Identification of false financial statements: A pre-ante tool for investment decisions, solvency analysis and bankruptcy predictions

This research paper tested the efficacy of ʹCPT Analysesʹ model for identifying false financial statements. The CPT analyses model equation is represented thus Ag = pv ~N. The paper examines further some relevant literatures in an attempt to develop analytical tool for detecting false financial statements. Three null hypotheses were formulated and tested with samples of fifty-one companiesʹ financial statements. The decision outcomes of CPT analyses model were validated with T-test and Chi-square statistical tools. Out of the fifty one financial statements tested, 37% were found to be falsified. 57% of the predicted Companies that falsified their financial statements had been liquidated as at 2010. It was found that CPT analyses model can significantly discriminate between falsified and non-falsified financial statements. The proposed ʹCPT" analyses, showed that investment decisions and applications of corporate insolvency predictive models are useful only when financial statements are not falsified. It also showed that users of financial statements are at risk of forming opinions based on distorted and inaccurate information. The paper demonstrates that conducting and implementing the proposed ʹCPTʹ analyses for detection of false financial statements will, undoubtedly be helpful to professionals such as auditors, forensic accountants, insolvency practitioners, tax authorities, investors, consultants, banks and other users of financial statements.