Digital transformation of accounting and reporting in the agricultural sector as a tool to fight tax fraud and strengthen the region's economic security
Subject. This article deals with the methodology of digital transformation of analytical support for accounting and financial reporting in Russia's agro-industrial sector as a tool to counter tax fraud and strengthen the region's economic security. Objectives. The article aims to develop and scientifically justify an original method for the preventive detection of tax risks and combating fraud, based on a deep integration of financial, operational, and external non-financial data. Methods. For the study, we used a systems approach, the dialectical method, an interdisciplinary approach, comparative and systems analyses, statistical modeling, and the expert evaluation method. Results. The article presents an author-developed methodology for digital analytical support, helping to shift from a reactive control model to a proactive early risk detection system, a conceptual model of the digital ecosystem for agricultural analytical support, an algorithm for continuous monitoring of fraud 'red flags' adapted to the specifics of the agricultural sector, as well as a typology of tax fraud schemes in agriculture with corresponding digital indicators and a roadmap for implementing the methodology. Conclusions and Relevance. The practical and scientific value of the research lies in creating a dynamic, self-learning model for assessing tax security and reducing information asymmetry. The study results can be used by regional authorities, tax services, and internal control departments of agroholdings to improve risk management systems, ensure financial stability, and strengthen the economic security of the regional service sector and agriculture.
Keywords: digital transformation, accounting, agro-industrial complex, economic security, tax fraud
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