IDEAS home Printed from https://ideas.repec.org/a/ris/jecdev/023036.html

Machine-Learning Based Default Prediction: The Role of External Audits and Financial Constraints

Author

Listed:
  • Hyunjun Song

    (Ajou University, South Korea)

  • Dojoon Park

    (Kongju National University, South Korea)

  • Zoonky Lee

    (Yonsei University, South Korea)

  • Yong Joo Kang

    (Thompson Rivers University, Canada)

Abstract

We investigate the impact of external audits and financial constraints on predicting small and medium-sized enterprise (SME) defaults in Korea using data for both externally and non-externally audited firms. The importance of a SME-specific default model is highlighted through the performance comparison of default prediction models for SMEs and large firms. Since SMEs are more vulnerable to financial market shocks, variables related to cash reserves and financial constraints are included. The analysis by feature importance shows that variables related to cash balance and financial constraint contribute towards an improvement in default prediction for Korean SMEs.

Suggested Citation

  • Hyunjun Song & Dojoon Park & Zoonky Lee & Yong Joo Kang, 2026. "Machine-Learning Based Default Prediction: The Role of External Audits and Financial Constraints," Journal of Economic Development, The Economic Research Institute, Chung-Ang University, vol. 51(2), pages 13-41, June.
    • Handle: RePEc:ris:jecdev:023036
    DOI: 10.35866/caujed.2026.51.2.002
    as

    Download full text from publisher

    File URL: https://jed.cau.ac.kr/archives/51-2/51-2-2.pdf
    File Function: full text
    Download Restriction: None
    File URL: https://libkey.io/10.35866/caujed.2026.51.2.002?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:ris:jecdev:023036. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Jo A Jeong (email available below). General contact details of provider: https://edirc.repec.org/data/eccaukr.html .

    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.