Alina Yefimenko

Type of the article: Theoretical ArticleAbstractNational cybersecurity opens new opportunities for digital transformation and helps counter the growing threat of cyberattacks. The purpose of this study is to develop a methodology and identify the most influential predictors of national cybersecurity in global competitiveness, utilizing the data mining approach. To assess the impact of cybersecurity characteristics, modern machine learning methods were implemented in the Salford Predictive Modeler software environment, including Classification and Regression Trees, Random Forest, Stochastic Gradient Boosting, Multivariate Adaptive Regression Splines, Generalized Path Seeker, and classical regression. Data mining was conducted using the World Competitiveness Ranking (WCR) indicators, constructed by the Institute for Management Development, and the National Cybersecurity Index (NCSI), constructed by the e-Governance Academy, for 64 countries as of 2024. Three groups of countries were identified with different predicted levels of competitiveness, underscoring the importance of balancing the development of both external and internal components of cyber defense. The empirical results demonstrate that countries with strong cybersecurity management capabilities achieve higher competitive positions, even with limited participation in global cyber initiatives. At the same time, active global involvement without sufficient internal readiness does not create sustainable competitive advantages. The regression tree provided a transparent allocation of key subfactors, with global cybersecurity contribution and cybersecurity management playing leading roles. The significance of the study lies in shaping methodology and state policy in cybersecurity, human resource development, regulatory framework enhancement, and digital ecosystem strengthening.AcknowledgmentsThe paper is prepared within the scientific research projects “Digital transformations to ensure civil protection and post-war economic recovery in the face of environmental and social challenges” (№0124U000549) and “Drivers and barriers to human capital transformation for a circular and green economy” (No. 0126U001080).

In the context of Ukraine’s ongoing digital transformation and persistent governance challenges, understanding the role of digitalisation in combating corruption is both timely and essential. As the country intensifies efforts to modernise its public sector and attract international support, digital tools have emerged as critical instruments for enhancing transparency and institutional accountability. This study aims to assess the impact of digitalisation and technological development on corruption processes in Ukraine between 2005 and 2023. The analysis is based on data from the World Bank and the State Statistics Service of Ukraine. Using structural equation modelling and principal component analysis, the study constructs latent indicators for corruption, digitalisation, and technological development, and explores the relationships among these factors through a system of structural equations. Data were standardised, normalised, and tested for robustness and model adequacy using various statistical criteria. The findings reveal a strong inverse relationship between digitalisation and corruption: a one-unit increase in digitalisation reduces the corruption index by 0.646 units. Technological development indirectly contributes to corruption reduction by enhancing digital capacity, with a 1% rise in technological indicators leading to a 0.263-unit increase in digitalisation. Key drivers include ICT infrastructure, research and development expenditure, and innovation activity among enterprises. The model confirms that digital reforms in Ukraine are not only effective in curbing corruption but are also statistically sound and policy-relevant, reinforcing the importance of continued investment in digital governance as a core anti-corruption strategy.

Corruption remains one of the most serious problems that hinders economic development, undermines trust in state institutions, and worsens the quality of life of citizens. In today’s digital transformation, innovative technologies such as artificial intelligence, blockchain, and automation of management processes are becoming key tools in the fight against corruption. The purpose of the study is to assess the impact of innovative and technological factors on curbing corruption in the country. The calculations are based on the World Bank data for Denmark, Finland, Singapore, New Zealand, Sweden, Ukraine, Albania, Serbia, Romania, Moldova, and Hungary for the period from 2017 to 2023. Using canonical analysis and a correlation matrix, the article confirms the hypothesis that innovation and technological determinants influence the reduction of corruption. A close relationship is found between the Global Innovation Index (according to the World Intellectual Property Organisation) and Control of Corruption (according to the World Bank), Corruption Perceptions Index (according to Transparency International), Rule of Law (according to the World Bank) and Regulatory Quality (World Bank). There is also a moderate relationship between High-Tech Exports (according to the World Bank) and Rule of Law, High-Tech Exports and Control of Corruption, High-Tech Exports and Corruption Perceptions Index, High-Tech Exports and Regulatory Quality. It was found that 84.7% of the variation in corruption indicators is explained by innovation and technology factors. The canonical coefficient is 0.929, which indicates a strong direct relationship between the groups of variables under study. It is determined that Regulatory Quality has the greatest direct impact on corruption processes. Based on the analysis, the authors suggest areas of innovative and technological changes to combat corruption, including processing large amounts of data, detecting anomalies and patterns, machine learning for risk prediction, preventive anti-corruption measures, and reducing the human factor in public administration. The results of the study can serve as a basis for developing anti-corruption strategies at the national and international levels, in particular through the introduction of digital technologies in public administration.

Bank capitalization is a key factor in the banking system’s resilience to economic shocks, as outlined in the Basel Accords on banking regulation. The paper aims to empirically evaluate the connection between bank capitalization and the socio-economic development level. The study uses World Bank data across 34 European countries of varying income levels (high, upper-middle, and lower-middle) for the years 2010, 2015, and 2020 as periods of financial and socio-economic turbulence. The study applies principal component analysis and correlation methods to identify relevant indicators. Countries were grouped using hierarchical clustering and K-means clustering methods. The results of the variance analysis revealed that only two indicators of bank capitalization – the share of non-performing loans and return on assets, and three socio-economic indicators – the Gini index, inflation, and unemployment, were statistically significant. As a result of both qualitative and quantitative changes between clusters, countries were reallocated from four clusters in 2010 and 2015 to three clusters by 2020: high-income countries, including Austria, Belgium, Denmark, Ireland, Iceland, Latvia, and others, consolidated into a single stable cluster (Cluster 3) in terms of both bank capitalization and socio-economic development. The primary drivers of inter-cluster movements were the positive dynamics of non-performing loans and bank assets, superior bank capitalization ratios, and improvements in inflation and unemployment levels. Based on the study’s findings, a matrix of transformational sustainability among European countries has been developed. The analysis confirms a relationship between the components of the chain: “level of bank capitalization – level of socio-economic development”.

A well-capitalised bank system is a key element for securing macroeconomic stability. By applying a comprehensive approach to managing the capitalisation of banks, policymakers, regulators, and financial institutions can strengthen the resistance of the financial system, reduce system risks, and contribute to macroeconomic stability. The goal of the research is to develop an international functional benchmarking model for managing bank capital in the context of securing macroeconomic stability for 34 European countries with different population income levels from 2010 to 2022 based on World Bank data. The aim is achieved through the implementation of the defined stages of benchmarking modelling.The international functional benchmarking model for bank capital management in the context of macroeconomic stability has been developed by defining the qualitative and quantitative characteristics of the leading countries, chosen based on the corresponding ranking. The three groups of benchmarks are identified: institutional and innovative approaches (based on Swiss and Luxembourg practices), monetary and credit approaches (based on Sweden and Iceland’s practices), and preventive and regulatory approaches (based on Norway and Finland’s practices).The research results can be used in the processes of a bank’s risk management and formation and regulation of capital adequacy by bank management, as well as when developing state socioeconomic and financial policies.

Corruption and the shadow economy are among the most pressing issues facing European countries. These phenomena significantly impact the socio-economic development, political stability, and legal systems of states. The purpose of the paper is to analyze the trends of corruption and the shadow economy in 34 European countries over the period from 2010 to 2022. The research employed tools such as grouping, comparison and generalization methods, time series analysis, and descriptive statistics calculations. Calculations were based on World Bank data using StataSE 18 software. Analyzing the standard deviation, minimum, and maximum values of corruption and shadow economy indicators identifies the most variable indicators: the indicator of primary government expenditures as initially approved budgets and the corruption perception index. It was found that despite the implementation of numerous anti-corruption reforms and regulatory measures, countries such as Albania, Moldova, Ukraine, and Bulgaria continue to face high levels of corruption, as evidenced by their low corruption perception index levels. The main reasons for this included weak enforcement mechanisms, gaps in accountability, and low levels of transparency in public administration. The least corrupt European countries were Denmark, Norway, Finland, Switzerland, and Sweden. This research observed high levels of the shadow economy in Ukraine, Cyprus, and Moldova, while Denmark, Norway, and Sweden demonstrated the lowest levels. The results of the study can be used to develop organisational and economic measures to combat corruption and the shadow economy by public authorities, business entities and other economic agents, which is important for the economic growth of European countries.

Adequate capitalization is crucial for ensuring a bank’s financial stability and, by extension, the financial security of the entire country. This importance is especially evident in terms of both the quantity and quality of capital that a bank holds to cushion potential losses. Various indicators and ratios are employed to assess the level of bank capitalization, often subject to regulatory oversight. However, there is currently no standardized methodology for calculating and analyzing this indicator. This article aims to analyze the comprehensive index of bank capitalization levels. The calculation is based on statistical reports from 34 European countries spanning the years 2010 to 2020. The author explores the main direct and indirect factors influencing the level of bank capitalization. Direct indicators include return on equity, capital to assets ratio, and the ratio of regulatory capital to risk-weighted assets. Indirect factors include return on assets, the level of non-performing loans, the number of bank branches, the ratio of expenses to income of banks, and the ratio of bank deposits to GDP.

A well-capitalized banking system is crucial for maintaining macroeconomic stability, preventing financial crises, and bolstering the economy's resilience to shocks. Governments often strive to ensure adequate bank capitalization to foster stable economic growth. This article aims to assess the relationship between bank capitalization and macroeconomic stability in 34 European countries from 2010 to 2021, based on World Bank statistics.The study utilizes the principal components method to identify relevant indicators of bank capitalization and macroeconomic stability, canonical analysis and regression analyses to detail the interconnections between these blocks. The canonical analysis confirms a link between bank capitalization and macroeconomic stability indicators with a coefficient of determination of 0.617 signifying that 61.8% of the variance in macroeconomic stability is explained by fluctuations in bank capitalization.The article presents one fixed-effect and two random-effect regression models detailing the directions and strength of influence of independent variables (NPL, ROA, ROE - indicators of the bank capitalization level) on dependent variables (INFLATION, UNEMPL, GINI - indicators of macroeconomic stability). The Wald criteria and a p-value less than 0.05 indicated that the models with random effects (UNEMPL, GINI) were statistically significant.The results reveal that a 1% increase in non-performing loans correlates with a 0.25% rise in the unemployment rate, and a 1% increase in return on assets leads to a 0.08% increase in the unemployment rate. Additionally, a 1% increase in non-performing loans raises the Gini index by 0.05%, while a 1% increase in return on equity decreases the Gini index by 0.03%. Notably, the impact of return on assets on the unemployment rate and the Gini coefficient is not statistically significant (p-value greater than 0.05).These results can inform the forecasting of national indicators, the development of tools to ensure sufficient bank capitalization, and the formulation of effective macroeconomic policies, taking into account fluctuations in banks' capitalization levels as key financial intermediaries.

A modern banking system is an integral part of the economic development of any country, as it ensures the functioning of the financial market, mobilizes resources of business entities, facilitates the expansion of credit opportunities and ensures the sustainability of the financial system as a whole. Ukraine, as a country with a transition economy, has faced numerous challenges and tasks in developing its banking system in recent decades. One of the main aspects is the infrastructure support for the sustainable development of the banking system, which is the country's key financial intermediary. Accordingly, in the era of dynamic economic shifts and global financial transformations, the role of infrastructural support in ensuring the sustainable development of banking systems is of primary importance. This issue is of great practical importance and is relevant for further research, given the impact of socio-political and economic turbulence observed in Ukraine where the banking sector is a key financial intermediary of the national economy. Therefore, for a timely and effective response to the challenges of the financial system and the needs of business entities, the Ukrainian banking system needs a reliable and adaptive infrastructure. In this context, the study aims to analyze the infrastructure support for the sustainable development of the banking (credit) system of Ukraine. The theoretical aspects of the sustainable development of the banking sector, which are highlighted in the eighth goal of the UN Sustainable Development Concept, are defined. The main indicators of payment (number of bank branches, number of ATMs) and monetary (number of bank accounts) infrastructure are allocated and analyzed. The goals and tools for implementing the Strategy for the Development of the Financial Sector of Ukraine until 2025 as a key document in the context of sustainable development of the banking sector are described. The following tools were used in the course of the study: grouping, comparison and generalization, analysis and synthesis, and graphical methods. The results of the study can be a source of information for public authorities, banks and other stakeholders seeking to promote the sustainable development of the banking system in Ukraine.

The research focuses on bank capitalization and macroeconomic stability, including corruption and the shadow economy. A well-capitalized banking system and a low corruption level are important for maintaining macroeconomic stability and reducing the size of the shadow economy. The paper is aimed at assessing the relationship between bank capitalization and macroeconomic stability, which includes corruption and shadow economy through canonical analysis. The research is conducted on the basis of financial and economic reporting of 35 countries with different levels of socio-economic development during 2010–2021 based on data from the World Bank and the European Central Bank. The main input blocks macroeconomic stability – corruption – shadow economy are characterized. During the research, the following tools were used: – methods of grouping, analysis and comparison in determining the characteristics of the elements of the chain «level of capitalization of the banking system – macroeconomic stability – corruption – shadow economy»; – factor analysis by applying the method of principal components in the selection of statistically significant indicators of the bank capitalization level and macroeconomic stability. The quantitative assessment of the bank capitalization level revealed the following dependencies: there is a strong correlation between return on assets and the level of non-performing loans, return on assets and return on equity. Using the principal components method, the following statistically significant indicators of macroeconomic stability were identified: GDP, Gini index, corruption perception index, corruption control index, and political stability index. Research, based on the canonical analysis, determined that 71.1% of changes in macroeconomic stability indicators are explained by fluctuations in the level of bank capitalization. The level of non-performing loans has a negative impact on macroeconomic stability, while the volatility of return on assets and return on equity has a greater positive impact on the development of the country's economy. The obtained results can be used by banks in the development of their resource and management policies, in the analysis of the volatility of capitalization level, by state bodies in the development of national policies of the country's economic development.