| Summary: | Fraud has been of concern for many corporate managers and regulators since many businesses have been victim of business failures. Business failure corporations have reported and become an element of fraudulent financial reporting. Therefore, the first aim of this study is to examine whether a collective prediction tool can be used to predict business failure and fraudulent financial reporting. The second and more important objective of this study is to examine whether business failure companies are associated with fraudulent financial reporting. The collective prediction tool is based on ratio analysis, Beneish M-score model and Z-score model. Using publicly available information in the annual reports of 24 failed firms matched with 24 non-failed firms listed on Bursa Malaysia, relevant information are extracted and applied in the three models to assist in predicting business failure and detecting fraudulent financial reporting. A total of 10 ratios, cash conversion cycle, Beneish M-score model and Altman’s Z-score model were identified for examination as potential predictors of business failure and fraudulent financial reporting. Based on the results, the model was accurate in classifying the total sample of approximately 96 per cent as predictors of business failure and approximately 83.3 per cent as predictors of fraudulent financial reporting as well as predicting the relationship between business failures and fraudulent financial reporting. Hence, it can be concluded that these model functions effectively and can be adopted by regulators, bankers, management, internal and external auditors and to the forensic accountants so that proper preventive or corrective action can be taken to mitigate fraud at its inception. © 2015 Institute of Public Enterprise SAGE Publications.
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