IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0300195.html
   My bibliography  Save this article

Machine learning in internet financial risk management: A systematic literature review

Author

Listed:
  • Xu Tian
  • ZongYi Tian
  • Saleh F A Khatib
  • Yan Wang

Abstract

Internet finance has permeated into myriad households, bringing about lifestyle convenience alongside potential risks. Presently, internet finance enterprises are progressively adopting machine learning and other artificial intelligence methods for risk alertness. What is the current status of the application of various machine learning models and algorithms across different institutions? Is there an optimal machine learning algorithm suited for the majority of internet finance platforms and application scenarios? Scholars have embarked on a series of studies addressing these questions; however, the focus predominantly lies in comparing different algorithms within specific platforms and contexts, lacking a comprehensive discourse and summary on the utilization of machine learning in this domain. Thus, based on the data from Web of Science and Scopus databases, this paper conducts a systematic literature review on all aspects of machine learning in internet finance risk in recent years, based on publications trends, geographical distribution, literature focus, machine learning models and algorithms, and evaluations. The research reveals that machine learning, as a nascent technology, whether through basic algorithms or intricate algorithmic combinations, has made significant strides compared to traditional credit scoring methods in predicting accuracy, time efficiency, and robustness in internet finance risk management. Nonetheless, there exist noticeable disparities among different algorithms, and factors such as model structure, sample data, and parameter settings also influence prediction accuracy, although generally, updated algorithms tend to achieve higher accuracy. Consequently, there is no one-size-fits-all approach applicable to all platforms; each platform should enhance its machine learning models and algorithms based on its unique characteristics, data, and the development of AI technology, starting from key evaluation indicators to mitigate internet finance risks.

Suggested Citation

  • Xu Tian & ZongYi Tian & Saleh F A Khatib & Yan Wang, 2024. "Machine learning in internet financial risk management: A systematic literature review," PLOS ONE, Public Library of Science, vol. 19(4), pages 1-23, April.
  • Handle: RePEc:plo:pone00:0300195
    DOI: 10.1371/journal.pone.0300195
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0300195
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0300195&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0300195?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Saleh F. A. Khatib & Dewi Fariha Abdullah & Ahmed A. Elamer & Raed Abueid, 2021. "Nudging toward diversity in the boardroom: A systematic literature review of board diversity of financial institutions," Business Strategy and the Environment, Wiley Blackwell, vol. 30(2), pages 985-1002, February.
    2. Zixian Liu & Guansan Du & Shuai Zhou & Haifeng Lu & Han Ji, 2022. "Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1481-1499, April.
    3. Linqi Huang & Shaofeng Wang & Xin Cai & Zhengyang Song, 2022. "Mathematical Problems in Rock Mechanics and Rock Engineering," Mathematics, MDPI, vol. 11(1), pages 1-3, December.
    4. Shuangshuang Fan & Yanbo Shen & Shengnan Peng, 2020. "Improved ML-Based Technique for Credit Card Scoring in Internet Financial Risk Control," Complexity, Hindawi, vol. 2020, pages 1-14, November.
    5. Yaqin Guang & Shunyong Li & Quanping Li & Miaochao Chen, 2022. "Internet Financial Risk Monitoring and Evaluation Based on GABP Algorithm," Journal of Mathematics, Hindawi, vol. 2022, pages 1-14, February.
    6. Dong Yang & Min Li, 2018. "Evolutionary Approaches and the Construction of Technology-Driven Regulations," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(14), pages 3256-3271, November.
    7. Mingjin Liu & Ruijie Gao & Wei Fu & Miaochao Chen, 2021. "Analysis of Internet Financial Risk Control Model Based on Machine Learning Algorithms," Journal of Mathematics, Hindawi, vol. 2021, pages 1-10, 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. Joao Felipe Gueiros & Hemanth Chandravamsi & Steven H. Frankel, 2025. "Deep Learning vs. Black-Scholes: Option Pricing Performance on Brazilian Petrobras Stocks," Papers 2504.20088, arXiv.org.
    2. Xiaoxi Men & Zhihui Han, 2023. "Prediction criterion and numerical validation for the interaction between hydraulic fractures and bedding planes," PLOS ONE, Public Library of Science, vol. 18(12), pages 1-16, December.
    3. Fuming Deng & Lu Cai & Xiaolei Ma, 2024. "Does digital transformation restrict the carbon emission intensity of enterprises? Evidence from listed manufacturing enterprises in China," Natural Resources Forum, Blackwell Publishing, vol. 48(2), pages 364-384, May.
    4. Saddam A. Hazaea & Ebrahim Mohammed Al-Matari & Saleh F. A. Khatib & Khaldoon Albitar & Jinyu Zhu, 2023. "Internal Auditing in the Arab World: A Systematic Literature Review and Directions for Future Research," SAGE Open, , vol. 13(4), pages 21582440231, October.
    5. Francisco Díez-Martín & Giorgia Miotto & Cristina Del-Castillo-Feito, 2024. "The intellectual structure of gender equality research in the business economics literature," Review of Managerial Science, Springer, vol. 18(6), pages 1649-1680, June.
    6. Saddam A. Hazaea & Ebrahim Mohammed Al-Matari & Khaled Zedan & Saleh F. A. Khatib & Jinyu Zhu & Hamzeh Al Amosh, 2022. "Green Purchasing: Past, Present and Future," Sustainability, MDPI, vol. 14(9), pages 1-28, April.
    7. Ali Shariff Kabara & Saleh F. A. Khatib & Ayman Hassan Bazhair & Hamid Ghazi H Sulimany, 2022. "The Effect of the Board’s Educational and Gender Diversity on the Firms’ Performance: Evidence from Non-Financial Firms in Developing Country," Sustainability, MDPI, vol. 14(17), pages 1-15, September.
    8. Dhir, Amandeep & Khan, Sher Jahan & Islam, Nazrul & Ractham, Peter & Meenakshi, N., 2023. "Drivers of sustainable business model innovations. An upper echelon theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    9. Shuchi Pahuja & Anita Agrawal, 2023. "Board Attributes and Corporate Social Responsibility: A Systematic Literature Review and Future Research Perspectives," Indian Journal of Corporate Governance, , vol. 16(1), pages 108-138, June.
    10. Xue, Qinyuan & Zhan, Peng & Jin, Yifei & He, Hui, 2024. "Reputation, commitment, and financial market regulation," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    11. Zhang, Yanan & Zhang, Xiaoyu, 2024. "Top management team functional diversity and ESG performance," Finance Research Letters, Elsevier, vol. 63(C).
    12. Ibrahim, Awad Elsayed Awad & Hussainey, Khaled & Nawaz, Tasawar & Ntim, Collins & Elamer, Ahmed, 2022. "A systematic literature review on risk disclosure research: State-of-the-art and future research agenda," International Review of Financial Analysis, Elsevier, vol. 82(C).
    13. Cláudia Pereira & Albertina Monteiro & Diana Silva & Armindo Lima, 2023. "Do the Levels of Environmental Sustainability Disclosure and Indebtness Affect the Quality of Earnings?," Sustainability, MDPI, vol. 15(4), pages 1-13, February.
    14. Yoojung Kim & Sejung Marina Choi, 2022. "When Bad Becomes Good: The Role of Congruence and Product Type in the CSR Initiatives of Stigmatized Industries," Sustainability, MDPI, vol. 14(13), pages 1-16, July.
    15. Talat Mehmood Khan & Naiping Zhu, 2025. "How social and environmental investments attract and repel foreign investors: Insights on shareholder and stakeholder engagement," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(2), pages 2996-3007, April.
    16. Tampakoudis, Ioannis & Nerantzidis, Michail & Eweje, Gabriel & Leventis, Stergios, 2022. "The impact of gender diversity on shareholder wealth: Evidence from European bank M&A," Journal of Financial Stability, Elsevier, vol. 60(C).
    17. Olubunmi Florence Osemene & Paulina Adinnu & Temitope Olamide Fagbemi & Johnson K. Olowookere, 2024. "Corporate Governance and Environmental Accounting Reporting in Selected Quoted African Companies," Global Business Review, International Management Institute, vol. 25(4), pages 1096-1119, August.
    18. Hamzeh Al Amosh & Saleh F. A. Khatib & Khaled Hussainey, 2022. "The Financial Determinants of Integrated Reporting Disclosure by Jordanian Companies," JRFM, MDPI, vol. 15(9), pages 1-20, August.
    19. ABM Fazle Rahi, 2025. "Unpacking women’s power on corporate boards: gender reward in board composition," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 22(1), pages 64-80, March.
    20. Lennart Ante, 2020. "A place next to Satoshi: foundations of blockchain and cryptocurrency research in business and economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1305-1333, August.

    More about this item

    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:plo:pone00:0300195. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.