A Chatbot to Help Promoting Financial Literacy

Currently, governments and many other institutions have been making significant efforts to promote financial literacy. However, a considerable portion of the population still lacks basic financial knowledge, highlighting the need for updated strategies to enhance financial education. In today’s digital world - where people often search for quick and convenient solutions - the development of a reliable and intelligent chatbot to answer questions related to financial concepts and decision-making can be very beneficial. This paper proposes the implementation of an automated web scraper to extract content from a trustworthy financial education website with plenty of useful concepts about finances, using this collected data to develop a chatbot which provides accurate and helpful responses to users. The solution is built using technologies such as Streamlit, Langchain, and OpenAI.

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Publication Details

Journal
DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
Published
2025-01-01
DOI
https://doi.org/10.4230/oasics.slate.2025.7
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00

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article

A Chatbot to Help Promoting Financial Literacy

DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
AI in Service Interactions
article

A Chatbot to Help Promoting Financial Literacy

article en

Abstract

Currently, governments and many other institutions have been making significant efforts to promote financial literacy. However, a considerable portion of the population still lacks basic financial knowledge, highlighting the need for updated strategies to enhance financial education. In today’s digital world - where people often search for quick and convenient solutions - the development of a reliable and intelligent chatbot to answer questions related to financial concepts and decision-making can be very beneficial. This paper proposes the implementation of an automated web scraper to extract content from a trustworthy financial education website with plenty of useful concepts about finances, using this collected data to develop a chatbot which provides accurate and helpful responses to users. The solution is built using technologies such as Streamlit, Langchain, and OpenAI.

DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
Universidade Politécnica de Bragança (PT)
Ministério da Ciência, Tecnologia e Ensino Superior, Fundação para a Ciência e a Tecnologia
Quality Education
Openalex Percentile: Top 74%
AI in Service Interactions
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