Artificial Intelligence Authoring Financial Recommendations: Comparative Australian Evidence

Article

Neilson, Ben. 2023. "Artificial Intelligence Authoring Financial Recommendations: Comparative Australian Evidence." Journal of Financial Regulation. 9 (2), pp. 249-257. https://doi.org/10.1093/jfr/fjad004
Article Title

Artificial Intelligence Authoring Financial Recommendations: Comparative Australian Evidence

ERA Journal ID210875
Article CategoryArticle
AuthorsNeilson, Ben
Journal TitleJournal of Financial Regulation
Journal Citation9 (2), pp. 249-257
Number of Pages9
Year2023
PublisherOxford University Press
Place of PublicationUnited Kingdom
ISSN2053-4833
2053-4841
Digital Object Identifier (DOI)https://doi.org/10.1093/jfr/fjad004
Web Address (URL)https://academic.oup.com/jfr/article/9/2/249/7163206
AbstractThis article explores the use of artificial intelligence software to create financial recommendations. It seeks to define the impacts and outline the benefits of using ChatGPT software in the highly regulated Australian financial sector. ChatGPT was asked to create a financial recommendation, which was evaluated against the relevant regulations and the recommendations of existing professionals and market contributors. The data generated was analysed using Qualtrics analysis techniques. The findings suggest that ChatGPT significantly reduces the time required to carry out creation, input, and editing services for simple financial advice recommendations. However, ChatGPT fails to operate effectively with complex financial advice and requires professional guidance to ensure regulatory adherence. In future, it may be possible to develop ChatGPT as a complementary tool to decrease the time and cost required to create financial recommendations.
KeywordsChatGPT; artificial intelligence; regulation; financial recommendation
ANZSRC Field of Research 20203899. Other economics
Byline AffiliationsUniversity of Southern Queensland
Permalink -

https://research.usq.edu.au/item/z296y/artificial-intelligence-authoring-financial-recommendations-comparative-australian-evidence

Log in to edit

Download files

Published Version
fjad004.pdf
License: CC BY 4.0
File access level: Anyone

  • 34
    total views
  • 45
    total downloads
  • 0
    views this month
  • 1
    downloads this month

Export as

Related outputs

Revising data collection methodology - evidence from the Australian financial sector
Neilson, Ben, Marty, Tom and Daley, Nat. 2024. "Revising data collection methodology - evidence from the Australian financial sector." The Journal of Finance and Data Science. 10. https://doi.org/10.1016/j.jfds.2024.100131
Investigating the relationship between processes and profit: A work-based assessment of process used in Australian financial planning firms
Neilson, Ben. 2024. "Investigating the relationship between processes and profit: A work-based assessment of process used in Australian financial planning firms." The Journal of Finance and Data Science. 10. https://doi.org/10.1016/j.jfds.2024.100128
Identifying the properties and impact of education on misconduct: Evidence from Australian financial advisers
Neilson, Ben Oakley and Lee, Steven J.. 2024. "Identifying the properties and impact of education on misconduct: Evidence from Australian financial advisers." International Journal of Educational Development. 105. https://doi.org/10.1016/j.ijedudev.2023.102976
Investigating the impact financial content structure has on consumer appreciation: An empirical study of Australian statement of advice documents
Neilson, Ben. 2023. "Investigating the impact financial content structure has on consumer appreciation: An empirical study of Australian statement of advice documents." The Journal of Finance and Data Science. 9. https://doi.org/10.1016/j.jfds.2023.100103