In conditions of unprecedented economic turbulence and increasing global financial instability, there is a growing need to improve approaches to forecasting financial risks of investment projects, which will ensure their viability and effectiveness in the long term. The aim of this work was to develop a comprehensive methodology for assessing and forecasting financial risks that takes into account multiple factors of uncertainty and improves the quality of investment decisions. Using the example of the project “Restoration of the material and technical base and infrastructure facilities of the State Enterprise “International Children's Centre “Artek”, an analysis of key risk factors was carried out, among which the most significant were macroeconomic indicators (57.4%), political and institutional factors (29.6%), and project risks (13%). The developed integrated forecasting model combines quantitative and qualitative risk assessment methods, taking into account their interaction and multiplicative effects. The proposed early warning system allows detecting signs of increased risk 3-6 months before the actual impact on the project. Monte Carlo modelling has shown that for high levels of economic instability, the most effective strategy is to minimise risk through phased financing and diversification of sources, which can reduce the probability of project termination by 40-45%. For medium levels of instability, it is recommended to apply balanced management using reserve funds and public-private partnership mechanisms. The impact of the digital transformation of the economy on the risk structure was also studied, and methods for adapting investment strategies to new technological challenges in the context of growing global competition were proposed. The practical value of the results lies in the possibility of using them to improve the efficiency of investment project management in various sectors of the economy in conditions of uncertainty, which is particularly relevant for projects with long investment cycles and public funding
Muzychenko et al. (Wed,) studied this question.