Is the External Audit Report Useful for Bankruptcy Prediction? Evidence Using Artificial Intelligence
AbstractDespite the number of studies on bankruptcy prediction using financial ratios, very little is known about how external audit information can contribute to anticipating financial distress. A handful of papers have shown that a combination of ratios and audit data is significant for predictive purposes, but only one recent paper provided a predictive accuracy of 80% solely by using the disclosures contained in audit reports. This study was complemented by simplifying the analysis of audit reports for prediction purposes and the same predictive accuracy was achieved. By applying three artificial intelligence techniques (PART algorithm, random forest, and support vector machine), the predictive ability of more easily extracted information from the report was examined and a practical implication suggested for each user. Simply by (1) finding the audit opinion, (2) identifying if a matter section exists, and (3) the number of comments disclosed, any user may predict a bankruptcy situation with the same accuracy as if they had scrutinized the whole report. In addition, an extended literature review is included, on previous studies on the interaction between bankruptcy prediction and the external audit information.
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Muñoz-Izquierdo, N.; Camacho-Miñano, M.-D.-M.; Segovia-Vargas, M.-J.; Pascual-Ezama, D. Is the External Audit Report Useful for Bankruptcy Prediction? Evidence Using Artificial Intelligence. Int. J. Financial Stud. 2019, 7, 20.
Muñoz-Izquierdo N, Camacho-Miñano M-D-M, Segovia-Vargas M-J, Pascual-Ezama D. Is the External Audit Report Useful for Bankruptcy Prediction? Evidence Using Artificial Intelligence. International Journal of Financial Studies. 2019; 7(2):20.Chicago/Turabian Style
Muñoz-Izquierdo, Nora; Camacho-Miñano, María-del-Mar; Segovia-Vargas, María-Jesús; Pascual-Ezama, David. 2019. "Is the External Audit Report Useful for Bankruptcy Prediction? Evidence Using Artificial Intelligence." Int. J. Financial Stud. 7, no. 2: 20.
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