Aleksey Mints

The article proposes an approach to analyzing the reliability of commercial banks using multilayer neural networks and Kohonen self-organizing maps, and also conducted their approbation on the example of the Ukrainian banking system from 2014 to 2018 with breakdown into 3 periods. Based on the experiments, the best variants of the architecture of neural networks are revealed. It is found that solving the problem of assessing the reliability of commercial banks in the clustering formulation gives a better result than in the classification formulation. The conclusion that a rapid change in the conditions of functioning of a modern banking system makes inefficient the use of analytical models with rigidly prescribed coefficients is experimentally substantiated. The results of the research are of practical importance and can be used to identify potential partners in the banking sector of the economy.

Achieving business success for a company is directly related to financial planning, budgeting and analysis of results. Any system is viable if it includes feedback elements that provide an analysis of what the system has done and current adjustments to the system’s behavior as signals about its state. The article deals with the features of the budget process at energy enterprises as part of vertically oriented holding structures. The system formed by such enterprises is very complex, so it is necessary to take additional measures to maintain the efficiency of the budget process in such conditions. Therefore, an important issue is the organization of effective control in the budget execution system to make operational management decisions, which turns it into an effective tool for managing the enterprise. The essence and importance of budget control of energy companies are revealed. The paper deals with the organization of budget planning at an enterprise of the energy industry. Models for budget development and budget execution processes were built and budget limits were adjusted for enterprises using the IDEF0 methodology. The methods of control over the budget execution of energy industry enterprises are considered. The essence and types of the process of adjusting the budget of enterprises are revealed.

The article proposes an approach to analyzing reliability factors of commercial banks during the 2014–2017 systemic crisis in the Ukrainian banking system, using the Kohonen self-organizing neural networks and maps. As a result of an experimental study, data were obtained on financial factors affecting the stability of a commercial bank in a crisis period.

It has been concluded that during the banking crisis in Ukraine in 2014–2017, the resource base of a bank was the main factor of this bank stability. The most preferred sources of resources were funds from other banks (bankruptcy rate of 5.7%) and legal entities (bankruptcy rate of 8%), and the least stable were funds from individuals (bankruptcy rate of 28.5%).

The relationship between financial stability and the amount of capital and the structure of bank loans is less pronounced. However, one can say that banks that focused on lending to individuals experienced a worse crisis than banks whose main borrowers were legal entities.

The tools considered in the article (the Kohonen self-organizing neural networks and maps) allow for efficiently segmenting data samples according to various criteria, including bank solvency. The “hazardous” zones with a high bankruptcy rate (up to 49.2%) and the “safe” zone with a low rate of bankruptcy (6.3%) were highlighted on the map constructed. These results are of practical value and can be used in analyzing and selecting counterparties in the banking system during a downturn.

In Ukraine, card payment systems develop at a rate similar to that of modern digital payment instruments in most European countries.
The purpose of the paper is to establish interdependence and explain the nature of changing situations in the market of bank payment cards (BPC) taking into account the dynamics of economic development parameters in non-financial sectors of the Ukrainian economy.
The methodology of the study includes graphic methods analyzing the dynamics of economic development indicators and a method for analyzing the cause-and-effect relationship between the studied parameters considered with different lags.
Results showed that the most significant parameters for the development of the payment card infrastructure were the level of provision with POS terminals and the share of non-cash transactions. Their correlation with the economic development indicators reached 0.97. Up to the stage when the volume of non-cash payments by cards reached 5% of GDP, the impact of the BPC market on the change in the level of economic development had been insignificant according to the general idea. The development of the economy up to that point stimulated the development of the BPC market. Subsequently, the BPC market that was already sufficiently developed became one of the drivers aimed at the development of non-financial sectors of the Ukrainian economy after overcoming the 5% GDP level.