Abstract
The issue of determining the financial condition of commercial banks and separating investment-attractive banks from problem banks on this ground is extremely important for developing countries. The aim of this study is to make sure on the example of Ukraine that commercial banks really form separate clusters, where more reliable, stable and efficient banks are well separable from less successful ones in this regard. The study used the t-SNE and UMAP dimensionality reduction algorithms, and the Ward's Agglomerative Hierarchical Clustering algorithm. The results of visual analysis of two-dimensional t-SNE projections show that banks of different degrees of risk are well separable and have their own specifics. Clustering in the UMAP algorithm allowed distinguishing clusters with banks of Class A,
Highlights
The financial condition of commercial banks is one of the most important categories of the financial sector of any developed or developing country
We came to several approaches to diagnosing the financial condition of Ukrainian commercial banks
Having obtained sufficiently adequate results in the course of interpreting clusters, we can conclude that the separation of Ukrainian commercial banks based on a wide range of indicators of their activities is possible and efficient, investment-attractive banks are separable from problem banks, we proved our hypothesis H1
Summary
The financial condition of commercial banks is one of the most important categories of the financial sector of any developed or developing country. The reaction and behaviour of banking institutions during the 2007-2008 crises have been examined and analysed over the past decade by researchers around the world in order to assess the effect, the resulting damage and/or develop methods to mitigate future financial impacts [2,3,4,5]. This issue has become important for developing countries. Confidence in the banking system provides confidence in the economy as a whole [5]
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