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.

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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
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article

A Tool for Explainable Pension Fund Recommendations using Large Language Models

Edleno Silva de Moura, Altigran Soares da Silva, Leandro Balby Marinho, Eduardo Silva
Machine Learning in Healthcare
article

A Tool for Explainable Pension Fund Recommendations using Large Language Models

Edleno Silva de Moura, Altigran Soares da Silva, Leandro Balby Marinho, Eduardo Silva
article en

Abstract

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.

Universidade Federal de Campina Grande (BR), Universidade do Vale do Itajaí (BR), Universidade Federal do Amazonas (BR)
Openalex Percentile: Top 85%
Machine Learning in Healthcare
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