Generative AI is coming to financial services, as it is to many industries. Financial services firms are exploring the use of generative AI to distill patterns, generate analytics outputs, and develop new products and services from many types of data.
Join Wells Fargo distinguished engineer and SVP Prasanth Nandanuru for this case study as he discusses strategy and criteria for using generative AI to build synthetic data for their operational requirements. He will explore the impact of generative AI on decentralized data infrastructure, focusing on its use in generating multivariate, time-series synthetic data of high dimensionality for machine learning and artificial intelligence applications.
He will discuss the pros and cons of such generative techniques as variational encoding, generative adversarial networks, and diffusion models. He will also address considerations and best practices for safeguarding sensitive information and complying with regulatory guidelines when applying generative AI models to financial data.