GDPR-Compliant AI Architecture for European Fintech Startups

Adding AI to a fintech product triggers GDPR questions fast: Are you processing personal data? Is inference automated decision-making? Do you have a lawful basis? We architect AI features for European fintech clients with compliance as a default constraint, not a post-launch audit fix.

Separate PII from prompts

Never send raw customer records to third-party LLM APIs if you can avoid it. Use retrieval with redacted context, tokenization for identifiers, and on-prem or EU-region inference for sensitive workflows. Document what leaves your VPC in a data flow diagram — auditors will ask.

Retention and deletion

Log prompts and outputs with TTL aligned to your privacy policy. Build deletion hooks that cascade when a user exercises erasure rights. Vector databases need the same erasure strategy as relational stores — embeddings of personal data are still personal data.

Human-in-the-loop for high-impact decisions

Credit, fraud, and KYC automation may trigger Article 22 considerations. Design review queues, explainability summaries, and override paths for human operators. AI suggests; humans approve for consequential outcomes unless legal counsel confirms otherwise.

Documentation pack for regulators

• Lawful basis per processing purpose
• DPIA for high-risk AI use cases
• Subprocessor list including model providers
• Model change log and rollback procedure