Implementing Guardrails to Ensure the Responsible and Ethical Use of AI

Video

Jul 16, 2024

Christopher Smigielski, Risk Model & Director, Arvest Bank Group

Tags: Regulation and Compliance Model risk AI and Technology (including Fintech)

The views and opinions expressed in this content are those of the thought leader as an individual and are not attributed to CeFPro or any other organization

It is crucial to implement rigorous frameworks that prioritize ethical considerations and ensure compliance with regulatory standards in AI applications.
Robust testing and validation processes are essential for detecting and mitigating biases in AI models, thereby ensuring fairness and reliability.
Incorporating continuous monitoring and annual reviews helps maintain the effectiveness and ethical integrity of AI models throughout their lifecycle.
Balancing the adoption of innovative AI technologies with strict adherence to ethical and regulatory requirements is key in the banking sector.

Christopher Smigielski Bio

Chris Smigielski Director of Model Risk Management – Arvest Bank With over 30 years of experience in the financial services industry, Chris is a recognized leader in model risk management, model governance, and team development. He currently serves as the Director of Model Risk Management at Arvest Bank, where he also plays a pivotal role as a member of the AI Center of Excellence, overseeing the ethical and strategic deployment of artificial intelligence across the organization. Prior to Arvest, Chris led Model Risk Management at TIAA Bank and held senior leadership roles at global organizations including Diebold and Fiserv. His career is marked by a deep expertise in Asset Liability Management (ALM) and a proven track record of consulting with financial institutions to implement growth- oriented financial strategies. Chris is a thought leader, frequent presenter and panelist at conferences and webinars, speaking on evolving model risk management and enterprise risk management (ERM) topics.