Phase 01
Architecture-level GDPR
GDPR-compliant data flows are designed before implementation: lawful basis, purpose limitation, and DPA-ready documentation for every processing activity.
GDPR-Compliant Development
AIDevelopmentforFintech&FinancialServices
We build GDPR-compliant AI software for fintech and financial services companies — fraud detection, document intelligence, KYC/AML automation, and investment analytics. Compliance is architecture, not an afterthought.
GDPR-first architecture
Data protection built in from the start
Every fintech project starts with a data flow mapping exercise. GDPR obligations, consent mechanisms, and audit requirements are defined before development begins.
Phase 02
Consent & lawful basis
Consent management and lawful basis are captured in-product and in specs so regulators and partners see a clear, auditable trail.
Phase 03
Right to erasure wired in
Right-to-erasure hooks live in your data model and jobs from day one — not as a panic migration before an audit.
Phase 04
Data residency controls
Region-aware storage and processing for EU data subjects, aligned with your cloud and subprocessors.
Phase 05
PII audit logging
Structured audit logging for PII access and AI inferences supports investigations, DPAs, and internal security reviews.
Phase 06
SOC 2–aligned delivery
Access logging, change management, encryption, and incident response patterns that map to SOC 2 control narratives.
See how our six-phase AI harness enforces QA, metrics, and compliance checkpoints on every engagement.
Read the full process →Fintech AI use cases
What we build for financial services companies
Fraud Detection & Prevention
AI systems that analyze transaction patterns, flag anomalies, and surface explanations for compliance teams — with configurable risk thresholds and human-in-the-loop review.
Document Intelligence (KYC/AML)
LLM-powered pipelines that extract structured data from identity documents, financial statements, and beneficial ownership records — accelerating onboarding without compromising accuracy.
Automated Underwriting
AI-assisted credit and risk assessment workflows that process applications faster, surface explainable decisions, and integrate with existing LOS and CRM systems.
Investment Analytics
AI models that analyze market data, portfolio performance, and risk factors — delivering insights that advisors and fund managers can act on with confidence.
GDPR Data Governance
Data residency controls, consent management, right-to-erasure hooks, and audit trails built into the platform from day one — not retrofitted before a DPA audit.
Compliance Architecture Review
Architecture audit and compliance hardening for existing fintech platforms — identifying GDPR exposure risks, PII handling gaps, and SOC 2 control shortfalls.
Technology stack
Tools we use for fintech AI
OpenAI APIClaude APILangChainLangGraphRAG PipelinesPythonNode.jsAWSPostgreSQLAudit LoggingPII EncryptionData Residency Controls
Common questions
Fintech AI development — answered
We implement GDPR compliance from the architecture level: data minimization, consent management, right-to-erasure hooks, data residency controls, and audit logging for all PII processing. We document data flows for DPA obligations and ensure lawful basis for all AI processing activities.