Relevance. The transformation of the Russian economy in the context of sanctions pressure from the European Union and the United States necessitates a drastic shift in the structure of the national economy. It is based on an augmentation of the share of processing industries, enhancing economic security and self-sufficiency of the leading sectors in the production of strategic goods, as well as accelerating the pace of production renewal and improving its efficiency. Such alterations require substantial modifications, primarily, regarding control processes that constitute the information basis of the management system, thereby offering comprehensive justification for strategic, current, and operational management resolutions. It is of particular importance in this regard, as it is currently essential to assess the rationale for these adjustments.

The subject of the study. The analysis will encompass the existing accounting methods, the various types of reporting and auditing, and the new national goals. In addition, it will analyse the changes in the organisational and technological situation in production. It will evaluate the potential for the use of modern information and communication technologies and AI. Risks and opportunities for achieving the stated objectives will be identified. General scientific methodology was used: economic and mathematical methods, systems, dynamic, functional cost, and business analysis. The article examines the possibilities of using domestic management experience in different periods of the nation’s economic development.

The theoretical basis of the study includes materials summarising the experience of leading economic entities, industries, and regions of the country.

The results of the study may be of use to specialists at economic entities involved in the development of accounting, control, and preparation of various types of reporting systems, taking into account the requirements for ensuring financial stability, social and environmental responsibility. As well for the state and regional government bodies in the development of regulatory materials and methodological recommendations.

The purpose of the study was to identify relevant areas of capital accounting for sustainable development, and its subject was to define the concepts of capital in the models of long-term development of business and society. The author used such general scientific research methods as analysis, abstraction, generalization, deduction and analogy.

Conclusions. The models of long-term business and society development compete with each other. The transformation of views on business ethics without a fundamental change in the economic and political system can mitigate, but not resolve, global contradictions. The dominant approach is one in which all forms of capital are defined as controlled tangible and intangible assets. Perhaps, the classical approach to capital as an amount of debt, enriched by the concept of the autonomous existence of capital, better corresponds to the goals of sustainable development and the preservation of natural and social capital.

The results of the study can be useful in theoretical research in the field of accounting for non-financial forms of capital.

The quality of professional audit services is fundamental for trust in the work of auditors, which ensures the protection of interests of users of financial statements. The implementation of international Statement on Quality Management Standard 1 (MSC 1) and International Standard on Auditing 220 (ISA 220, revised) in the Russian Federation upgrades methodological approaches to documenting information on quality risk management in audit organisations.

The objective of the study is to develop comprehensive methodological approaches to the procedure of documenting risk management processes related to the quality of audit services in view of the requirements of modern legislation of the Russian Federation and international professional standards. The study included the methods of system analysis, synthesis, structural and logical modeling, generalisation of domestic and foreign practice of the organisation of quality management systems (QMS) in auditing organisations. The research established that effective documentation of information on quality risks requires the integration of three main approaches: process-based, risk-oriented and systemic one. A documentation model has been developed, which includes strategic, tactical and operational levels, thus ensuring the capacity to trace the chain from risk identification, risk assessment, development of response measures to monitoring of effectiveness. The study suggests a classification of working documents used in the framework of QMS by functional purpose and stages of the risk assessment process. The research defines the criteria for completeness, reliability and timeliness of documentation of information on quality risks.

The research results are focused on the practical implementation by audit organisations of various levels in construction and improvement of quality management standard in accordance with MSC 1.

The article examines the theoretical and institutional aspects of development of sustainability ratings under the growing regulatory pressure on non-financial reporting.

The object of the study is the international and national approaches to the development of the rating methodologies, while the tasks include systematising the theoretical foundations of rating agencies’ approaches and identifying the key directions of their institutional evolution.

As a result, the study reveals factors underlying the methodological fragmentation of the sustainability rating market, including the diversity of criteria, differences in scoring scales, and the absence of unified reliability standards.

The (authors of the) research demonstrated that the given sustainability ratings function as a mechanism for reducing information asymmetry and serve as signals of companies’ non-financial risks; however, their interpretation is complicated due to the lack of methodological comparability. The study substantiates the need to transition to a regulatory model that ensures transparency, comparability, and verifiability of the ratings.

The practical implication of the study lies in establishing a foundation for the development of a national regulatory system for the sustainability rating market and for improving the quality of non-financial information for stakeholders. The study may be of interest for national regulators, professional communities, as well as for investors and financial market participants.

In conditions of high volatility of commodity markets and the growing role of behavioral factors, traditional methods of comparative approach to business assessment are losing accuracy and predictive stability. This problem is particularly acute when using cost multipliers that do not reflect investors’ expectations and the future dynamics of companies’ financial performance. The article proposes a method for constructing forward multipliers based on the integration of machine learning and Monte Carlo simulation. The method allows you to separately predict the components of the multiplier – the market price of shares and net profit, taking into account fundamental, industry and behavioral cost factors. Special attention is paid to the problem of the lack of forecast values for exogenous variables, which is solved using scenario modeling. The method was tested on data from a public company in the oil and gas sector, which made it possible to identify structural differences in the factors determining price and profit. The results obtained demonstrate the high predictive ability of the models and confirm the expediency of switching from historical to forward multipliers in the practice of valuation. The developed approach expands the tools of the comparative approach and can be used in investment analysis and business valuation in conditions of uncertainty.

The relevance of the study is determined by the social significance of auditing. This branch of professional services in the financial market is strategically important for the state: it ensures the efficient use of both budget funds and private investment. The audit ecosystem encompasses bearers and users of audit competencies, whose range is expanding, which is primarily associated with institutional transformations and the development of the Russian financial market. Currently, the audit community anticipates a critical shortage of suitably qualified personnel in the industry soon. This factor is of particular concern to the entire ecosystem, as it requires for regulatory changes to enhance the prestige of this profession and promote early qualification certification in universities.

The objective of the present article is to provide substantial proposals for the development of the audit ecosystem through institutional transformations to reboot the competitiveness of the audit profession. This is in view of the broad versatility of competencies and the social significance of auditing.

The analytical methods yielded such findings as the assessment of development trends of the audit ecosystem, the determination of institutional factors affecting the industry, the identification of generalised competitive advantages of the audit profession, as well as empirical analysis of success percentage of qualification exams and a survey of audit ecosystem participants.

The results may be of practical interest to industry regulators, primarily, the Russian Ministry of Finance, the Bank of Russia, the Ministry of Labor, the Ministry of Education and Science, as well as the universities involved in training personnel for the financial market.

In the context of demographic decline, modern universities are compelled to compete with one another, striving to achieve a superior position in the educational services market by developing strategies for the growth of intellectual capital (IC). Therefore, the quantitative assessment of intellectual capital components represents a current scientific and practical challenge.

The objective of the study is to assess the contribution of educational assets to enhance the effectiveness of university. The research tasks included the following: conducting a literature review, classifying educational activities according to their affiliation with IC components, processing empirical data related to educational assets, as well as assessing statistical relationships between forms of academic activity and final results. The given scientific problem was solved by means of Bayesian sampling, the Monte Carlo method, Fisher’s Z-transformation, and correlation analysis. Utilising the analysis of posterior distributions of correlations between various educational assets and assessment results, the authors recommend a model with weighting coefficients that correspond to different forms of academic activity and reflect their differentiated contribution to IC.

The results of the study could be of use for heads of university departments and educational program developers to optimise the educational process and allocate resources. The practical significance of the work lies in the algorithmisation of the developed mathematical tools.

The purpose of this study is to identify methodological gaps in the regulatory framework for internal audit in credit institutions implementing state subsidized lending programs and to substantiate the need to develop a specialized methodology for its implementation. The relevance of this work is determined by the increasing volume and complexity of such operations during periods of economic instability, which gives rise to specific regulatory, operational, and reputational risks in the banking sector. In analyzing Bank of Russia regulations, the author of the article concluded that there are no direct provisions mandating targeted audits of this segment of activity. It was also demonstrated that such an obligation is indirect and stems from a systematic interpretation of requirements for monitoring all business processes and compliance with regulatory legal acts. Furthermore, it was established that the lack of a standardized methodology leads to heterogeneity in audit practices in the banking sector and reduces the effectiveness of controls. Ultimately, a reasoned conclusion was reached regarding the need to transform internal audit into a proactive risk management tool in this segment.

The results of the study will be useful for commercial banks participating in preferential lending programs to improve internal audit activities and enhance the effectiveness of risk management.

The given article explores the areas of application of artificial intelligence (AI) focused on the transition from traditional periodic and expert methods of analysing bank activity to integrated autonomous data processing systems.

The objective of the study is to give a strong rational for such a transition, taking into account the limitations of existing methods, including the fragmentary nature of procedures, a high degree of dependence on expert interpretation and time delays inherent in decision-making.

The methodological basis of the study becomes the analysis of the institutional and functional characteristics of the traditional and integrated analytical cycles, the comparison of various methods of data interpretation, and the study of practical capabilities of modern automation technologies.

The results indicate that the development of integrated analysis transforms its role from a supporting instrument to an integral ingredient of the digital banking process. The research presents a novel approach used in banking activities, the so-called «self-assessment», in which the processes of collecting, processing and interpreting information are automated and integrated directly into the infrastructure of execution of operations.

The practical significance of the study lies in the results, which can be used to develop and implement AI-based embedded analysis systems in credit institutions. This allows them to transition from traditional methods with periodic data processing to continuous operation, which helps reducing operational risks and strengthen financial stability in compliance with ethical and legal requirements for the use of AI technologies.