- Volume and velocity of interactions
- System capacity and resilience
- Monitoring and control frameworks
- Managing unpredictable workloads
- Moving beyond rules-based surveillance
- Explainability for enforcement and audit
- False positives vs missed risk
- Integration with trader oversight
- Real time decisioning across channels
- Data boundaries and consent
- Personalisation vs intrusion
- Commercial impact and customer retention
- Evidence frameworks for AI decisions
- Traceability from input to output
- Audit readiness for GenAI systems
- Lessons from early regulatory reviews
- Where trust is built or lost
- Transparency vs friction trade offs
- Behavioural design and reassurance
- Long term impact on customer relationships
- AI incident taxonomy
- Kill switches and rollback
- Third party dependencies
- Reporting to regulators
- Turning analytics into frontline actions
- Integration with CRM and workflow tools
- Behavioural nudges and next best action
- Adoption challenges in sales teams
- What an AI native banking product looks like
- Moving from feature layers to embedded intelligence
- Product lifecycle in an AI environment
- Where traditional product design breaks
