Financial risk management at creative economy enterprises in the context of the development of new digital technologies

Abstract

Creative economy enterprises in Ukraine form a significant part of modern digital content, services, and innovations, while they are vulnerable to financial risks due to high dependence on demand, fluctuations in cash flows, the cost of financing, and rapid technological changes. Thus, in the period 2020–2024, these risks increased due to martial law, uneven market recovery, and the need for an accelerated transition to new technology that requires investments and creates an additional burden on liquidity and financial stability. The object of the study is the processes of financial risk management at creative economy enterprises in the context of digital transformation. The subject of the study is methods of quantitative assessment and forecasting of financial risk, taking into account the intensity of digital investments. The purpose of the work is to develop a model that allows explaining and forecasting the financial risk index of creative economy enterprises based on reporting indicators and calculated indicators of digitalization. The methodology includes descriptive statistics, correlation analysis, comparison of functional regression forms, and evaluation of an extended model with a period indicator to separate the regimes of 2020–2021 and 2022–2024. Additionally, a scenario forecast for 2026 was performed for three digital investment trajectories, which allows obtaining a ranking of enterprises by the forecast risk level and assessing the sensitivity of risk to the acceleration of digitalization. The proposed model and a set of tables and graphs can be used by the management of creative enterprises to plan digital investments, assess their risk consequences, form scenario budgets, and prepare analytical materials for creditors and investors. The proposed approach is reproducible, since it uses indicators that can actually be obtained from reporting, and demonstration values can be replaced with actual data of enterprises without changing the calculation logic and modeling structure.