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Green-curious retail investors and unmediated interactions with GenAI

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  • Boni, Leslie

Abstract

This paper examines how generative AI (GenAI) tools such as ChatGPT respond when green-curious retail investors seek investment advice through unmediated, prompt-based interactions. Motivated by climate concern, these investors may lack financial or climate literacy and may prefer GenAI tools to human advisors, robo-advisors, or platform-integrated systems. Drawing from prior research on investor interactions with GenAI and on information critical for making green investment decisions, we conducted a prompt-based experiment using ChatGPT-4o and ChatGPT 5. Results show that ChatGPT encouraged green investing across all queries, but the inclusion or omission of decision-critical information varied widely. Key considerations, such as lower expected returns relative to other investments, greenwashing and confusing label warnings, and distinctions between ESG and climate-aligned products, often were surfaced only when explicitly prompted. These findings highlight the importance of GenAI literacy along with climate and financial literacy in shaping investor outcomes. We propose a research agenda to examine how GenAI tools inform or mislead retail investors in unstructured settings and to guide investor education, system design, and policy development for responsible GenAI use in retail finance.

Suggested Citation

  • Boni, Leslie, 2025. "Green-curious retail investors and unmediated interactions with GenAI," Finance Research Letters, Elsevier, vol. 86(PE).
    • Handle: RePEc:eee:finlet:v:86:y:2025:i:pe:s1544612325019798
    DOI: 10.1016/j.frl.2025.108725
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