Mark Ritcey
Vice President, AI & Automation Delivery, Latent Bridge
Ritcey is an AI Automation & Innovation Leader with nearly 15 years of experience in private, corporate, and investment banking and 8+ years leading enterprise AI and automation programs. He currently serves as Vice President of AI & Automation Delivery at LatentBridge plc, an AI and automation consulting firm focused in the financial services industry. Mark has implemented assessment frameworks, automation governance models, and deployed multiple Machine Learning, GenAI, and intelligent automation solutions across front, mid, and back-office functions.
All Sessions by Mark Ritcey
Use Case 11: Enterprise Wide Automation
AI is often thought about department by department at a bank. In fact, most banks pick a department and platform to test the waters in artificial intelligence. While this approach has merit, it can often be at the expense of an enterprise view where the right AI infrastructure and solutions are built from the top down, rather from the department up. Join this session with an expert in Enterprise AI Solutions, who will share his experience and best practices to think strategically about AI across your organization.
Enterprise Wide AI Automation
Many banks are piloting artificial intelligence projects, learning about how this advance can benefit customers and improve bank performance. But what about enterprise wide AI projects? How can your bank do AI at scale to harness the full potential of artificial intelligence? Attend this session to learn more about enterprise wide AI opportunities, and best practices in deploying AI solutions at scale across your institution.
Enterprise Wide AI Automation
Many banks are piloting artificial intelligence projects, learning about how this advance can benefit customers and improve bank performance. But what about enterprise wide AI projects? How can your bank do AI at scale to harness the full potential of artificial intelligence? Attend this session to learn more about enterprise wide AI opportunities, and best practices in deploying AI solutions at scale across your institution.
Operationalizing AI Risk Governance in Financial Services: From Policy to Practice
As financial institutions accelerate AI adoption, risk governance must evolve from high-level principles to operationalized, defensible frameworks. This session explores how to design and implement an enterprise-grade AI risk governance model tailored for regulated financial services environments. Designed for risk leaders, AI and technology executives, and control partners, this discussion moves beyond theory to provide a scalable governance approach that enables innovation while maintaining regulatory alignment, model risk discipline, and enterprise risk transparency.
