IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v17y2024i8p352-d1455210.html

Bibliometric Analysis of the Machine Learning Applications in Fraud Detection on Crowdfunding Platforms

Author

Listed:
  • Luis F. Cardona

    (Facultad de Minas, Universidad Nacional de Colombia Sede Medellín, Medellín 050001, Colombia)

  • Jaime A. Guzmán-Luna

    (Facultad de Minas, Universidad Nacional de Colombia Sede Medellín, Medellín 050001, Colombia)

  • Jaime A. Restrepo-Carmona

    (Facultad de Minas, Universidad Nacional de Colombia Sede Medellín, Medellín 050001, Colombia)

Abstract

Crowdfunding platforms are important for startups, since they offer diverse financing options, market validation, and promotional opportunities through an investor community. These platforms provide detailed company information, aiding informed investment decisions within a regulated and secure environment. Machine learning (ML) techniques are important in analyzing large data sets, detecting anomalies and fraud, and enhancing decision-making and business strategies. A systematic review employed PRISMA guidelines, which studied how ML improves fraud detection on digital crowdfunding platforms. The analysis includes English-language studies from peer-reviewed journals published between 2018 and 2023 to analyze the pre- and post-COVID-19 pandemic. The findings indicate that ML techniques such as Random Forest, Support Vector Machine, and Artificial Neural Networks significantly enhance the predictive accuracy and utility of tax planning for startups considering equity crowdfunding. The United States, Germany, Canada, Italy, and Turkey do not present statistically significant differences at the 95% confidence level, standing out for their notable academic visibility. Florida Atlantic and Cornell Universities, Springer and John Wiley & Sons Ltd. publishing houses, and the Journal of Business Ethics and Management Science magazines present the highest citations without statistical differences at the 95% confidence level.

Suggested Citation

  • Luis F. Cardona & Jaime A. Guzmán-Luna & Jaime A. Restrepo-Carmona, 2024. "Bibliometric Analysis of the Machine Learning Applications in Fraud Detection on Crowdfunding Platforms," JRFM, MDPI, vol. 17(8), pages 1-23, August.
    • Handle: RePEc:gam:jjrfmx:v:17:y:2024:i:8:p:352-:d:1455210
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/17/8/352/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/17/8/352/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gaia Bassani & Nicoletta Marinelli & Silvio Vismara, 2019. "Crowdfunding in healthcare," The Journal of Technology Transfer, Springer, vol. 44(4), pages 1290-1310, August.
    2. Antonella Francesca Cicchiello & Francesca Battaglia & Stefano Monferrà, 2019. "Crowdfunding tax incentives in Europe: a comparative analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 25(18), pages 1856-1882, December.
    3. Abhishek Behl & Pankaj Dutta & Zongwei Luo & Pratima Sheorey, 2022. "Enabling artificial intelligence on a donation-based crowdfunding platform: a theoretical approach," Annals of Operations Research, Springer, vol. 319(1), pages 761-789, December.
    Full references (including those not matched with items on IDEAS)

    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. Harrison, Richard T. & Bock, Adam J. & Gregson, Geoff, 2020. "Stairway to heaven? rethinking angel investment policy and practice," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
    2. Borello, Giuliana & Muri, Roberta, 2024. "The effect of covid policy restrictions on donations during the sustainable and entrepreneurial context," Journal of Business Research, Elsevier, vol. 177(C).
    3. Thanwamas Kassanuk & Khongdet Phasinam, 2023. "A Hybrid Binary Bird Swarm Optimization (BSO) and Dragonfly Algorithm (DA) for VM Allocation and Load Balancing in Cloud," International Journal of Cloud Applications and Computing (IJCAC), IGI Global Scientific Publishing, vol. 13(1), pages 1-21, January.
    4. Abhishek Behl & Brinda Sampat & Sahil Raj, 2025. "An empirical investigation of repeated donations on crowdfunding platforms during COVID-19," Annals of Operations Research, Springer, vol. 348(3), pages 1849-1877, May.
    5. Wang, Qiang & Ji, Xiang & Zhao, Nenggui, 2024. "Embracing the power of AI in retail platform operations: Considering the showrooming effect and consumer returns," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    6. Nora Kenworthy & Zhihang Dong & Anne Montgomery & Emily Fuller & Lauren Berliner, 2020. "A cross-sectional study of social inequities in medical crowdfunding campaigns in the United States," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-23, March.
    7. Rizwan, Amina & Hanif, Muhammad Shehzad & Khan, Talha Zubair Ahmad, 2025. "Laying the foundations of technology startups– An inquiry of crowd-funding investment decisions in a developing country," Technology in Society, Elsevier, vol. 81(C).
    8. Laura Grassi & Simone Fantaccini, 2022. "An overview of Fintech applications to solve the puzzle of health care funding: state-of-the-art in medical crowdfunding," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-27, December.
    9. Hua, Sheng & Liu, Huina & Ji, Zheng & Liang, Han, 2025. "The impact of air pollution on crowdfunding donations for critical illnesses: Evidence from China," China Economic Review, Elsevier, vol. 91(C).
    10. Lazos, Aristogenis, 2025. "When policy makers want to protect investors in equity crowdfunding: Does it have regional implications?," Technological Forecasting and Social Change, Elsevier, vol. 215(C).
    11. Fugeray-Scarbel, Aline & Lemarié, Stéphane, 2024. "The amplified effect of market size on innovation: A comparative analysis of pea and wheat seed value chains in France," Agricultural Systems, Elsevier, vol. 219(C).
    12. Wanting Hao & Xianguo Li & Fangliang Zhang, 2025. "Certified by social networks: the role of social certifications in medical crowdfunding," Electronic Commerce Research, Springer, vol. 25(3), pages 1827-1864, June.
    13. repec:bcp:journl:v:8:y:2024:i:10:p:1635-1642 is not listed on IDEAS
    14. Liu, Jiawei & Ding, Jie, 2020. "Requesting for retweeting or donating? A research on how the fundraiser seeks help in the social charitable crowdfunding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    15. Juliane Proelss & Denis Schweizer & Tingyu Zhou, 2021. "Economics of philanthropy—evidence from health crowdfunding," Small Business Economics, Springer, vol. 57(2), pages 999-1026, August.
    16. Vincenzo Butticè & Silvio Vismara, 2022. "Inclusive digital finance: the industry of equity crowdfunding," The Journal of Technology Transfer, Springer, vol. 47(4), pages 1224-1241, August.
    17. Caitlin Neuwelt-Kearns & Tom Baker & Octavia Calder-Dawe & Ann E Bartos & Susan Wardell, 2024. "Getting the crowd to care: Marketing illness through health-related crowdfunding in Aotearoa New Zealand," Environment and Planning A, , vol. 56(1), pages 311-329, February.
    18. Zhengwei Huang & Jing Ouyang & Xiaohong Huang & Yanni Yang & Ling Lin, 2021. "Explaining Donation Behavior in Medical Crowdfunding in Social Media," SAGE Open, , vol. 11(2), pages 21582440211, April.
    19. Aristogenis Lazos, 2025. "Does equity crowdfunding benefit ventures located in high unemployment regions?," Small Business Economics, Springer, vol. 64(2), pages 575-598, February.
    20. Francesco Schiavone & Natalia Vershinina, 2024. "Examining the Entrepreneurial Revolution in Healthcare," Post-Print hal-04663235, HAL.
    21. Sara Picas & Pedro Reis & António Pinto & José Luís Abrantes, 2021. "Does Tax, Financial, and Government Incentives Impact Long-Term Portuguese SMEs’ Sustainable Company Performance?," Sustainability, MDPI, vol. 13(21), pages 1-16, October.

    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:8:p:352-:d:1455210. 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 The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (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.