A Tool for Explainable Pension Fund Recommendations using Large Language Models
In this demo, we present a prototype tool designed to help financial advisors recommend private pension funds to investors based on their preferences, offering personalized investment suggestions. The tool leverages Large Language Models (LLMs), which enhance explainability by providing clear and understandable rationales for recommendations and effectively handles both sequential and cold-start scenarios. We outline the design, implementation, and results of a user-based evaluation using real-world data. The evaluation shows a high recommendation acceptance rate among financial advisors, highlighting the tool’s potential to improve decision-making in financial advisory services.
Authors
- Edleno Silva de Moura (ORCID: https://orcid.org/0000-0002-7860-9575)
- Altigran Soares da Silva (ORCID: https://orcid.org/0000-0002-8992-495X)
- Leandro Balby Marinho (ORCID: https://orcid.org/0000-0001-7599-372X)
- Eduardo Silva (ORCID: https://orcid.org/0000-0002-5213-7805)
Institutions
- Universidade Federal de Campina Grande (BR)
- Universidade do Vale do Itajaí (BR)
- Universidade Federal do Amazonas (BR)
Publication Details
- Published
- 2024-10-08
- DOI
- https://doi.org/10.1145/3640457.3691699
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00