Generative Artificial Intelligence in Finance: Risk Considerations study notes cover the following learning objectives:
Compare generative AI and traditional AI/ML algorithms.
Explain the challenges generative AI systems pose for the financial sector, including those related to data privacy, embedded bias, model robustness, and explainability.
Examine the use of synthetic data to enhance AI models and the potential risks associated with synthetic data generation and application.
Evaluate the cybersecurity threats and potential impact on financial stability posed by the use of generative AI in the financial sector.