The aim of the study is to identify and analyze the problems and priorities of budgetary support for the socio-economic development in the Republic of Bashkortostan at the present stage and to develop recommendations for improving the balance of the parameters in the consolidated budgets of the regions from a perspective of strategic development priorities. The relevance of this study stems from the need to improve the quality of budget planning and support for socio-economic development at the regional level, based on the strategic priorities of the constituent entities of the Russian Federation, in the context of decreasing inter-budget transfers and increasing debt and tax burden on the regional economies. Research methods include systemic, logical and statistical approaches, as well as considering the requirements of budgetary legislation, strategic planning documents, and the parameters of regional economic security. Based on the results of the study, the following conclusions were drawn: 1) An analysis of the forecast parameters for the socio-economic and budgetary development in the Republic of Bashkortostan for 2026–2028 was conducted. This made it possible to identify the lag of the region in a number of indicators compared to the average for Russia (nominal GRP growth rates, average monthly wages, labor productivity, capital productivity). The revenue side of the regional budget is formed based on the planned increase in the contribution of tax revenue, primarily due to an increase in household income taxes; 2) The main problems and risks of budgetary support for sustainable socio-economic development in the region are highlighted — the negative impact of external environmental factors, such as maintaining sanctions and slowing growth rates in the global economy; imbalance of supply and demand in the economy; personnel shortages; insufficient levels of budget expenditure on education, healthcare and culture, affecting the quality of the human potential in the territory, from the standpoint of economic security requirements; growth of the debt burden; environmental risks, etc.; 3) Recommendations were given to improve the balance of the parameters in the consolidated budget of the Republic of Bashkortostan in order to achieve the strategic priorities for its development. Conclusions: The implementation of the proposed recommendations would contribute to improving the balance of regional budget systems and achieving the strategic priorities for the socioeconomic development in the constituent entities of the Russian Federation.

The relevance of the study lies in the gradual regionalization of the entire world economy, where Russia has sufficient potential to improve its position on the international stage. This is possible, among other things, through increasing the level of innovation in the Russian economy. The purpose of this work is to test a hypothesis about the positive impact of the used instruments of the state tax policy regulation in order to increase the level of innovation of the Russian economy in the context of sanctions pressure and transformation of the country’s foreign economic relations within the global economy. The objective of this study is to analyze and identify the instruments of tax policy for state regulation in order to increase the level of innovation in the Russian economy. The main methods used in this study include the collection and processing of statistical data, their comparative analysis, study of regulatory framework for the fiscal policy on innovative development of the country, as well as other documents related on sustainable economic development. The scientific novelty of the research conducted consists in determining the relationship between the indicators of the innovativeness of the economy and measures of tax incentives for R & D. As a result of the research, proposals are made to improve the existing fiscal instruments in the Russian tax law to stimulate innovative development of the economy. A conclusion is drawn about the significant innovative contribution of tax preferences and the possibility of strengthening their role in the area under study. The practical significance of the work done consists in the possibility of using the research results to improve the effectiveness of implementing of state tax policy in relation to business in order to stimulate R & D expenditures, increase the production and consumption of domestically produced innovative products, and export high-tech products.

The subject of this study is the tax incentives that promote the intellectual transformation of Russian companies. The objective of the article is to assess the role of stimulating tax policy in ensuring the intellectual transformation of business. Research methods include qualitative analysis of tax incentives, correlation and regression analysis (including assessment of autocorrelation, multicollinearity, and heteroscedasticity), structural analysis, analysis of dynamic time series, tabular, and graphical methods of data visualization. The study conducted an inventory and systematization of tax incentives that promote the intellectual transformation of companies. Three groups of tax incentives were identified: (1) incentives aimed at supporting the infrastructure for the intellectual transformation of a company; (2) innovation incentives, and (3) investment-oriented tax incentives. Within the framework of the analysis of the theoretical aspects of the influence of tax incentives on the intellectual transformation of companies, four areas of such influence have been identified. The impact of tax incentives on the intellectual transformation of business through direct and indirect channels has been assessed. A positive indirect (peripheral) impact of taxes on digital transformation through the development of the information and telecommunication technology sector has been revealed, while the direct impact of fiscal incentives on business digitalization processes has not been proved statistically. The scientific novelty of this study lies in the development and testing of the author’s methodology for assessing the direct and indirect impact of tax incentives on the intellectual transformation of companies, based on the use of correlation and regression analysis.

The relevance of the study stems from the need to improve the accuracy of business sustainability forecasting in a highly turbulent economy. In this regard, the purpose of the research was to create a forecast for business sustainability using an example from the non-ferrous metallurgy industry using an advanced approach with a logit analysis of its financial prospects as a means of assessing key risks, and creating scenarios that could increase the accuracy of forecast estimates. The research methodology included principles, factors, indicators, models of sustainable development, empirical analysis and a risk-factor approach. The selection of factors and indicators for the model characterizing the multidimensionality in financial potential is based on an industry risk analysis, which includes the results of a study of the uncertainty of the business environment. Additionally, correlation analysis and assessment of the statistical significance of various factors were conducted. To build the model, data from 2014 to 2023 was downloaded from the SPARK information system, as well as public industry data. The constructed logit model allows us to assess the probability of the realization of key sustainability risks. The proposed assessment scale allows us to interpret the results as a basis for forecasting of the financial potential of non-ferrous metallurgy companies. The scientific novelty lies in improving the algorithm for forecasting business sustainability. This includes identifying risk factors, selecting indicators based on industry analysis, and developing logit models for financial potential. It also involves developing scenarios, that increase the reliability of forecasts of company sustainability over the short and medium terms. The practical value of the results lies in their potential use in research and development projects, as well as assessing and developing industry strategies at the Ministry of Industry and Trade, and by industry professional, investing funds for industrial development, and in generating reports on the sustainable development of socially and economically important enterprises.

In the context of Vietnam, as an emerging economy characterized by limited financial transparency, this study aims to clarify how the credit market responds to financial management behaviors. It also examines the roles of audit quality and listing status in this relationship. The topic holds both practical and academic significance, particularly in shaping policies related to credit risk control and enhancing financial market discipline. This paper investigates the impact of earnings management and corporate income tax avoidance on the cost of debt among firms listed on the Vietnamese stock exchange during the period from 2016 to 2024. A quantitative research approach is employed using panel data regression models with firm and year fixed effects. The primary independent variables include proxies for earnings management and tax avoidance, while the dependent variable is the cost of debt. Control variables such as profitability, firm size, financial leverage, and foreign ownership are also included to ensure robustness. Further analysis is conducted by dividing the sample based on audit firm type (Big4 vs. non-Big4) and listing status (listed vs. unlisted) to investigate the heterogeneity in audit quality and market visibility. The findings indicate that earnings management has a statistically significant negative impact on the cost of debt, particularly among firms audited by Big4 and listed companies. In contrast, the effect of tax avoidance on the cost of debt is positive but relatively weak and inconsistent across groups. These results underscore the crucial role of audit quality and financial transparency in shaping credit risk responses in emerging markets.

The article focuses on the study of issues related to assessing the business value of publicly traded companies using artificial intelligence. The purpose of the study is to develop a model for predicting the business value of publicly traded companies within the framework of a comparative approach. The relevance of this work is that in times of uncertainty, it can be difficult to justify the market value of the business of public companies due to the fact that historical transaction prices, which are used as the basic information for calculating market value in the framework of the capital market method, may not reflect the company’s future prospects. The scientific novelty of the research consists in developing a method for predicting the business value of publicly traded companies using the main section of artificial intelligence — machine learning. The authors used the following methods in their scientific research, including logical and statistical methods (correlation analysis) and machine learning techniques such as linear regression, decision tree, tree ensembles, and recurrent neural network. The developed method consists of six stages which integrate the main steps of machine learning with the classical stages of data cost estimation. Based on the results of testing the method, eleven models of extra-random decision trees have been developed. These Trees allow us to predict the direction of movement of industry indexes Moscow Exchange depending on exogenous and technical indicators. It can be concluded that the developed models have a high level of accuracy (based on the test data R2 of 0.99 and MAPE below 1%) of forecasting industry indices and the suitability of the method for solving the problem of predicting the share price of a single public company within the context of the capital market method. The prospect of further research relates to the development of predictive models for all public companies, taking into account their financial characteristics and behavioral factors. This article will be beneficial for practicing appraisers in their evaluation of businesses in this field and for investors.

The topic of financial fraud is often raised in various publications due to its significance. Increasing the level of financial literacy among the population is frequently suggested as a way to reduce the prevalence of financial fraud. However, there is a lack of research on the impact of financial literacy on financial fraud, and the studies that do exist are based only on logical arguments derived from economic theory. The purpose of this article is to examine the impact of financial literacy on financial fraud in Russia. We used data from the Ministry of Internal Affairs on crime rates in the country, as well as estimates of financial literacy levels among Russians published by NAFI (National Agency for Financial Research) between 2008 and 2023. Given the ongoing link between financial fraud and the use of cash in money laundering the database of analyzed parameters includes data from the Central Bank of Russia on the dynamics of cash inflows. The study used correlation analyses. The article suggests that financial literacy has limited usefulness in protecting the population from financial fraud. The strong positive correlation between the number of fraud cases and the average level of financial literacy suggests that, as people acquire certain financial knowledge, they become more interested in various financial products and are more likely to fall victim to financial fraud. While financial knowledge alone may not be enough to deter fraudsters who exploit the trust of citizens, increased efforts to develop behavioral skills among the public, such as through the “Hang Up the Phone” campaign, seem to be a promising approach to strengthening the population’s ability to protect themselves against financial fraud. However, a more effective approach would be to strengthen the financial system’s protective measures, particularly for banks, in order to identify and halt suspicious transactions of customers who may have fallen victim to fraud.

The aim of this study is to determine the financial performance of the corporate sector employing the integrated SOWIA-ELECTRE III method. In this framework, the data of 10 real sectors operating in Borsa Istanbul over the period 2016–2022 are utilized. It was observed that the financial performance indicators affecting the sector performance varied over the years and that current liability rate, price to earning ratio, firm value/EBITA and return on equity ratios were important determinants of financial performance. According to the results of the performance rankings of the sectors obtained by the ELECTRE III method, it is understood that the highest performance was realized by retail trade in 2017, 2018, 2019, 2021 and 2022, construction and public works in 2016 and food, beverage and tobacco in 2020. In addition, the study compared sector performance rankings with sector index return rankings and the degree of the relationship was determined by the Spearman’s rank correlation coefficient. Accordingly, the correlation coefficients are positive, high and significant in 2017 and 2018. Accordingly, it can be said that there is a partial relationship between sector performances and sector returns. The study results show that portfolio managers and investors should give importance to financial performance analysis when making sector analysis, and economic managers that general economic conditions are important determinants in the development of sectors.

All the Russian commercial banks, which have any types of license, whether basic or universal, must meet the mandatory standards set by the Bank of Russia. Otherwise they may face the risk of having their license revoked. The problem raised by the study relates to the question of whether it is possible for the Bank of Russia to strengthen its control over default factors in commercial banks through economic regulatory measures, such as monitoring compliance with banking regulations. The purpose of this work is to identify factors that influence the probability of license revocation for commercial banks in Russia during a period of relative stability in the banking system between 2016 and 2021. Special attention is paid to the reasons for the revocation of licenses and the analysis of factors related to compliance by commercial banks with basic standards of banking activity. The following methods were used: analysis of the reasons for the revocation of banking licenses, division of 244 banks that lost their licenses into two groups: those with license revoked for economic reasons, and those in connection with violations of legislation. A multinomial logistic regression was used to analyze the impact of banking regulations’ value on the probability of license revocation. The econometric analysis showed that factors influencing the license revocations of Russian commercial banks, including those belonging to both groups considered, vary significantly. Not all indicators related to regulations and the probability of license revocation proved to be significant in this sample. Lowering the capital adequacy ratio significantly increases the risk of license revocation due to economic reasons. An increase in the maximum value of large credit risk also increases the likelihood of license withdrawal, regardless of reason.

The study focuses on Iran’s monetary and financial challenges between 2018 and 2025, which are caused by a complex combination of external and internal factors that have impacted the country’s economic situation. External factors, such as sanctions imposed on Iran, have restricted its access to global capital markets and contributed to the country’s financial difficulties. Internal factors like the specific functioning of the banking system, institutional limitations, and monetary policy decisions, including the use of multiple exchange rates, also contribute to these challenges. The purpose of this study is to investigate the role of both external and internal factors in the emergence and evolution of Iran’s monetary and financial challenges between 2018 and 2025. We employ methods of comparative and structural analysis as well as statistical analysis of macroeconomic data sourced from official government reports. Through our analysis of these economic issues, we have been able to draw the following conclusions. Firstly, international sanctions, restrictions on oil exports, the disconnection of the banking sector from global payment systems, and the blocking of assets have significantly reduced the space for maintaining macroeconomic stability and weakened the stability of the national currency. Secondly, internal imbalances, including inefficient currency regulation, vulnerable banking systems, high levels of problematic assets, and limited independence of financial institutions, have increased the impact of external shocks and contributed to the formation of persistent inflation and reduced confidence in the Rial. Monetary and financial instability in Iran is caused by external restrictions imposed on internal institutional and structural vulnerabilities. To maintain macroeconomic stability in modern times, it is essential to adapt to external challenges while also implementing consistent institutional changes that affect monetary policy, the transparency and competitiveness of the foreign exchange market, and the organization of the banking sector. The results of this study have practical value, as they provide a systematic approach to understanding the dynamics of monetary aggregates, inflation, and exchange rates in Iran. By identifying the relationships between external and internal factors that contribute to monetary and financial instability, we can develop solutions to improve the country’s financial situation and conduct comparative and applied research in global finance.

The subject of this study is the financial aspects of international industrial cooperation. The aim of the work is to identify the motivations of foreign companies to engage in production activities in the Russian Federation and develop proposals to improve its economic efficiency. The research methodology includes the use of theories of international economic cooperation, as well as empirical-statistical and qualitative analysis. The study found that countries with large and solvent markets, such as China and Russia, are attractive to foreign direct investment (FDI). Multinational enterprises (MNEs)operating in these countries often use more advanced production technologies than they would in other countries. As a result, the rate and amount of profit from producing goods in these countries is typically higher than exporting the same goods from the manufacturing country. The paper argues that these circumstances may override MNEs’ desire to maintain control over imported technologies if the authorities of the FDI host country insist on partnership with a local company in the enterprise established by the MNE. A condition of such partnership should be the obligation of the MNE to transfer its technology used in production to the local company, with the right for the latter to freely use and further develop it. Although such a requirement did not exist for foreign companies in the Russian Federation previously, the study suggests that foreign MNEs are likely to consider this exchange acceptable and beneficial. Establishing a condition for foreign MNEs to carry out production activities in the Russian Federation in partnership with local businesses would allow Russian companies to more quickly adopt new technologies. This would contribute to enhancing the efficiency of the Russian economy. Additionally, society would benefit from higher-quality products that are created with the participation of local capital, meeting the demands of consumers.

The relevance of the study is determined by the fact that in the context of the transformation of the international monetary system and the pressure of sanctions, Russia faces the need to take a proactive position in terms of ensuring the sovereign nature of its national financial and monetary systems. In this context, a team of researchers from the Institute of Innovative Financial Instruments and Technologies at the Plekhanov Russian University of Economics have developed a model for the creation of an investment (reserve) contour for the national financial system, based on the use of multi-commodity and multi-currency price stability indices, while the check of the degree of stability to the external environment and the possibility of practical application of this model is the purpose of the study in question. The methodology of stress testing of risk factors accompanying the functioning of the model was chosen as the basis for the evidence base. To implement the stress testing procedure, the cognitive modeling apparatus was used, which is capable of dealing with weakly formalized situations and expert-based parameters within its interdisciplinarity framework. Based on the generated list of control factors, a cognitive model was created in matrix and graph forms. An analysis of its structural stability and resistance to disturbances was conducted. The main hypothesis of this study is the ability of the proposed model for this issue, circulation and redemption of financial instruments secured by raw materials, currencies of friendly countries and other assets to overcome the main stresses (risks) generated by the control factors selected by the authors. This hypothesis was tested using a scenario approach. Within the framework of this approach, a number of scenarios were tested that corresponded to risk groups associated with the stages of the functioning of financial instruments in the investment (reserve) circuit. The substantive formulation of scenarios and their implementation using the impulse model have allowed us to obtain results in the context of three options for the development of situations. These results have substantiated the stability of the optimistic and basic behavior under stress tests, and confirmed the practical suitability of the developed approach to forming the non-emission (reserve) contour of the national financial system.

The relevance of the research topic lies in the fact that the demand for goods and services plays a significant role in determining the efficiency and financial stability of companies. It is not enough for a company to simply produce a product. Instead, it is essential to create a customer base in order to sell the product. The purpose of this study is to systematically organize and expand methods of product promotion through theoretical justification and analysis of factors that influence key financial and economic indicators of companies. Based on the set goals, the following research objectives have been identified: analyzing the dynamics and assessing the financial condition of domestic companies, evaluating the business activity and product promotion efficiency of these companies, developing methods for managing company’s accounts receivable; and formulating and implementing a product promotion strategy. In the process of solving research problems and achieving objectives, general scientific methods such as generalization and synthesis, comparison, dynamic analysis, calculation of average values, economic efficiency analysis, trend analysis, factor analysis, coefficient methods, matrix methods, and modeling were employed. The results of the study include the calculation of the duration of the production, operating and financial cycles for the period 2016–2023. A significant conclusion was made regarding a sharp increase in the length of the operating and financial cycles, which is attributed to an advanced increase in the accounts receivable turnover period compared to accounts payable. Based on trend analysis, it is predicted that the length of the financial cycle will reach 39 days by 2027. In order to understand the reasons behind the decline in business activity among Russian companies, a factor analysis has been conducted to examine changes in the length of the financial and operational cycles from 2016 to 2023. We also assessed the economic impact of these changes on the length of the financial cycle. However, the food industry has accumulated best practices for creating and implementing credit policies, which has resulted in the reduction in the duration of the financial cycle from 2017 to 2023, with the cycle reaching 6 days by the end of the period. An algorithm for optimizing strategies has been proposed, which involves choosing the promotion strategy that maximizes the return on investment. This article was prepared based on the results of research conducted using budgetary funds under the state assignment of the Financial University.

The question of the optimal capital structure existence has been a controversial field for scientists for more than 70 years. The development of capital structure theories has prompted scientists to analyze the factors that influence the decision-making on the equity/debt ratio. The applied methods of capital structure management depend on the goals of the company’s management and may include ensuring financial stability, profit maximization or ensuring the return on invested capital. At the same time, managerial decision-making regarding the capital structure is based, as a rule, on informal assessments due to the lack of specific tools that allow for making scientifically sound decisions in this area. The purpose of the study is to develop a formalized approach to capital structure management by varying lag determinants. A three-factor lag model allows us to determine the corporate capital structure based on the increment of three determinants — return on sales, resource efficiency, and equity multiplier. A five-factor lag model takes into account, in addition to the above, the costs of debt and taxes. The choice of a model for capital structure is based on the availability and objectivity of information for calculation. At the same time, both three-factor and five-factor lag models produce a very similar capital structure for the metallurgical industry. As calculations have shown, the difference in modeling arises due to an increase in the return on sales (ΔROS) and an interest burden (ΔIb). Moreover, if the increase in the return on sales exceeds ΔIb, then the share of equity capital will rise. In order to improve the quality of management decisions regarding the capital structure, it is advisable to carry out forecasting using two models, and in practical activity the obtained results should be used as a guideline for possible changes in the total capital structure. The empirical basis of the study was the reporting and forecast data from the largest companies of the metallurgical industry in the Russian Federation over 2019–2023.

The concept of stochastic order between random variables has been formed and developed in science since the middle of the 20th century. However, it was only in the last decade that these concepts began to penetrate into risk management applications and into the actuarial field. This has made it possible for them to become an actively developing area, allowing us to compare the risk factors themselves, as well as the level of hazards (risks) associated with them. The purpose of this work is to develop recommendations for solving the problem of comparing various risks and to propose methods for comparing risks with different degrees of catastrophicity. The relations of stochastic and dispersion orders in a set of risks are investigated. As a result, a study of these orders is carried out using risk measures VaR, as well as risk measures VaR^{(t )} (VaR to the power of t), introduced into scientific use in recent years. The description of these orders is analyzed using the stop loss method of risk transformation, as well as the danger rate method. In addition, in this study, for well-known examples of loss distributions are given that find wide application in risk management and actuarial science. Simple methods are obtained to allow one to compare risks under these distributions, which are expressed through the parameters of these distributions. The results and methods presented in this work may be of interest to both practitioners and researchers involved in the problems of risk management and the actuarial fields.

The research aims to investigate the impact of investment behavior and risk appetite on investment decision-making for rural investors, with frequent analysis of the demographic characteristics of rural investors. The research was based on a cross-sectional research design in which the data was collected from the rural areas of Haryana and Punjab; 486 individual investors’ data was collected using structured questionnaires from all 22 districts of Haryana and seven districts of Punjab. Frequency analysis of the demographic characteristics has been performed using SPSS version 26. For testing the reliability and validity of the questionnaire, the Cronbach alpha test, Composite reliability, and Discriminant validity and hypothesis testing have been done using Structural Equation Modelling [SEM] with Smart PLS 4. The results of the study reveal that investment behavior has a significant impact on investment decision-making. This implies that rural investors make decisions based on their behavioral aspects, i. e., needs, objectives, the history of particular assets. The results also show that risk appetite does not significantly affect the decision-making process of rural investors, implying that regardless of its level, it is not the major factor in investment decision-making.

This study integrated two theories: the Theory of Planned Behavior (TPB) and the AIDA (Attention Interest Desire Action) model, to understand interest in using cashless fintech and to assess the impact of marketing communication on consumer behavior. The study included culture as a factor believed to influence the intention to use cashless fintech. For the AIDA model, only the variables attention, interest, and desire were used, excluding action, as the study focused on consumer interest rather than the decision-making to use cashless fintech. The conceptual model and hypotheses combine key constructs from both models to predict behavioral intentions. This quantitative study involves residents of Ambon City and used Partial Least Square (PLS) analysis, a structural equation modeling (SEM) technique, to estimate the simultaneous effects between variables. The results revealed that first, integrating the AIDA model and TPB does not show AIDA as a stimulus for increased interest in fintech usage, with attention, interest, and desire negatively impacting behavior intention. Second, TPB, through its three constructs: attitude towards behavior, subjective norm, and perceived behavioral control, successfully explained fintech interest, and culture was found to have a significant influence on behavioral intention.

This study examines the economic and geopolitical ramifications of the ongoing Russia-Ukraine conflict on Russia and the global economy. It conducts a comparative analysis of selected macroeconomic and financial indicators across the pre-conflict (2005–2013) and during-conflict (2014–2022) periods. The objective is to determine whether significant differences exist in the mean values of key variables across the two phases. The study employs ratio analysis, descriptive statistics, the Shapiro-Wilk test, Wilcoxon matched-pairs signed-rank test, and t-tests. Methodologically, the two-period framework enables comparison of means, medians, and ratios, representing a key analytical contribution. The results indicate significant differences in oil rents and foreign direct investment (FDI) between the two periods, with higher average levels in the pre-conflict phase. In contrast, unemployment rates are lower during the conflict period compared to the pre-conflict period. These findings suggest structural shifts in Russia’s macroeconomic performance amid geopolitical tensions, sanctions, the 2014 conflict escalation, the COVID‑19 pandemic, and the 2022 special military operation. The study concludes that while oil rents and FDI declined during the conflict period, the Russian economy exhibited relative labor market resilience despite Western sanctions. It recommends future research applying regression analysis to further examine the impact of oil rents, FDI, and unemployment on economic growth under conditions of conflict and instability.