Assessing and forecasting the risk of financial statement fraud of enterprises listed on the Vietnamese stock market - A logistic regression model approach
This article aims to assess and forecast the risk of financial statement fraud of enterprises listed on the Vietnamese stock market from 2018 to 2023. Based on the application of the Logistic Regression model with machine learning technique together with the famous M-Score model of Beneish (first published in June 1999) on the data collected from 25 enterprises, including 279 observations. The results of the study show that the application of the logistic regression model is capable of detecting fraud risks in financial statements with relatively high reliability. Most indicators have the same impact on the likelihood of fraudulent financial reporting.
Authors
- Thach Tran (ORCID: https://orcid.org/0000-0002-6454-124X)
- Thu Hang Nguyen (ORCID: https://orcid.org/0000-0002-1959-5708)
- Minh Trinh-Hoang (ORCID: https://orcid.org/0000-0002-9162-6644)
- Thu Thuy Nguyen
- Thi Thanh Huyen Nguyen (ORCID: https://orcid.org/0000-0002-3293-1745)
Publication Details
- Journal
- Journal of Finance & Accounting Research
- Published
- 2025-02-01
- DOI
- https://doi.org/10.71374/jfar.v25.i1.15
- Primary Topic
- Imbalanced Data Classification Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00