Abstract
The study uses data of listed non-financial companies in 2018 and 2019, combining M-Score and Z-Score models, applying ANN and SVM machine learning techniques in forecasting evidence of fraud in financial statements. Research results show that using SVM technique and M-Score index has high accuracy in predicting.
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This research is funded by Vietnam National University Ho Chi Minh City (VNU-HCM) under grant number DS2022-34-03.
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Phong, N.A., Tam, P.H., Thanh, N.P. (2022). Fraud Identification of Financial Statements by Machine Learning Technology: Case of Listed Companies in Vietnam. In: Ngoc Thach, N., Kreinovich, V., Ha, D.T., Trung, N.D. (eds) Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics. ECONVN 2022. Studies in Systems, Decision and Control, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-030-98689-6_28
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