Yevgeniya Mordan

Nowadays, there are many preconditions and circumstances for conducting shadow schemes in the financial market. Therefore, the level of risk of participation of bank and non-bank financial intermediaries in such schemes is assessed as high. The lack of a practical methodology for assessing the development trajectory of financial intermediaries raises the question of the need for preventive control and quality modeling of their growth dynamics. The study aims to identify and formalize the patterns of development paths of banking and non-banking financial intermediaries based on the Harrington desirability function, which will be used to identify risk patterns as indicative patterns of financial intermediaries’ participation in shadow schemes. The sample includes 13 banking institutions, 3 credit unions, 3 pawnshops, 3 insurance companies, and 3 financial companies. The obtained results showed the relationship between the financial intermediary risk level in terms of its participation in shadow schemes and the phases of the economic cycle as a catalyst for the economic dynamics of the formal and informal economy. Thus, in 2012–2015, most financial intermediaries were in the zone of most significant risk, especially banks, characterized by economic, social, and political instability. Today, banks are in the group with a controlled level of risk of participation in scheme operations. Over the years analyzed, a stable neutral level of risk of participation in shadow schemes was inherent in most non-bank financial institutions. They were less sensitive than banks to the phases of the economic cycle.

Acknowledgment
Alina Bukhtiarova and Yevgeniya Mordan gratefully acknowledge financial support from the Ministry of Education and Science of Ukraine (0120U100473, 0121U100469).

Russia’s open aggression against Ukraine has resulted in significant changes across all sectors of the Ukrainian economy and its financial sphere, including financial security. The paper aims to identify the impact of the primary macroeconomic determinants, i.e., military defense spending, non-performing bank loans, exchange rate, foreign debt, and state (total) reserves, on the financial security of Ukraine under martial law. The canonical correlation analysis is employed to assess the strength of the relationship between the above macroeconomic indicators and the level of the state’s financial security. It was found that the reduction of the state’s financial security level in 2022 was 63.9%, explained exactly by the changes in the above macroeconomic determinants after the start of a full-scale invasion. The study determined the degree of influence of each indicator on Ukraine’s financial security level. An increase in the level of military defense spending, non-performing bank loans, hryvnia’s devaluation, and external debt growth had a direct negative impact on Ukraine’s financial security. At the same time, an upsurge in total reserves had an indirect negative impact (through the external debt growth). The research findings confirm the necessity for effective monitoring and management of the macroeconomic indicators to maintain both Ukraine’s financial security and macro-financial stability in order to ensure its’ sustainable economic development during the postwar recovery period.

Acknowledgment
This research is financially supported by the NATO SPS Program “Security of territorial communities: evidence from the Eastern European countries”.

Type of the article: Research Article

Abstract
Digital technologies have become a key driver of economic growth, competitiveness, and social inclusion, while significant disparities in digital development persist across national economies. The aim of this study is to map and interpret the trajectories of digital transformation in 30 selected European countries (EU member states, associated economies, and Ukraine) during 2011–2022. The study employs the self-organizing map (SOM) with Ward hierarchical clustering to uncover latent structures of digital development, using a balanced panel of 20 indicators across three domains: ICT sector development, digital infrastructure, and digital technology adoption and skills. Cluster validity was assessed via the Elbow Method, Silhouette Coefficient, Calinski-Harabasz, and Davies-Bouldin indices. Results indicate that the two-cluster solution is statistically robust, while the three-cluster solution provides additional insight into transitional patterns of digital transformation. The two-cluster solution revealed a clear distinction between digital leaders and less advanced economies, with the greatest disparities observed in online banking (71% vs. 29%), online purchases (68% vs. 32%), and e-government use (68% vs. 34%). The three-cluster solution provided further nuance, showing that in 2011 most European economies were concentrated in the weakest cluster, while only Northern Europe achieved high levels of digitalization. By 2020, all European countries had reached at least the middle cluster, reflecting a shift from strong polarization toward a more balanced distribution of digital development. Despite progress, structural gaps remain, emphasizing the need for policies that advance digital skills, encourage inclusive adoption, and build trust in online services to sustain digital transformation.

Acknowledgment
The authors acknowledge with gratitude the financial support provided by the Ministry of Education and Science of Ukraine for the research project “Cybersecurity and digital transformations of the country’s wartime economy: the fight against cybercrime, corruption and the shadow sector”, state registration number 0124U000544).