Generative AI and Investor Processing of Financial Information

Abstract

This paper provides descriptive evidence on retail investors' use and perceptions of generative AI (GenAI) to process financial information and inform investment decisions. Our survey of 2,175 retail investors, complemented by an analysis of 40,000 investor questions posed to a GenAI chatbot, reveals three key findings. First, we observe widespread adoption, with nearly half of surveyed investors already using GenAI, primarily for gathering and interpreting financial or market data. Investors perceive GenAI as enhancing their ability to process complex information quickly and easily. Second, more sophisticated retail investors understand and leverage GenAI’s strengths to a greater extent. These investors lead GenAI adoption and utilization, using it for more complex tasks and drawing from a broader range of sources. Third, while nearly two-thirds of investors plan to continue or start using GenAI and believe it will become a standard tool for investors, many non-users remain skeptical. This hesitancy toward future GenAI adoption appears related to concerns about data privacy and response quality, as well as younger and less sophisticated investors having difficulty identifying or leveraging the processing benefits of GenAI. This disparity suggests that while overall adoption is likely to increase, it may also widen the gap between more and less sophisticated investors, challenging expectations of democratized access to complex financial information for all retail investors. This nuanced perspective on GenAI's future in retail investing highlights the need for further research into its long-term impact on investor behavior and market dynamics.

Keywords: Generative AI, information processing, investment decisions, financial accounting, retail investors

JEL Classification: G41, M41, G11, D83, G53