The consequences of Industry 4.0 have adverse side effects on cybercrime growth, which requires creating an effective cybersecurity system for companies. Therefore, this study aims to develop a composite indicator of company cybersecurity to assess its development needs. For this purpose, the authors modified Porter’s method by constructing a superposition matrix based on the growth rates of cyber threats and risks, calculating their quantitative characteristics and a composite indicator. The computations are based on indicators for 2016-2022 characterizing cybersecurity vulnerabilities and the consequences of cyber threats: the share of companies experiencing one, six or more successful cyberattacks, considering the likely and very likely success of cyberattacks on them in the next 12 months, security threat and concern indices, the share of companies with a growing security budget affected by ransomware and experiencing a shortage of skilled IT security personnel, the cost of stolen or compromised credentials. As a result, cybersecurity needs increased significantly for 2020-2022, mainly due to digital transformation and the cyber threats growth after the COVID-19 pandemic. A comparative analysis of the proposed indicator with those characterizing the development of Industry 4.0 showed that the need for a reliable cybersecurity system is much more important than the active development of modern technologies. Spending on IT is also increasing, but not enough to meet the needs of cybersecurity development, except for the 2022 results. The proposed indicator is defined for companies worldwide, but its versatility allows the methodology to be applied to enterprises of various industries and sizes.

Digital financial technologies create a basis for forming new concepts for studying the prerequisites for the emergence of the shadow economy, the search for mechanisms to counteract illicit financial flows, and ensuring financial stability in the country. The article aims to assess the degree of connections between the shadow economy, financial stability and finance digitalization using the principles of cognitive modelling. The empirical study proved that the current status of development of digital finance and financial strength in Ukraine is sufficient for a significant reduction of shadow operations in the economy, namely to the level of 14.43% of GDP, which is 55.8% less compared to the average annual value for the period 2005-2021 years. It is advisable to implement a set of measures aimed at increasing the volume of the cashless economy; reducing non-performing loans; optimization of banking infrastructure; encouraging citizens to use online banking; reduction in the level of fictitious direct investments.

Money laundering has become a global threat to the international stability and security, leading both to economic and social upheavals, and to an increase in terrorist threats. Therefore, an objective necessity arises for a more detailed study of the money laundering within the scope of its developmental patterns and time-dependent behaviour. The study mission is the development of a theoretical framework and methodological support for modelling the cyclic component of the money laundering risk. The correlation and regression are used for isolating the cyclic component. In turn, the Fourier harmonic analysis allows specifying the cyclic component. Additionally, we carried out a decomposition of time series, analysis of its volatility and persistence using the Hurst exponent. We determined the peaks, downturns and duration of the money laundering cycles in the developed economies and economies in transition, and established the possibility of predicting this process in the medium term. We proved the internationalization of the money laundering and the similarity of behaviour of trends that characterize it both for developed economies among themselves and between groups of countries. The further scientific research is needed within the framework of the imposition of trends in the development of the money laundering processes of some countries on others and the formation of international medium-term anti-fraud strategies.

This paper aims to address the practical challenge of enhancing the effectiveness of anti-money laundering systems within the context of the digital economy. Specifically, it examines how institutional, financial, and educational channels can be optimised to combat illicit financial activities. This research responds to the growing need for a comprehensive anti-money laundering framework that can adapt to the evolving dynamics of the digital economy, where financial crimes are becoming increasingly sophisticated. A methodological framework is proposed to assess and forecast the effectiveness of these channels, employing the principal component method and Saaty hierarchy analysis. The study incorporates both linear and nonlinear regression models to provide medium-term forecasts for the channels' characteristics and their contribution to anti-money laundering effectiveness. An integral indicator is developed to quantify the impact of these channels in combating illicit financial activities. Historical data are utilised to project trends up to 2025, revealing the expected influence of institutional, financial (investment), and educational channels on the anti-money laundering system. The results indicate that, without targeted interventions, the effectiveness of institutional and financial channels gradually decreases, whereas the educational channel maintains a positive trajectory. This analysis underscores the importance of strengthening institutional frameworks and financial oversight to ensure the sustainability of anti-money laundering measures in the digital economy.