Automation of tax risk identification in the accounting support system for import contracts using AI algorithms

Abstract

The relevance of the study is determined by the growing volume of import operations within enterprises’ foreign economic activity and the increasing requirements for the reliability of accounting and tax reporting. The purpose of the article is to develop approaches to automating tax risk identification within the system of accounting and control support for import operations, using artificial intelligence algorithms, to improve the efficiency of tax control and the reliability of reporting. Methods. The study employs methods of system analysis, generalization and systematization of scientific approaches to accounting and taxation of import operations, comparative analysis of tax control mechanisms, as well as analytical methods to assess the applicability of artificial intelligence algorithms in accounting support systems for foreign economic contracts. Results. The study characterizes the organizational features of accounting and control support for managing critical import goods and identifies the key stages of accounting and taxation of import operations. The role of customs value and value-added tax formation in the system of tax control of import transactions is determined. It is proven that the use of artificial intelligence algorithms enables the automation of the analysis of accounting, customs, and tax data, the detection of anomalies in financial indicators, and the formation of risk-oriented models for controlling import operations. The main problems in tax risk identification are identified, including fragmentation of information flows between accounting and customs systems, the complexity of determining customs value, and the limited analytical capabilities of traditional accounting systems. Conclusions. The expediency of forming an integrated system of automated tax control for import operations, based on the integration of accounting, customs, and tax information resources, and on the use of artificial intelligence algorithms for financial data analysis and tax risk forecasting, is substantiated. Prospects for further research include developing economic and mathematical models to assess tax risks in import operations, as well as exploring the integration of artificial intelligence technologies into digital accounting systems and the tax administration of foreign economic activity.