A method of identifying banks’ business models and studying the features of their risk profile, considering the system of indicators featuring the structure of assets, liabilities, income, expenses, and other qualitative indicators based on monthly statistical reporting. Kohonen's self-organizing maps (SOM) are used to process large data sets, revealing objects’ hidden features by forming homogeneous groups according to similar values of a large system of indicators. The choice of the system of indicators that play the most significant role in describing the business models of modern banks is substantiated. The proposed method makes it possible to group banks with homogeneous characteristics into so-called structural-functional groups and studies the change in the characteristics of groups of banks over time to compare their behavior during periods of active development of the system and during a crisis. That approach is useful for studying the banking system at the macro level, as it provides a quantitative measure of its financial stability. The more banks are in groups with negative values of parameters, increased risks, and unprofitable performance, the worse the general state of the system. The method also allows studying the features of each structural and functional group and the business models’ features at the meso-level. The number and composition of banks inherent in any group change dynamically, which characterizes the features of the relevant business model in a particular period. The averages of each group reflect the objective changes in the banking system structure. In addition, the SOM trajectory can be built for each individual bank determining the development of its strategy, features of a particular business model, and risk profile. At the micro-level, it allows comparing the features of individual banks within the SFGB and models ways to improve efficiency and financial stability by forecast values for SOM. An extensive system of indicators used to form structural and functional groups of banks allows to quickly respond to changes in the banking system, identify areas of increased risk and explore the adequacy and effectiveness of banks’ business models.

Evaluation of ukrainian banks’ business models by the structural and functional groups analysis method

The purpose of this paper is to identify the peculiarities of banks’ business models and assess their risks, which is especially relevant in the context of the war in Ukraine since 2014. The information base is the published statements for each month of 63 Ukrainian banks for the period from 1 January 2018 to 1 January 2024. The number of indicators is chosen in an empirical manner. Business models are investigated using the method of structural-functional groups of banks, which allows estimating large arrays of financial indicators, grouping banks with similar characteristics and drawing conclusions about the main risks. It is convenient to use neural networks, namely Kohonen’s self-organizing maps, to estimate large data sets. The largest group of banks places a significant part of assets in government securities and has an unstable resource base. The share of these banks in the system as of January 1, 2024 is 38% and total assets are 10%. The second group by number of banks is focused on corporate lending with a high share of current resources in liabilities, and includes 21% of banks, whose assets account for 31% of total assets. State-owned banks, PrivatBank and OschadBank, account for 35% of total assets. The business models of these banks are characterized by dependence on retail funds, a high share of investment operations, and high credit and currency risks. Ukraine’s banking system has significantly developed a risk-oriented approach to management, which allowed it to maintain stability in the face of a full-scale war. 

Risk management through a Kohonen MAP bank business model survey: The case of Ukraine

This study aims to assess the potential risks of setting up a hydrogen infrastructure in the Netherlands. An integrated risk assessment framework, capable of analyzing projects, identifying risks and comparing projects, is used to identify and analyze the main risks in the upcoming Dutch hydrogen infrastructure project. A time multiplier is added to the framework to develop parameters. The impact of the different risk categories provided by the integrated framework is calculated using the discounted cash flow (DCF) model. Despite resource risks having the highest impact, scope risks are shown to be the most prominent in the hydrogen infrastructure project. To present the DCF model results, a risk assessment matrix is constructed. Compared to the conventional Risk Assessment Matrix (RAM) used to present project risks, this matrix presents additional information in terms of the internal rate of return and risk specifics.

Hydrogen Infrastructure Project Risks in The Netherlands

Обгрунтування моделей стохастичного хаосу для підвищення ефективності інвестиційних стратегій на міжнародних фондових ринках

The article analyzes changes in the business models of Ukrainian banks using the author's method of structural and functional groups of banks (SFGB). The method’s basis is the processing, systematization, and visualization of the system’s values of banks’ financial indicators using Kohonen’s self-organizing map (SOM). Depending on the level distribution of a large number of indicators that characterize the structure of assets, liabilities, income, expenses, and other qualitative indicators that describe the business models of each bank on successive reporting dates, homogeneous groups of banks are formed. The purpose of this study is to compare the key features of the banking system as of January 1 and September 1, 2022, and the corresponding changes in business models.Over the eight months of 2022, the number of banks with corporate lending increased slightly, but the resource base of these banks gradually changed. The number of banks with retail financing decreased at the expense of banks with current resources. During an increase in the discount rate and in the price of refinancing loans, banks’ business model that attracts resources on the interbank market and places them in securities has shrunk. At the same time, the number of banks with an increased level of securities in assets and corporate financing increased. The quality of the portfolio indicates the increased credit risks of the respective large state banks.The drawback of the proposed method is the dependence of conclusions on official banks 'statements that do not always reflect nuisances of financial position. Within small banks, we can sometimes observe that current changes in clients' account balances affect the position in SFGB. The SFGB method can be applied to analyze trends and estimate the probability of subsequent structural changes. For each bank, one can observe the trajectory change on the map and investigate the reasons for the change in business strategy.

Changes in ukrainian banks ‘business models in times of military crisis

The article investigates the main characteristics of the financial stability of Ukrainian banks, their risk profile, structure of assets, liabilities, income, expenses based on the monthly reporting data for 2004—2020 (number of observations — 3 813). The Kohonen self-organizing map (SOM) toolkit is used to form homogeneous groups of banks based on a large number of financial indicators. The selected toolkit provides a convenient visualization of the results. Each bank occupies a specific place on the SOM. The close location of banks on the map indicates that these banks have many common characteristics. This study is called the method of structural and functional groups of banks. The study formed stable groups of banks with the same characteristics of business models and risk profile. The formation of consecutive maps for each reporting period allows to obtain the characteristics of each bank separately and the banking system as a whole. The trajectory of an individual bank’s activity during the observation period characterizes the development of its business strategy. The migration of a large number of banks between groups reflects the objective changes in the conditions of banking. Increasing groups of high-risk banks indicate systemic problems. The results show that after a significant reduction in the banking system of Ukraine in 2014—2016, the business models of banks have changed significantly. The resource base relies on unstable sources of current funds with no set term of use. In the assets of banks, a significant portion is invested in government securities — government bonds. Bank loan portfolios have declined and have a higher proportion of non-performing assets (NPL). Many banks have increased currency risk. Concerns are raised about the state of large state-owned banks that hold a separate high-risk group. Thus, the conducted research allows to distinguish groups of banks with specific characteristics of business models and to observe changes of risk profile inherent to these groups. For each structural-functional group, changes in the values of financial indicators are investigated and migration between groups is studied. The proposed methodology is useful for studying both macro and macro levels.

Main characteristics of business models and risk profile of ukrainian banks

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Main characteristics of business models and risk profile of ukrainian banks