Abstract:

The purpose of this study is to investigate whether there is a specific set of financial information that indicates manipulation in financial statements. The report aims to develop a model with a meaningful and high explanatory power in the detection of the risk of manipulation in financial statements. Carma models based on ratio analysis have been tested with BIST companies’ financial table data and strong indicators selected by logistics regression. Benford analysis has been used to classify risk and control groups. The model proposed in the study was created by the study of the strong and weak aspects of three models commonly used in literature - Altman (1978), Beneish (1999) and Spathis (2002) - to determine the risks in financial statements. The model has a 10.4 percent high explanatory power among the models compared to other models. The model predicts that the risk of manipulation in the financial statements is high by 16.7%. Also, all the variables in the model are meaningful at a 95 percent meaning level. This research is limited to 184 companies that trade in the real sector of BIST and the period 2008-2017. This article suggests an original model as an alternative to the karma models that can be used for manipulation risk detection. It also offers a new approach using Benford Analysis to classify models, risk and control groups. It is estimated that this model may be useful for auditors, experts and researchers for their audit objectives.

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