GENERALIZATION OF THE WORLD PRACTICE OF RISK ANALYSIS IN TAX DEBT MANAGEMENT

The article is devoted to the world experience of tax debt management. The authors discuss the experience of organizing public administration of tax debt of OECD countries and European Union countries, which may become a benchmark for the development of the tax debt administration system in Ukraine. It is in the context of European integration that it is necessary to find ways to improve the administration of tax debt on the basis of new approaches that meet the goals and objectives of the state in the tax field. A clear division of taxpayers with tax debt into segments and sub-segments according to the risk factors of debt repayment will make changes to the organization of the administration of tax debt in order to prevent the emergence and accumulation of new debts before the budget and ensure the repayment of existing ones. The problems of tax debt optimization are investigated. Risk oriented approaches to tax debt management are considered. In the process of research, the countries in which the controlling authorities are noted for their efficiency in particular in paying off tax debt are highlighted. Debtor segmentation criteria and priority areas for improving tax debt administration procedures in the context of the implementation of the global experience are identified and systematized, and taxpayer segmentation criteria for tax debt are further substantiated to further determine priorities in tax administration. The proposed approaches are based on the study of foreign experience and take into account the factors of value and probability of repayment of tax debt. Tax debt administration strategies are applied to each segment of debtors. Emphasis is placed on the need to apply an individual approach to the debtor in the application of impact measures to collect a tax debt. Tactical and strategic measures to collect taxpayer debt are summarized. Keywords: tax debt, collection authorities, tax debt management, taxpayers, automated analytical models.