IDEAS home Printed from https://ideas.repec.org/a/epw/ejbmr0/v8y2023i3id51985.html

Detecting Fraudulent Financial Reporting with Financial Ratios: Case Study on Indonesia Stock Exchange

Author

Listed:
  • Abdul Hafiz Tanjung

    (National PASIM University, Indonesia)

  • Af’idatul Maghfiroh

    (National PASIM University, Indonesia)

Abstract

This study aimed to examine the significant differences in the financial ratios of FFR and non-FFR companies listed on the Indonesia Stock Exchange (IDX) in 2018-2019. It used the difference test of two population means and the Mann-Whitney U test to determine the financial ratios useful in distinguishing the companies. Furthermore, multiple logistic regression was employed to determine significant financial ratios as predictors against Fraudulent Financial Reporting (FFR). The M-Score formula was applied to classify the sample into 19 non-FFR and 59 FFR public companies. The results showed that seven financial ratios effectively differentiate FFR and non-FFR companies. Moreover, one significant financial ratio predicts FFR in public companies listed on the Indonesia Stock Exchange.

Suggested Citation

  • Abdul Hafiz Tanjung & Af’idatul Maghfiroh, 2023. "Detecting Fraudulent Financial Reporting with Financial Ratios: Case Study on Indonesia Stock Exchange," European Journal of Business and Management Research, European Open Science, vol. 8(3), pages 298-304, April.
    • Handle: RePEc:epw:ejbmr0:v:8:y:2023:i:3:id:51985
    DOI: 10.24018/ejbmr.2023.8.3.1985
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejbmr/article/view/51985
    File Function: Abstract page
    Download Restriction: no
    File URL: https://eu-opensci.org/index.php/ejbmr/article/download/51985/7734
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.24018/ejbmr.2023.8.3.1985?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

    ;
    ;
    ;
    ;

    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:epw:ejbmr0:v:8:y:2023:i:3:id:51985. 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: Support Team (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejbmr .

    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.