Proceedings of the 1st MICOSS Mercu Buana International Conference on Social Sciences, MICOSS 2020, September 28-29, 2020, Jakarta, Indonesia

Research Article

The Extensible Business Reporting Language and Fraudulent Financial Statement in Indonesia

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  • @INPROCEEDINGS{10.4108/eai.28-9-2020.2307378,
        author={Desya Puspa Wijaya and Diah Hari Suryaningrum},
        title={The Extensible Business Reporting Language and Fraudulent Financial Statement in Indonesia},
        proceedings={Proceedings of the 1st MICOSS Mercu Buana International Conference on Social Sciences, MICOSS 2020, September 28-29, 2020, Jakarta, Indonesia},
        publisher={EAI},
        proceedings_a={MICOSS},
        year={2021},
        month={5},
        keywords={extensible business reporting language (xbrl) firm size fraudulent financial statement},
        doi={10.4108/eai.28-9-2020.2307378}
    }
    
  • Desya Puspa Wijaya
    Diah Hari Suryaningrum
    Year: 2021
    The Extensible Business Reporting Language and Fraudulent Financial Statement in Indonesia
    MICOSS
    EAI
    DOI: 10.4108/eai.28-9-2020.2307378
Desya Puspa Wijaya1,*, Diah Hari Suryaningrum1
  • 1: UPN Veteran Jawa Timur, Surabaya, Indonesia
*Contact email: puspadesya22@gmail.com

Abstract

This study aims to prove the effectiveness of the implementation of Extensible Business Reporting Language (XBRL) on the level of fraudulent financial statements. The sample was determined by using purposive sampling method and obtained 81 companies as the research sample. The results showed that XBRL with the SIZE control variable affected financial statement fraud. In contrast, the control variables DAR, ROA, GDP, and PBV did not support the effect of XBRL on financial statement fraud. The test results also prove that there are differences before and after implementing XBRL, where the measurement of financial statement fraud is lower after the application of XBRL. This result means that the implementation of XBRL will force companies to provide accountable and transparent information. The business and financial information collected in XBRL is a machine format reading and operation, thereby increasing the ease of dissemination and public analysis, thus making it easier to detect fraudulent financial statements.