The study examines how user context—such as memory, profiles, and role prompts—affects Large Language Models’ (LLMs) financial analysis. Using 3,575 SEC filings and twelve LLMs, the authors distinguish between evidence selection and interpretation, finding that most context spillover arises from differing interpretations under various roles rather than from retrieving different evidence. They evaluate two mitigation strategies—expressing investor mindset as a user profile instead of an assistant role, and separating evidence-based from personalized outputs—both of which reduce but do not eliminate spillover, with effectiveness varying across models.
By Ahmed Asaad, Amr Mohamed, Yang Zhang, Omneya Abdelsalam
arXiv:2608. 04095v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly used as personalized assistants in high-stakes domains such as financial advising, yet it remains unclear whether they can maintain and update an individualized user model over long horizons.
By Ben Wang, Kang Zhou, Lifan Guo, Feng Chen, Chi Zhang
arXiv:2608.24842v1 Announce Type: cross
Abstract: Large language models (LLMs) are increasingly deployed as AI analysts to process financial disclosures and support AI-assisted investment decisions....
By Miao Liu, Zhizhe Liu
Demand for personalized financial advising is growing, but consistent advisor expertise is difficult to obtain, scale, and encode in LLM systems. Simple persona prompts rarely specify how a financial advisor should reason and often drift toward generic recommendations.
arXiv:2606.29793v3 Announce Type: replace
Abstract: Demand for personalized financial advice is growing, yet current LLM-based advisors often fail to provide consistent and specialized guidance.\ Sim...
By Suhwan Park, Hoyoung Lee, Zhangyang Wang, Alejandro Lopez-Lira, Young Cha, Chanyeol Choi, Jaewon Choi, Yongjae Lee
arXiv:2607. 09121v1 Announce Type: cross Abstract: In this study, we examine the opportunities brought by Large Language Models (LLMs) to various aspects of fundamental analysis of companies based on their reports as well as data and documents describing macroeconomic situation like GDP and inflation changes as well as documents filled to the U.
By Bartosz Zi\'o{\l}ko, Kacper Dobrzeniewski