The author examines how monetary and fiscal policy influences the shocks facilities in the Russian economy caused by the coronavirus pandemic. The article aims to provide an economic assessment of the monetary measures by the Central Bank and the Government of the Russian Federation to overcome the consequences of the COVID-19 crisis. The author exploited the methods of content analysis, benchmarking, and logical analysis. The study covers the period of March — July 2020 and relies on the analysis of data from international organizations, analytical centers, mass media, official data sources of the Government of Russia and the Central Bank of the Russian Federation. The literature review and the analysis of the Mundell-Fleming model contribute to the better understanding of monetary policy of countries in its connection with fiscal policy. The author analyzed the monetary and fiscal measures against the COVID-19 crisis in Russia and other countries. The study provides the assessment of the COVID-19 shocks and the remedial actions. The conclusion is that when most economic activity is prohibited, lower interest rates cannot stimulate it in the short term. More visible are the efforts to maintain liquidity in the economy, as financial institutions often have troubles. During the analysis, the work focuses on the theoretical foundations of monetary policy and its connection with fiscal policy, as well as provides a number of stylized facts of its implementation in Russia during the coronavirus pandemic. This can be useful for further empirical research and practical recommendations in the field of monetary and fiscal policy in the Russian Federation.

The authors analyze the trends and patterns for reproducing investment potential of institutional sectors. This is relevant for the economic and financial security of territorial systems. The aim of the study is to design a scenario model for reproducing investment potential of institutional sectors at the regional level. This model suggests systems of predictive scenarios for the reproduction and choosing the optimal one to achieve positive dynamics of the socio-economic development of the regions. When designing the scenario model, the authors used statistical methods for data collecting and processing, regression analysis with the least squares method and ARIMA forecasting. The authors developed an algorithm of scenario modelling for reproducing investment potential of institutional sectors in regional systems. The authors designed a balance model for financial flows between them for various investment instruments. They analysed the regularities of reproducing their investment potential. The paper presents an econometric analysis of financial flows among the sectors considering the impact factors, and the basic scenarios of reproducing their investment potential. The work reveals a stable trend of the outflow of investment resources in institutional sectors accumulated by the banking sector abroad during periods of economic downturns and the development of financial and economic crises. The study suggests a model allowing to determine the most likely forecast scenarios for reproducing investment potential of institutional sectors: inertial, extremely negative (pessimistic) and the most favorable (optimistic). The authors conclude that an increase in volatility in financial markets, a weakening of the domestic currency, and an increase in negative trends in economic development significantly increase the likelihood of a pessimistic scenario. To prevent this, the Central Bank of the Russian Federation, must change its policy of regulating the financial and economic activities of the banking sector: to limit the speculative activities of credit institutions that facilitate the withdrawal of financial resources from the domestic economy, to support investment programs for developing of enterprises of the real sector. The prospect for further research is building a system of mechanisms for transiting to the implementation of the optimal scenario of reproducing investment potential of institutional sectors, ensuring the restoration and progressive socio-economic development of territorial systems.

Microfinance is a way to fight poverty, and therefore is of high social significance. The microfinance sector in Russia is progressing. However, the engagement of microfinance organizations in illegal financial transactions associated with fraud, illegal creditors, money laundering, significantly limits their potential and has negative impact on their development. The aim of the paper is to study the possibilities to automate detection of unscrupulous microfinance organizations based on machine learning methods in order to promptly identify and suppress illegal activities by regulatory authorities. The author cites common fraudulent schemes involving microfinance organizations, including a scheme for cashing out maternity capital, a fraudulent lending scheme against real estate. The author carried out a comparative analysis of the results obtained by classification methods — the logistic regression method, decision trees (algorithms of two-class decision forest, Adaboost), support vector machine (algorithm of two-class support vector machine), neural network methods (algorithm of two-class neural network), Bayesian networks (algorithm of two-class Bayes network). The two-class support vector machine provided the most accurate results. The author analysed the data on microfinance institutions published by the Bank of Russia, the MFOs themselves, and banki.ru. The author concludes that the research results can be of further use by the Bank of Russia and Rosfinmonitoring to automate detection of unscrupulous microfinance organizations.

The authors investigate the risks of computer attacks on automated banking systems. The relevance of the study is due to the need to revise the approaches to risk assessment based on the technical components of banking business processes and the consequences of cyber-attacks aimed at banking automated systems in credit institutions. The aim of the study is to describe the developed methods for assessing cyber risks in a commercial bank and provide an option for assessing the risks of information security violations in electronic banking technologies. The methodology of the article includes the analysis of domestic and foreign literature on the research topic, the theoretical and probabilistic method of calculation, computer programming and graphic interpretation of information. The authors analysed the operational risk of a commercial bank to develop components of the operational risk management system in the context of developing electronic banking technologies. They designed a computer program to quantify risk probabilities of cyberattacks on electronic banking technologies (by means of Borland Delphi). The work presents a formalised probabilistic model for determining the most vulnerable segment of risk management techniques used by information security structures. The conclusion is that it is possible to develop a software package based on a mathematical model that reduces the number of checks of risk factors by several times. The research results may be of further use for the development of risk divisions in credit institutions using electronic banking technologies.

The problem of fiscal dominance tends to be most pronounced in emerging markets. The research subject is the monetary policy of the Central Bank of the Republic of Armenia and its participation in solving fiscal problems. The aim of the article is to analyze and assess fiscal dominance in the macroeconomic regulation of Armenia. The methodological basis of the study is a review of theoretical and practical models of fiscal dominance known in the scientific literature, as well as applying the most optimal models to the Armenian economy. The authors conclude that the tasks of fiscal policy are the priority of macroeconomic management, and monetary policy aims to solve fiscal problems.

According to Bank of Russia Regulation No. 590-P dated June 28, 2017, Russian banks assess credit risk and make loss provisions for potential loans. Since 01.01.2018, credit institutions have been required to create loss provisions for expected losses in accordance with international standards (IFRS 9). This novation seems relevant due to the lack of a common risk assessment method and the importance of cost optimization on loan provisions. The aim of the study is to improve the credit risk assessment method for making loss provisions for potential loans. The author used the methods of system and logical analysis and synthesis, techniques of high financial calculations, the balance method, the method of financial ratios. When estimating the probability of borrowers’ default, potential credit losses and loan provisions, the author applied actuarial, market, statistical and econometric methods. Based on a Russian bank’s sample data for 2012-2019, the author developed a regression model that establishes the relationship between financial ratios and the default of corporate borrowers — agricultural producers, and checked the significance of the model’s financial ratios. The author divided the borrowers into rating groups by score. The probability of default is the ratio of the number of defaults to the number of borrowers by group. The average default loss for each group depends on the collection / debt ratio in the bank under review. The score of a borrower brings them into a certain rating group, helps calculate the probability of a default and losses in case of default. The calculated expected losses may be of further use when determining loss provisions for potential loans. The author concludes that this method allows assessing risks and making a decision on lending to borrowers — agricultural producers. The expected credit loss approach will allow for more reasonable provisioning, which corresponds to other authors’ findings. Applying this method in a particular bank requires considering the specifics of the composition and structure of the loan portfolio. It is necessary to analyze the impact of the expected credit loss method on the profitability of banks.

Distortion risk measures have been popular in financial and insurance applications in recent years due to their attractive properties. The aim of the article is to investigate whether risk measures “VaR in the power of t”, introduced by the author, belong to the class of distortion risk measures, as well as to describe the corresponding distortion functions. The author introduces a new class of risk measures “ES to the power of t” and investigates whether it belongs to distortion risk measures, and also describes the corresponding distortion functions. The author used the composite method to design new distortion functions and corresponding distortion risk measures, to prove that risk measures “VaR to the power of t” and “ES to the power of t” belong to the class of distortion risk measures. The paper presents examples to illustrate the relevant concepts and results that show the importance of risk measures “VaR to the power of t” and “ES to the power of t” as subsets of distortion risk measures that allow identifying various financial catastrophic risks. The author concludes that risk measures “VaR to the power of t” and “ES to the power of t” can be used in risk management of companies when assessing remote, highly catastrophic risks.

The aim of the article is to study the impact of tax and tariff policy on the financial balance of the compulsory pension insurance system in Russia, as well as to substantiate proposals for its financial stabilization. The authors analyzed the consequences of regression applied on wages while forming tariffs for pensions. The methods used in this study were economic, statistical and empirical methods, analysis and synthesis, abstraction, systemic-structural approach. The authors analyzed the influence of preferential tariffs for certain types of economic activity and the use of simplified tax systems for organizations on the income of the Pension Fund of the Russian Federation. The work contains the calculation of income shortfalls in the compulsory pension insurance system resulting from the use of regression and tax benefits when calculating insurance payments to the budget of the Pension Fund of Russia. The authors estimated the financial consequences of the pension valorization in the Soviet period and the pension indexation policy in Russia resulted in the rising costs of the Pension Fund of Russia. The conclusion is that the current procedure for determining insurance contributions to the Pension Fund of the Russian Federation, which provides for a large number of benefits, does not correspond to generally accepted world practice and creates major risks for the financial balance of the pension system. This may cause increasing poverty among seniors. Raising the retirement age did not solve the problem of balancing the pension system, but exacerbated it. The regression in the payment of insurance premiums led to a conundrum in Russia, when an increase in wages resulted in the decrease of the Pension Fund of the Russian Federation’s income. This is associated with the precarization of wages and the desire of business to minimize tax payments. The prospect of further research is to study the conditions for financial stabilization of compulsory pension insurance during the Russian economic crisis. The analysis showed that there is a need to create an independent actuarial center for setting tariffs for deductions to the Pension Fund of the Russian Federation, as well as the redistribution of areas of responsibility between the Pension Fund of the Russian Federation and the Ministry of Finance of Russia.

The paper discusses an integrated research of implementing internal state financial control by the Federal Treasury. The aim of the study is to show the organization and stages (algorithm) of implementing internal state financial control, to identify problems and possible solutions. The relevance of the study determines the modern development of financial control, aimed at automation and digitalization. Scientific novelty is in systematizing problems of financial control and finding new solutions. The author uses methods of analysis, synthesis, induction, deduction, scientific abstraction, logical thinking, the dialectical method of cognition and observation. The study results in describing an algorithm for internal state financial control by the Treasury of Russia, and identifies problems (weaknesses) related to the planning and implementation of control measures in the financial and budgetary sphere, as well as possible solutions. The author points out the need to revise the procedures for implementing internal state financial control and its new forms with the current methods of financial control. The study suggests such a new form of financial control as automated remote financial monitoring, which warns on the impermissibility of violations in the financial and budgetary sphere. The author concludes that in order to automate and digitalize internal state financial control, it is necessary to create a unified information base, including systematized information according to the criteria set by the state. This will allow for a deeper economic analysis of using budgetary funds allocated by the state for certain purposes, at the stages of preliminary and subsequent control, that will improve and increase the efficiency of financial control, and save time and labor during control activities. The author recommends to improve the regulatory framework governing the implementation of financial control by the Russian Treasury, including internal state financial control.

The article discusses the nature of stablecoins and their specifics in the financial market. The aim of the article is to reveal the economic nature and characteristics of various types of stablecoins. The author used system-functional and system-structural research methods as well as methods of statistical analysis and synthesis. The paper analyses different approaches to the interpretation of stablecoins and their regulation in developed countries, as well as provides the author’s interpretation and classification of stablecoins. The article analyses the main indicators of stablecoins and identifies the potential benefits and risks associated with payment. The conclusion is that stablecoins are to be interpreted as a new hybrid type of digital financial assets. Stablecoins are not homogeneous and may have different economic and legal characteristics. Clearly identified blockchain-based issuers issue most stablecoins as tradable digital bonds or depository receipts that can be used as a means of exchange, savings, and payment. The major economic and functional criteria for the classification of stablecoins are: the form of collateral, the category of users, and the scale of circulation. The research has shown that currently the most widely used are centralized stablecoins, backed by fiat currencies and gold, used for exchange transactions and retail payments. Local stablecoins are primarily a store of value and a medium of exchange. Their widespread use can significantly affect the development of the crypto-asset market by increasing its liquidity and stimulating the development of more stable forms of digital financial assets. Global stablecoins may gain widespread use as a cross-border means of payment. They can increase the speed of crossborder settlements and reduce their costs, as well as provide wider financial inclusion for users without bank accounts. To realize the potential benefits of stablecoins, one should address the legal, regulatory and supervisory challenges associated with national and cross-border circulation of stablecoins.

The relevance of the study is due to the growing influence of external factors on the structure of cross-border capital flows associated with Russia. The aim of the study is to identify the main changes in the internal and geographical structure of international capital flows in Russia, trace their connection with the state economic policy and make practical proposals for improving their internal and geographical structure in Russia. The author uses statistical methods related to the calculation of individual indicators and the analysis of statistical data, the study of international experience. The analysis of the calculated structure of flows and stocks of foreign investment in 2007-2019 proves that the internal structure had an increase in the importance of direct investments in the composition of liabilities and a decrease in the role of reserve assets in the composition of assets. Offshore and related jurisdictions dominate in the geographic structure of direct investment, while the structure of reserve assets has shifted from the United States to Asian countries (China and Japan). International experience indicates the development of new approaches to the regulation of international capital flows, including measures of macroprudential policy. The author made a conclusion about the ineffectiveness of the current economic policy in regulating the internal and geographical structure of cross-border capital flows in Russia and about the prevailing influence of administrative measures by the external players. To improve the structure of international capital flows in Russia, the author suggests using separate currency restrictions, macroprudential policy measures, deoffshorization policy, as well as targeted insurance of external risks for Russian investors.

The author examines long-term changes in economic inequality in the global economy. The aim of the article is to update, analyze and systematize the long-term causes of changes in economic inequality in the global economy and identify its country specifics. The author used the methods of analysis and synthesis, systematization, classification and categorization of information from various scientific and statistical sources and databases. To illustrate the trends in economic inequality, the author applied the indicator of the share of national income among different groups of the population. The study revealed the cyclical nature of economic inequality in accordance with Kondratieff innovation waves lasting 50-60 years. Based on the data analysis of economic inequality for the period 1900-2018, the author concluded that technological progress is the priority factor in changing economic inequality. Together with the country specifics of the financial mechanism for redistributing income and wealth and various regimes of international cooperation and trade, it affects the changes in cross-country and domestic economic inequality. Understanding the nature of changes in inequality will allow for effective long-term strategies for economic development and the corresponding state regulation policy in the context of faster digitalization and robotization of the global economy.