Since the COVID-19 pandemic, the global macroeconomic landscape has been characterized by a high level of uncertainty. The purpose of the work is to study the role of accounting risk assessment in ensuring the macroeconomic stability of markets. To achieve this goal, structural, functional and theoretical research methods were used: analysis, generalization and synthesis of literature in the field of accounting and finance. The study analyzed the macroeconomic uncertainty that may affect macro-financial stability. It is noted that financial variables may not fully cover macroeconomic uncertainty, therefore, in order to assess macrofinancial stability, accountants need to consider them as part of a systemic risk assessment and tail risk forecasting for markets and economic activity. To assess the relationship between macroeconomic uncertainty and the risks of deterioration in future production, accountants can use the extended GaR model using artificial intelligence methods. In conclusion, it is noted that high uncertainty regarding economic fundamentals and policies increases the risks of reducing future real GDP growth, stock and bond market returns, and bank lending, so it is important for accountants to conduct a competent risk assessment, including using machine learning models that improve the predictive ability of risk assessment frameworks.