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Factors affecting the quality of financial statements from an audit point of view: A machine learning approach

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  • Dang Ngoc Hung
  • Vu Thi Thuy Van
  • Lan Archer

Abstract

This study examines the influence and importance of firm characteristics on the quality of financial statements of listed companies in Vietnam’s stock market from the audit point of view. We use regression models and machine learning algorithms to investigate data from 2225 observations of listed companies in the period 2014–2020. We find that business profitability, business size, and the size of the Board of Directors positively correlate with the quality of financial statements. In contrast, dividend policy, state ownership, and enterprise listing time have a negative relationship. Results show that the most critical factors affecting financial statement quality include profitability, profit after tax on total assets, state ownership, and enterprise size. This finding has practical implications for market participants and policymakers in improving financial reporting transparency and quality.

Suggested Citation

  • Dang Ngoc Hung & Vu Thi Thuy Van & Lan Archer, 2023. "Factors affecting the quality of financial statements from an audit point of view: A machine learning approach," Cogent Business & Management, Taylor & Francis Journals, vol. 10(1), pages 2184225-218, December.
    • Handle: RePEc:taf:oabmxx:v:10:y:2023:i:1:p:2184225
    DOI: 10.1080/23311975.2023.2184225
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    Cited by:

    1. Fatih Konak & Mehmet Akif Bülbül & Diler Türkoǧlu, 2024. "Feature Selection and Hyperparameters Optimization Employing a Hybrid Model Based on Genetic Algorithm and Artificial Neural Network: Forecasting Dividend Payout Ratio," Computational Economics, Springer;Society for Computational Economics, vol. 63(4), pages 1673-1693, April.

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