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Identification of financial non-compliance in Russian companies: Tools and their testing

Gudova M.R. Financial University under Government of Russian Federation, Moscow, Russian Federation ( GudovaMR@gmail.com )

Journal: Finance and Credit, #12, 2018

Subject The article investigates the financial non-compliance in organizations, which includes instances of financial irregularity, legal offense, corporate fraud, and other destructive events of economic life.
Objectives The focus is on introducing an effective model to identify instances of financial non-compliance by organizations through testing the tools being the most appropriate for Russian economic conditions.
Methods I use the data on 700 Russian organizations, including those that Russian courts found guilty of gross violation of accounting (financial) requirements. I update the equations of tested models on a sample of Russian organizations by using the tools of a logit model in accordance with initial methodology for model development.
Results I assessed the classification accuracy of Russian organizations by pilot basic models based on the analysis of financial non-compliance identification, and proved the low accuracy of foreign basic models in Russian economic conditions. It is reasonable to use the findings to improve the mechanism of mitigating the risk of fraudulent actions by economic entities and increasing the transparency of the corporate sector, including through reducing the unintentional misstatement and shrinking the off-the-books economy.
Conclusions It is crucial to have effective tools to minimize financial and non-financial damage from financial non-compliance of companies. The paper confirms low accuracy of tested models for identifying financial non-compliance in Russian economic conditions. Updating the equations enabled to enhance the model accuracy, however, it is insufficient for significant reduction of investors' and creditors' losses.


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