AI Built for Banks and Financial Institutions

Our AI systems are designed with regulatory compliance at their core. We ensure FCA compliance through comprehensive audit trails where every AI decision is logged with timestamp, confidence score, and reasoning. All decisions include explainable AI with clear explanations that satisfy regulatory transparency requirements. We maintain active relationships with regulatory bodies and ensure all systems meet current and upcoming requirements including SR 11-7, MiFID II, and Basel III standards.

Financial institutions typically see measurable ROI within 12 to 18 months. Common outcomes include operational cost reduction through automating manual processes, fraud loss reduction through earlier detection and prevention, improved process efficiency through streamlined workflows, and significant annual savings. Specific use case ROI varies: fraud detection shows immediate impact, compliance automation reduces costs substantially, and risk management improvements prevent significant losses.

Absolutely. We specialise in seamless integration with major banking platforms including Temenos T24/Transact, Oracle FLEXCUBE, FIS Profile/Systematics, and Fiserv DNA/Premier. Our APIs support industry-standard protocols including RESTful APIs, SOAP Web Services, message queues, and database connections. We can adapt to bespoke banking infrastructure with real-time integration that works within existing operational workflows without disrupting daily operations.

Implementation timeline varies by scope and complexity. A pilot implementation for a single use case typically takes 6 to 8 weeks. Full departmental deployment usually requires 3 to 6 months. Enterprise-wide rollout can take 6 to 12 months. We recommend starting with a high-impact pilot to demonstrate value, then scaling successful implementations. This minimises risk and ensures buy-in from stakeholders.

Financial data security is our paramount concern. Our comprehensive approach includes end-to-end encryption with AES-256 for data at rest and TLS 1.3 for data in transit with perfect forward secrecy. We implement data minimisation through PII tokenisation, minimal retention, and automatic purging. Privacy-preserving AI techniques include federated learning and differential privacy. We hold certifications including ISO 27001, ISO 9001, and Cyber Essentials.

Comprehensive training ensures successful adoption and maximises ROI. We provide executive leadership training covering AI strategy, governance, risk management, and business value realisation. Technical team training covers system administration, integration, monitoring, and troubleshooting. End-user training focuses on daily operations, interpreting AI outputs, and escalation procedures. Ongoing support includes 24/7 technical support, regular optimisation reviews, and continuous education through online modules, hands-on workshops, and on-site sessions.

Our model validation framework follows SR 11-7 guidelines and industry best practices. We implement comprehensive testing including backtesting, stress testing, and sensitivity analysis. All models undergo independent validation before deployment, with ongoing monitoring for model drift and performance degradation. Documentation includes model methodology, assumptions, limitations, and validation results suitable for regulatory review.

Our disaster recovery planning ensures continuous AI operations. We implement multi-region deployment with automatic failover, regular backup and recovery testing, and defined RPO/RTO targets. Business continuity plans include manual fallback procedures, communication protocols, and regular DR exercises. All critical systems maintain hot standby configurations with sub-minute failover capabilities.

Our AI infrastructure is designed for elastic scalability. Auto-scaling capabilities handle transaction spikes automatically, while horizontal scaling supports growing baseline volumes. We use distributed processing architectures that scale linearly with demand. Performance monitoring ensures consistent response times regardless of load, with capacity planning reviews conducted quarterly to anticipate growth requirements.