Tymoshchuk, O. L.Bidyuk, P. I.Levenchuk, L. B.Guskova, V. G.2026-01-052026-01-052025Intelligent decision support systems for financial risk modeling and analysis / Tymoshchuk O. L., Bidyuk P. I., Levenchuk L. B., Guskova V. G. // Системні науки та інформатика : збірка доповідей ІV науково-практичної конференції, [Київ], 1–5 грудня 2025 р. / Навчально-науковий Інститут прикладного системного аналізу КПІ ім. Ігоря Сікорського. – Київ, 2025. – С. 68-75.https://ela.kpi.ua/handle/123456789/77848The article examines approaches to financial risk analysis based on mathematical models and intelligent decision support systems (IDSS). The study describes key types of financial risks and the properties of economic processes that complicate modeling, such as non-stationarity, nonlinearity, and heteroscedasticity. It outlines the main stages of model construction – from data preprocessing and structure identification to parameter estimation and adequacy assessment. Classical risk management models, including BIA, LDA, and IMA, are analyzed, and the potential of Bayesian networks and fuzzy logic methods for handling uncertainties is highlighted. The article demonstrates that specialized IDSS, designed according to the principles of systems analysis, improve the quality of risk assessment and provide users with recommendations on model selection, uncertainty mitigation, and evaluation of forecasting performance. It is emphasized that the use of such systems reduces the labor intensity of analysis and increases the accuracy of forecasting potential financial losses.enfinancial risksrisk analysisnon-stationary processesnonlinear modelsheteroscedasticityBayesian networksfuzzy logicLoss Distribution ApproachBasic Indicator ApproachInternal Measurements Approachrisk modelingforecastingdecision support system (IDSS)ArticleС. 68-750000-0003-1863-30950000-0002-7421- 35650000-0002-8600-08900000-0001-7637-201X