The Worth of a “Woâ€: Gender Bias in Financial Advice from LLMs

Richard Foltyn and Jonna Olsson

No 21323, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: Do large language models (LLMs) provide gender-neutral financial advice? We answer this question by prompting 33 widely used LLMs from five vendors, varying only a single word in otherwise identical prompts: “man†versus “woman.†We find that women are advised to allocate 1.8 percentage points less to equity funds than men; this gap persists across vendors, model generations, and model complexity. Providing richer investor information attenuates but does not entirely eliminate the gender gap. Since even modest allocation differences imply persistent return differentials, algorithmic financial advice can shape wealth accumulation across demographic groups.

JEL-codes: C1 G11 J16 (search for similar items in EconPapers)
Date: 2026-03
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