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The article analyzes the prerequisites for systematic use of Big Data sources by government agencies as a tool for forecasting systemic financial risks during investment decision processes at the state level as well as for the formation of public investment policy. The author made a comprehensive assessment of the system of factors that influence the investment decision-making process in terms of post-industrial transformations. The author proposes to solve the problem of forming investment activity information risks based on empowerment of big data analytics. The proposed model assesses the institutional framework by analyzing a wide range of factors such as the level of shadow economy, corruption and economic freedom, including government integrity, property rights, investment freedom, that influence the process of investment decision. Based on indices analysis expands the limited capabilities of risk assessment models of financial instruments based on market data, that reflect the components of expectations, covering the behavioral factor - speculative behavior. Cluster assessment of investment inflows to Ukraine was conducted based on econometric modeling using VAR analysis revealed no significant impact of indicators that reflect the presence of institutional barriers for investors concerning FDI from offshore countries (Cyprus, British Virgin Islands), the impact was limited to an average of 5%. Along with economic factors, the determinants of FDI inflows from developed countries (Germany, Great Britain, United States of America, Austria, the Netherlands) were institutional ones influencing the formation of compliance risks, the impact of which ranged within 30%.

Evaluating the system of factors influencing the investment decision under postindustrial transformations