The session titled "Navigating The Regulatory Landscape & AI’s Impact on Compliance" by Sriram Natarajan, President of Quinte Financial Technologies, at the CULytics Summit held from March 25th to 28th, 2024, delves into the implications of artificial intelligence (AI) on regulatory compliance and financial institutions' (FIs) approach to AI technologies. Here's a summary of the session:

• Technological Evolution: Natarajan outlines the trajectory of technological innovations from past to present, emphasizing how advancements like quantum computing, large language models, generative AI, blockchain, metaverse, mobile wallets, app-based payments, open banking, and cloud computing evolve from hype to integral components of daily operations.

• Global AI Regulation: Highlights the global initiative towards developing AI-related legal frameworks, with over 37 countries working on regulations, stressing the need for FIs to adapt compliance, implement ethical AI practices, enhance risk management, and invest in new technologies and training.

• European AI Act: Discusses the European Parliament's approval of the Artificial Intelligence Act on March 13, 2024, focusing on protecting fundamental rights, promoting safety, compliance, and AI development, and banning certain AI applications to safeguard citizen rights. It emphasizes obligations for high-risk AI systems and measures to support innovation and transparency.

• US Regulatory Trends: Lists looming regulatory trends impacting FIs, including CFPB’s adverse action notifications for credit decisions, OCC’s Fair Lending Act requirements, the US AI Executive Order for "Red Teaming" AI governance, crackdowns on junk fees, AML/CFT measures, and CFPB’s Regulation Z amendment.

• Challenges to AI Adoption: Identifies barriers such as the lack of transparency, fairness, and accountability in AI models, increased regulatory scrutiny, operational inefficiencies, and ethical considerations.

• ChatGPT/LLMs and DEI: Examines challenges posed by ChatGPT and other large language models (LLMs) in terms of potential misuse, intellectual property rights, perpetuating societal biases, and the importance of fairness testing, diverse training data, and DEI principles.

• Regulatory Scrutiny and AI Governance: Contrasts traditional rule-based models with AI/ML models, highlighting the need for evolving governance frameworks, bias testing, continuous monitoring, and MLOps skills due to AI models' complexity and adaptive nature.

• Responsible AI Principles and Governance: Covers aspects essential for AI model governance, including model documentation, algorithm fairness, privacy and security controls, auditing, monitoring, explainability, and interpretability.

Natarajan's presentation underscores the importance of adapting to evolving AI regulations, implementing responsible AI practices, and preparing for the future with a specialist's approach to ensure compliance, fairness, and ethical AI use within the financial industry.