI scope. Scope reduction requires technical controls at every AI intercept point.
Firms must demonstrate AI governance, oversight, and explainability. Audit log and CISO dashboard support FCA review readiness.
Data minimisation and appropriate technical measures for financial personal data processed through AI tools.
Record-keeping obligations extend to AI-assisted communications, analysis, and client interactions.
These are the specific workflows most organisations in your sector deploy first, in plain terms.
Credit card numbers, account identifiers, and IBANs are hard-blocked, replaced with a [CREDIT_CARD] placeholder. The LLM can still reason about the transaction context without ever receiving the real number.
Generate statistically faithful training datasets for credit scoring, fraud detection, and risk models. Differential privacy mode for GDPR-compliant ML outputs. No real cardholder data in training pipelines.
Anonymise cardholder data in staging, analytics, and dev environments. Remove PCI scope from non-production systems without rebuilding pipelines. Every anonymisation action written to the tamper-evident audit record.
Group-based policies: the trading desk gets different rules to the back-office team. Role-aware intercept. Fits inside existing access control frameworks without changes to IAM.
Both products share the same detection engine. Most organisations in your sector start with one before adding the other.
Hard-block and transform policies for PCI-scoped entities. Covers every AI endpoint: browser, MCP, and API. CISO dashboard for real-time visibility into AI traffic.
Synthetic data for ML pipelines. PCI scope reduction through in-place anonymisation. PCI-DSS 4.0 and GDPR compliant.
Card numbers, IBANs, and SSNs hard-blocked by default. [CREDIT_CARD] placeholder means the LLM can still reason about transaction context without receiving the real number.
Real-time visibility: prompts intercepted, entities transformed by type, hard blocks with reason and user context. Export for FCA governance review.
Group-based policies aligned to existing IAM. Trading desk, compliance, and back-office teams get different intercept rules without a separate identity stack.
Immutable audit log for every AI interaction. Entity inventory per session. Hash-chained: tampering breaks the chain. Attributable to user and tool.
Transform, block, warn, or audit-only per entity type and user group. Configured once, enforced consistently across every AI endpoint.
Everything runs in your environment. No data routed to vendor infrastructure. Data residency requirements satisfied by default.
Scan every database, file store, and cloud bucket for cardholder data, account identifiers, and IBANs. Field-level findings with confidence scores and row counts.
Anonymise cardholder data in staging, analytics, and dev environments. Remove PCI scope from non-production systems without rebuilding pipelines.
GDPR and HIPAA compliant synthetic training datasets for credit scoring, fraud detection, and risk models. No real cardholder data in training pipelines.
Automated production-to-analytics pipeline. Quant and data teams always have a current, anonymised dataset without accessing production.
Referential integrity maintained across related tables. Realistic relational structure preserved in anonymised exports.
Records of processing activities automatically maintained from scan findings. Financial personal data documented, located, and governed.
We connect to something real in your environment and you see actual findings. No slide decks. No fabricated data. Median time to first scan: under 4 hours from credentials.
For CISOs and Chief Risk Officers. PCI-DSS scope reduction and FCA governance questions welcome.