Abstract
The main purpose of the article is to model the dynamics of cause-and-effect relationships of banking risks using the method of constructing fuzzy cognitive maps. To construct a fuzzy cognitive map, a system of indicators of banking risks in Ukraine was formed, their dynamics in 2020–2025 were analyzed, and a correlation matrix of relationships was constructed. This allowed us to characterize the main cause-and-effect relationships between banking risks and formulate recommendations for risk management. Based on the analysis of banking risks, a moderate level of credit risks, a low level of liquidity risk, an increase in banks’ operational risks, a decrease in the level of interest rate risks, and an increase in currency market risks due to an increase in banks’ currency liabilities in 2020–2025 were identified. The study found that there is an inverse negative relationship between credit, interest rate, operational and liquidity risks of banks in Ukraine due to a significant share of non-performing loans and a moderate level of concentration of counterparty loans. In addition, a direct relationship was found between market risk and liquidity risk, interest rate, and operational risks. This indicates the importance of increasing assets in foreign currency and reducing the volume of open currency positions of banks. Interest rate risk (reduction in net banking profitability) negatively affects lending, including in foreign currency, as well as liquidity risk. At the same time, interest rate risk, measured as net interest margin and net interest spread, has a direct relationship with operational risk (i.e., with an increase in these indicators, the volume of operational risk will increase). This means the need to supervise interest rates on new loans and deposits.
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