Impact of financial information fraudulence on financial distress in Malaysia and Singapore

Financial distress has been extensively debated since the 1960s by numerous researchers. The huge scandal in financial reporting among gigantic companies such as Enron, Xerox and Worldcom has motivated this study to examine the impact of financial information fraudulence on the accuracy of financial...

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Bibliographic Details
Main Author: Abu Bakar, Dalila
Format: Thesis
Language:English
Published: 2020
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/99195/1/SPE%202021%2024%20IR.pdf
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Summary:Financial distress has been extensively debated since the 1960s by numerous researchers. The huge scandal in financial reporting among gigantic companies such as Enron, Xerox and Worldcom has motivated this study to examine the impact of financial information fraudulence on the accuracy of financial distress prediction. Most of the existing studies had focused on established markets using tests set by the Security Stock Exchange for identifying financial information fraudulence but of which corrective actions are considered too late. This study used consumer product companies listed on the main board and the timeframe is from 2011 till 2015. The Altman Z score indicates that 37 out of 133 and 55 out of 110 Malaysian and Singaporean consumer product companies respectively are financially distressed. Meanwhile, the M score shows that 14 (28 observations) out of 37 and 28 (49 observations) out of 55 companies in Malaysia and Singapore respectively are engaged in financial information fraudulence. However, these results are relatively low because the samples are taken from the main board and fraudulence in their financial statements might be done in lower magnitude in order to avoid sanctions by the Security Exchange Commission. Therefore, objective one is proven whereby some of the distressed companies are found to be engaged in financial information fraudulence activities. Logistic regression was used to measure accuracy in predicting financial distress. This test covered objective two whereby the result of the overall accuracy percentage slightly improved by 0.9 and 2.4 after eliminating fraudulent companies in Malaysia and Singapore, respectively. After comparing the confusion matrix result i.e. before and after the removal of financial information fraudulent companies, the misclassification errors especially type one for both countries improved. This finding satisfied objective three, whereby one of the reasons for the deterioration in financial distress prediction is due to the upward bias of financial information fraudulence. Overall, this study had proven that the deceitful act starts in the main market so that the companies can remain there. The design of simple models that are cost-saving and easy to operate by all investors seems to be helpful, especially in detecting financial information fraudulence and distressed companies as it can prevent investment losses.