Advances in Modeling for Falsified Financial Statements

This study is centered on developing advanced simplified Z-Score model for identification of falsified financial statements mainly from published data of emerging economies. The paper adopts qualitative response technique based on six parameter questions. The answers to these questions which are derivable from each financial statement are the nucleus for the construction of ‘Angus Z-Score’. Financial Statements of Fifty one companies with unique motivations to falsify were investigated. Statistical tools of analyses are T-test SPSS based and percentages. The study found it easier and simpler to use Angus Z-Score model in testing and identification of Falsified Financial Statements. The predictive efficacy of Angus Z-Score is significantly high. The model’s predictive ability increased in comparisons to adopted benchmark CPT. Model in some sectors. Angus Z-Score model is found to be an important analytical tool for pre-testing Corporate Financial reports for falsification/misstatements in order to enhance right investment and other business decisions.