Customer engagement and support for banking, insurance, and financial services. Compliant AI that handles enquiries and improves service efficiency.
Financial services face unique pressure: customer expectations for instant, digital service combined with strict regulatory requirements and security obligations. AI can improve customer experience and operational efficiency while meeting these constraints.
The sector has specific requirements:
Regulatory compliance: FCA rules, Consumer Duty, and sector-specific regulations constrain what AI can do and how.
Security requirements: Financial data demands the highest protection standards.
Customer trust: Financial relationships depend on confidence and reliability.
Complex products: Explaining financial products clearly and appropriately.
Fraud and risk: Protecting customers and institutions from financial crime.
AI must work within this regulated environment.
AI serves financial services customers through:
Account enquiries: Balance checks, transaction history, statement requests, account information.
Product information: Explaining products, features, rates, and terms without providing advice.
Service requests: Processing address changes, card requests, password resets, and routine tasks.
Claims handling: Initial claims intake, status updates, and documentation guidance.
Appointment booking: Scheduling conversations with advisers and specialists.
AI improves internal operations:
Document processing: Extracting information from applications, claims, and correspondence.
Compliance support: Checking transactions and activities against regulatory requirements.
Internal knowledge: Helping staff find policy information and procedural guidance.
Quality assurance: Monitoring interactions for compliance and quality.
Risk assessment: Supporting decision-making with data analysis.
Financial services AI requires careful design:
Appropriate boundaries: Clear about what AI can and cannot do, particularly regarding advice.
Audit trails: Recording AI decisions and interactions for regulatory review.
Consumer Duty alignment: Ensuring AI serves customer interests appropriately.
Vulnerable customers: Identifying and responding to customers who need additional support.
Complaint handling: Proper routes for customers to raise concerns.
We understand FCA expectations and design AI that supports compliance.
In practice, compliance-friendly design means separating “information” from “decision”. The assistant can explain processes and surface policy, but it should route to qualified humans for anything that requires judgement, advice, or exceptions. That boundary is usually where projects succeed or fail.
Strong monitoring and review processes ensure this boundary holds in production.
Financial services demand strong security:
Data protection: Encryption, access controls, and secure processing throughout.
Authentication: Appropriate verification before accessing account information.
Fraud detection: Integration with fraud prevention systems.
Infrastructure security: Deployment meeting financial services standards.
Penetration testing: Verification that systems resist attack.
We have worked with financial services organisations including BNP Paribas and Model Office. We understand the regulatory environment and compliance requirements.
Our approach ensures AI meets sector expectations while delivering genuine customer and operational value.
AI connects to:
Core banking platforms. Account data, transactions, and customer records.
Insurance administration systems. Claims, policy servicing, and customer enquiries.
CRM and customer databases. Context for service and routing.
Document management systems. Statements, forms, applications, and correspondence.
Compliance and risk platforms. Monitoring, review workflows, and audit trails.
We build integrations that respect data security and regulatory boundaries.
Financial services use cases succeed when boundaries are explicit.
Avoid advice. Systems must be clear about what is informational versus what requires a qualified human adviser.
Design for vulnerability. Identify vulnerable customers and route to appropriate human support paths.
Keep auditability end-to-end. Log what was asked, what data was accessed, what was answered, and when escalation occurred.
Yes, with clear boundaries, governance, and human oversight for consequential decisions.
Scope to factual information, use approved content, add deterministic checks, and escalate to humans when judgement is required.
We integrate identity and verification flows before exposing account-specific information.
Policies, monitoring, audit logs, and controlled releases for changes to content, prompts, and models.
Faster resolution for routine enquiries, better internal efficiency, and stronger consistency and oversight.
