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.

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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
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article

Assessing and forecasting the risk of financial statement fraud of enterprises listed on the Vietnamese stock market - A logistic regression model approach

Thach Tran, Thu Hang Nguyen, Minh Trinh-Hoang, Thu Thuy Nguyen et al.
Journal of Finance & Accounting Research
Imbalanced Data Classification Techniques
article

Assessing and forecasting the risk of financial statement fraud of enterprises listed on the Vietnamese stock market - A logistic regression model approach

Thach Tran, Thu Hang Nguyen, Minh Trinh-Hoang, Thu Thuy Nguyen, Thi Thanh Huyen Nguyen
article en

Abstract

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.

Journal of Finance & Accounting Research
Openalex Percentile: Top 99%
Imbalanced Data Classification Techniques
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