AI risk management must go beyond rigid definitions to capture all relevant risks

Arvest Bank adapts SR 11 7 to oversee AI and non traditional tools like fraud monitoring and AML systems

AI Center of Excellence manages inventory assessment and monitoring for AI tools outside model risk scope

Performance monitoring for GenAI is complex and needs automated scalable solutions

Governance prioritizes use case specific risk levels and human oversight needs

Vendor transparency on fairness and bias is essential and lack of proof is flagged

Regulation is fragmented but proactive principle based governance is pursued

AI literacy with mandatory employee training ensures safe and effective adoption

Governance must balance innovation with oversight and accountability