Integrating Generative AI Models in Risk Management

Overview

Generative AI (Gen AI) models are machine learning algorithms. They are trained on large and complex data sets to generate synthetic data outputs with similar statistical properties as samples in the training data. Although Large Language Models (LLMs) have become the most well-known examples of generative models, the range of GenAI algorithms and their applications in risk management are much broader in scope.   

At this New York chapter meeting, Rama Cont will provide insight and context on the use of generative models and “synthetic data” for risk management applications, including:  

• Simulating risk scenarios for complex portfolios
• Forecasting Value-at-Risk and portfolio risk
• Developing hedging strategies 

The presentation will also highlight the methodological challenges in the design and validation of such models, using examples based on equity portfolios, options portfolios and fixed income portfolios.

Following the panel discussion, please join us for a networking reception. 

Registration is required as seats are limited. Priority will be given to GARP Individual Members.