IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v17y2024i6p241-d1412445.html

ChatGPT, Help! I Am in Financial Trouble

Author

Listed:
  • Minh Tam Tammy Schlosky

    (College of Business and Management, University of Illinois Springfield, Springfield, IL 62703, USA)

  • Serkan Karadas

    (College of Business and Management, University of Illinois Springfield, Springfield, IL 62703, USA)

  • Sterling Raskie

    (Gies College of Business, University of Illinois Urbana-Champaign, Champaign, IL 61820, USA
    Blankenship Financial Planning, New Berlin, IL 62670, USA)

Abstract

This study examines the capability of ChatGPT to provide financial advice based on personal finance cases. We first write our own cases and feed them to ChatGPT to get its advice (recommendations) on them. Next, we assess the quality and the validity of ChatGPT’s recommendations on these cases. We find that ChatGPT serves as a suitable starting point, but its recommendations tend to be generic, and they often overlook alternative solutions and viewpoints and priority of recommendations. Overall, our analysis demonstrates the strengths and weaknesses of using ChatGPT in personal finance matters. Further, it serves as a helpful guide to financial advisors, households, and instructors of personal finance who are already using or considering using ChatGPT and want to develop a suitable understanding of the benefits and limitations of this new technology in addressing their professional and personal needs.

Suggested Citation

  • Minh Tam Tammy Schlosky & Serkan Karadas & Sterling Raskie, 2024. "ChatGPT, Help! I Am in Financial Trouble," JRFM, MDPI, vol. 17(6), pages 1-39, June.
    • Handle: RePEc:gam:jjrfmx:v:17:y:2024:i:6:p:241-:d:1412445
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/17/6/241/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/17/6/241/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pelster, Matthias & Val, Joel, 2024. "Can ChatGPT assist in picking stocks?," Finance Research Letters, Elsevier, vol. 59(C).
    2. Qianhua Liu & Ka-Ching Chan & Ranga Chimhundu, 2024. "Fintech research: systematic mapping, classification, and future directions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-33, December.
    3. Oehler, Andreas & Horn, Matthias, 2024. "Does ChatGPT provide better advice than robo-advisors?," Finance Research Letters, Elsevier, vol. 60(C).
    4. Niszczota, Paweł & Abbas, Sami, 2023. "GPT has become financially literate: Insights from financial literacy tests of GPT and a preliminary test of how people use it as a source of advice," Finance Research Letters, Elsevier, vol. 58(PA).
    5. Dowling, Michael & Lucey, Brian, 2023. "ChatGPT for (Finance) research: The Bananarama Conjecture," Finance Research Letters, Elsevier, vol. 53(C).
    6. Ko, Hyungjin & Lee, Jaewook, 2024. "Can ChatGPT improve investment decisions? From a portfolio management perspective," Finance Research Letters, Elsevier, vol. 64(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chiu, Ya-Ling & Gao, Xuechen & Liu, Hung-Chun & Zhai, Qiong, 2025. "Financial literacy of ChatGPT: Evidence through financial news," Finance Research Letters, Elsevier, vol. 78(C).
    2. Ali, Hassnian & Zafar, Muhammad Bilal & Aysan, Ahmet Faruk, 2025. "Generative AI in finance: Replicability, methodological contingencies, and future research directions," Finance Research Letters, Elsevier, vol. 86(PF).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dong, Mengming Michael & Stratopoulos, Theophanis C. & Wang, Victor Xiaoqi, 2024. "A scoping review of ChatGPT research in accounting and finance," International Journal of Accounting Information Systems, Elsevier, vol. 55(C).
    2. Lars Hornuf & David J. Streich & Niklas Töllich, 2025. "Making GenAI Smarter: Evidence from a Portfolio Allocation Experiment," CESifo Working Paper Series 11862, CESifo.
    3. Schneider, Constantin J. & Yilmaz, Yahya, 2025. "Stock portfolio selection based on risk appetite: Evidence from ChatGPT," Finance Research Letters, Elsevier, vol. 82(C).
    4. Ko, Hyungjin & Lee, Jaewook, 2024. "Can ChatGPT improve investment decisions? From a portfolio management perspective," Finance Research Letters, Elsevier, vol. 64(C).
    5. Ali, Hassnian & Zafar, Muhammad Bilal & Aysan, Ahmet Faruk, 2025. "Generative AI in finance: Replicability, methodological contingencies, and future research directions," Finance Research Letters, Elsevier, vol. 86(PF).
    6. Chiu, Ya-Ling & Gao, Xuechen & Liu, Hung-Chun & Zhai, Qiong, 2025. "Financial literacy of ChatGPT: Evidence through financial news," Finance Research Letters, Elsevier, vol. 78(C).
    7. Jeong, Woojin & Park, Seongwan & Lee, Seungyun & Son, Bumho & Lee, Jaewook & Ko, Hyungjin, 2024. "Influence and predictive power of sentiment: Evidence from the lithium market," Finance Research Letters, Elsevier, vol. 68(C).
    8. Hanyong Cho & Geumil Bae & Jang Ho Kim, 2026. "Investor risk profiles of large language models," Papers 2603.09303, arXiv.org, revised May 2026.
    9. Chon, Sora & Kim, Jaehoon & Kim, Jaeho, 2025. "Multifaceted variability in LLM-driven stock recommendations," Finance Research Letters, Elsevier, vol. 86(PG).
    10. Wang, Jying-Nan & Liu, Hung-Chun & Hsu, Yuan-Teng, 2025. "Do AI incidents and hazards matter for AI-themed cryptocurrency returns?," Finance Research Letters, Elsevier, vol. 74(C).
    11. Ma, Feng & Lyu, Zhichong & Li, Haibo, 2024. "Can ChatGPT predict Chinese equity premiums?," Finance Research Letters, Elsevier, vol. 65(C).
    12. Liu, Yingnan & Bu, Ningbo & Li, Zhiqiang & Zhang, Yongmin & Zhao, Zhenyu, 2025. "AT-FinGPT: Financial risk prediction via an audio-text large language model," Finance Research Letters, Elsevier, vol. 77(C).
    13. Song, Piaopeng & Lu, Hanglin & Zhang, Yongjie, 2024. "Unveiling tone manipulation in MD&A: Evidence from ChatGPT experiments," Finance Research Letters, Elsevier, vol. 67(PA).
    14. Christian Fieberg & Lars Hornuf & Maximilian Meiler & David J. Streich, 2025. "Using Large Language Models for Financial Advice," CESifo Working Paper Series 11666, CESifo.
    15. Oehler, Andreas & Horn, Matthias, 2024. "Does ChatGPT provide better advice than robo-advisors?," Finance Research Letters, Elsevier, vol. 60(C).
    16. Liyuan Chen & Shuoling Liu & Jiangpeng Yan & Xiaoyu Wang & Henglin Liu & Chuang Li & Kecheng Jiao & Jixuan Ying & Yang Veronica Liu & Qiang Yang & Xiu Li, 2025. "Advancing Financial Engineering with Foundation Models: Progress, Applications, and Challenges," Papers 2507.18577, arXiv.org, revised Dec 2025.
    17. Gregory, Gadzinski & Vito, Liuzzi, 2024. "ChatGPT: A canary in the coal mine or a parrot in the echo chamber? Detecting fraud with LLM: The case of FTX," Finance Research Letters, Elsevier, vol. 70(C).
    18. Zifeng Feng & Gangqing Hu & Bingxin Li & Jinge Wang, 2025. "Unleashing the power of ChatGPT in finance research: opportunities and challenges," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-26, December.
    19. Kevin He & Ran Shorrer & Mengjia Xia, 2025. "Human Misperception of Generative-AI Alignment:A Laboratory Experiment," PIER Working Paper Archive 25-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    20. Perlin, Marcelo S. & Foguesatto, Cristian R. & Müller, Fernanda M. & Righi, Marcelo B., 2025. "Can AI beat a naive portfolio? An experiment with anonymized data," Finance Research Letters, Elsevier, vol. 78(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:17:y:2024:i:6:p:241-:d:1412445. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.