Real-time transaction monitoring with ML models that detect anomalous patterns, flag suspicious activity, and reduce false positives.
Alternative credit scoring models using non-traditional data sources. Explainable AI that satisfies regulatory requirements for lending decisions.
Automated portfolio management with risk profiling, rebalancing algorithms, tax-loss harvesting, and regulatory-compliant client reporting.
AI-powered extraction from financial documents: bank statements, tax returns, loan applications, and KYC/AML verification documents.
Automated regulatory reporting, transaction monitoring for AML/BSA, and real-time compliance checks against sanctions lists and PEP databases.
Financial applications demand the highest security standards. We build that infrastructure from day one.
Development practices aligned with SOC 2 Type II requirements. Security controls, access management, and change management built into our workflow.
Payment card data handling that meets PCI DSS requirements. Tokenization, secure vaults, and minimal cardholder data exposure.
AES-256 at rest, TLS 1.3 in transit, field-level encryption for sensitive financial data, and HSM-backed key management.
Complete audit trails via event sourcing architecture. Every transaction, every state change, every decision — recorded immutably for regulatory review.
Our CTO architected systems for Banco Itaú (largest bank in Latin America), Ambev (AB InBev), and Walmart while at Avenue Code — a ~$179M revenue consulting firm. Deep understanding of financial transaction architecture, high-availability systems, and enterprise security patterns.
Company revenue (Avenue Code)
Years combined experience
Fortune 500 financial clients
Fintech MVPs start at $30,000 for core financial products and scale to $60,000+ for complex platforms with AI models, compliance automation, and enterprise integrations.