This article addresses the complexities inherent in real estate taxation systems. It highlights the lack of clearly defined priority areas in methods for calculating property taxes. The primary forms of taxation identified include ad valorem tax (based on property value), area-based tax, and income tax derived from real estate. Despite the diversity of these forms, there is a global trend toward ensuring fairness, transparency, and user-friendliness in the development of real estate tax systems. In this context, the integration of artificial intelligence and Automated Valuation Models (AVM) is becoming increasingly significant. The main objective of the paper is to analyze the fundamental elements of the real estate taxation system and to substantiate the crucial role of the property appraiser in ensuring consistency and equity within the taxing process. The research findings demonstrate that real estate taxation is a system composed of interconnected and complementary elements. Furthermore, the study scientifically justifies which specific stages of the taxable value determination process should be directly conducted by professional appraisers.

The rapid development of digital technologies has changed the way data is collected, stored, and analyzed. Big Data has created new opportunities and challenges for econometric research. This article discusses the integration of econometric methods with big data analysis, the methodological innovations needed, and the results of empirical economic research. The study also highlights modern tools and ideas that help econometricians manage the complexity and scale of large data sets while maintaining model accuracy and interpretability. It also highlights how the combination of traditional econometric thinking and computational methods can improve the quality and scope of economic analysis in the modern digital economy

This paper proposes a four-dimensional risk index model for designing internal audit programs in the public sector. The model integrates legal, financial, resource, and organizational risks to provide a comprehensive framework for risk-based audit planning. Through simulation involving hypothetical departments, the study demonstrates that aggregate risk scores can mask the diversity and specificity of underlying risk categories. By decomposing audit risk into distinct dimensions, the model enhances audit targeting, supports transparent decision-making, and aligns with international internal audit standards. It also proves particularly useful in environments with limited data availability. The model’s adaptability and clarity make it suitable for both manual and automated audit planning processes. While future enhancements could include dynamic weighting and digital integration, the model as presented already offers a robust and practical approach to prioritizing internal audit activities and improving public sector governance outcomes.

This article examines the impact of the systematic application of good corporate governance tools on the capitalization of joint-stock companies. Based on empirical data from leading public companies in Uzbekistan, an integrated model is proposed that includes board independence, audit committees, dividend policy, gender diversity, and stakeholder engagement. The results of the regression analysis show that the combined use of these corporate governance mechanisms significantly increases the value of Tobin’s Q, confirming the theoretical propositions of agency theory, resource-based approach, and stakeholder theory.

The article describes the procedure for improving the organization of reserve accounting of doubtful accounts receivable based on international financial reporting standards for accounts receivable, considered as a financial instrument in business entities. The diversity and complexity of financial instruments in financial markets around the world have increased dramatically in recent years. Accounting for financial instruments is a problem in practice, so it is desirable to widely use international standards.