Navigating Risk in the Age of Intelligent Applications

Presentation

Rodanthy Tzani discusses the critical need for robust AI governance frameworks, especially within the insurance sector. She highlights risk management, regulatory compliance, and practical steps to operationalize AI governance, including guiding principles, risk assessment, and bias testing.

Apr 30, 2025

Rodanthy Tzani, former Head of Model Risk Management, New York Life Insurance

Tags: AI and Technology (including Fintech) Model risk

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

Rodanthy Tzani's presentation emphasizes the increasing importance of risk management frameworks for AI applications, including both traditional AI models and GenAI use cases. She underscores that the risks associated with AI stem from the complexity of models, predictability, unintended biases, and potential financial and legal repercussions.

Tzani highlights the evolving regulatory landscape, particularly within the insurance industry, with examples from NAIC, Colorado State, and DFS. These regulations emphasize governing principles, bias testing, and explicit oversight. To address these challenges, she advocates for enhancing risk management frameworks and implementing effective controls, which include publishing guiding AI principles and establishing governance building blocks.

To operationalize AI governance, Tzani suggests developing a governance framework with a clear committee structure, well-defined roles and responsibilities, and an AI inventory with risk assessments. She emphasizes the importance of prioritizing AI applications based on risk levels and introduces the concept of a bias testing framework, particularly relevant for insurance companies.

Rodanthy Tzani Bio

Dr. Rodanthy Tzani is a Freelance Risk Executive who partners with organizations across industries to help them identify, assess, and mitigate financial, operational, and regulatory risks. Drawing from her wide experience, she advises industry leaders on the best approaches in building sustainable risk management practices, including Model Risk Management, Stress Testing and AI Application frameworks. Until end of 2024, Dr. Tzani was a Vice President and Head of Model Risk Management in New York Life Insurance Company, where she joined in 2018 and successfully built and operationalized the Model Risk Management function of the company. Recently, she established the enterprise-wide Governance and Risk Assessment framework for AI applications developed by the company. From 2009 to 2017 she was a Supervising Examiner and Risk Analytics Manager in the Supervision Group of the Federal Reserve Bank of New York. During her tenure at the Fed, she led numerous examinations evaluating all types of models and approaches used by large domestic and foreign bank SIFIs (Systemically Important Financial Institutions). Dr. Tzani oversaw model risk across the Systemically Important Insurance Companies while they were under the Fed’s supervision and established supervising standards for insurance practices. Supporting an internal Fed effort to advance analytical tools for efficient supervision, she also led her team in testing Large Language Models. Working with leaders within the Federal Reserve System, Dr. Tzani was instrumental in extending supervisory standards to foreign banking institutions and insurance SIFIs. Before joining the Fed, Dr. Tzani was the Head of the Structured Finance Risk Management at ACA Capital, where she oversaw the restructuring and winding down of the company during the 2008 crisis. Prior to that she was a Vice President with the Derivatives Group of Moody’s Investors Service. Dr. Tzani holds a Ph.D. in Theoretical Physics from the City College of CUNY and has spent time in academia conducting research in various universities in Europe and the USA before moving to finance in 2001. She has published numerous papers in refereed journals both in physics and finance.