Biased Echoes: Generative AI Models Reinforce Investment Biases and Increase Portfolio Risks of Private Investors
Type
conference paper
Date Issued
2024
Author(s)
Abstract
Generative AI models are increasingly used by private investors seeking financial advice. The current paper examines the potential of these models to perpetuate investment biases and affect the economic security of individuals at scale. It provides a systematic assessment of how generative AI models used for investment advice shape the portfolio risks of private investors. We offer a comprehensive model of generative AI investment advice risk, examining five key dimensions of portfolio risks (geographical cluster risk, sector cluster risk, trend chasing risk, active investment allocation risk, and total expense risk). We demonstrate across four studies that generative AI models used for investment advice induce increased portfolio risks across all five risk dimensions, and that a range of debiasing interventions only partially mitigate these risks. Our findings show that generative AI models exhibit similar “cognitive” biases as human investors, reinforcing existing investment biases inherent in their training data.
Keywords
generative AI
large language models
private investors
retail investors
financial portfolio risks
financial decision making
Event Title
2nd Annual Business & Generative AI Workshop
Event Location
San Francisco
Subject(s)
Division(s)
File(s)![Thumbnail Image]()
Name
biasedEchoes_preprint.pdf
Size
838.4 KB
Format
Adobe PDF
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