Information Management: the Key Driver of the Economic System’s Development

In the scientific article, an information management model was developed for assessing the influence of regulatory tools on business processes on the example of the insurance market of Ukraine. The main purpose of the research is to determine the role of information management as a key driver of business process development in economic systems (on the example of the Ukrainian insurance market). Systematization literary sources and approaches for solving the problem indicates that the development of innovative tools of public governance for the assessment of the regulatory influence of the state regulatory body on the business processes of insurance market is not completed and requires a more in-depth study. The formation of a system of indicators characterizing the business processes of insurance market, which take into account the influence of the Regulator's tools, is proposed to be implemented in the following sequence: to find out the causal links between the indicators of business processes of insurance market and the measures; to determine the existence of the reaction of business processes’ indicators of insurance market to the Regulator’s measures, taking into account the time gap, which determines the presence of lags in the process of applying the Regulator's measures; to define and formalize the variability of the business processes’ indicators of insurance market under the influence of the Regulator's measures. Then the scale of the state of insurance market was built: firstly, check for normality the distribution of the indicators’ values of these markets; secondly, in compliance with the distribution law to construct the scale of indicators according to the «three-sigma rule»; thirdly, in the case of nonconformance with the normal distribution law and presence of skewness, the method of «three sigma» may be used, but either the arithmetic mean, or the mode of the variation series, or its median, is taken as the reference point. The relevance of the decision of this scientific problem is that a set of models is developed for establishing causal relationships between the indicators characterizing the business processes of the insurance market and government regulation instruments, which are quantitatively determined, are theoretical and practical basis for their possible application for solving universal modeling problems of causal processes of estimating the influence of the taken decisions at any regulation of business processes. To solve the problem the Granger-test, the expanded Dickey-Fuller test, the Phillips-Perron test and the Kwiatkowski-Phillips-Schmidt-Shin test were applied. Time series distribution on stationarity and construction of vector autoregression models are implemented. In order to evaluate the adequacy of the models, a comparison of values of Fisher's, Student's criteria, determination coefficient and adjusted determination coefficient is used. Jarque-Bera criteria are used to test the model for stationarity, stability. The formalization of cause-and-effect relationships through the postulate of the theory of measurements and the construction of scales is performed. The built interval scales are based on the application of the three sigma rule, which made possible to specify the allowable boundary values of the indicators. The obtained results testify the influence of regulatory tools on the business processes of insurance market, which confirms the correctness of the use of this complex of models for the solution of weakly formalized problems of causal nature of universal type. The proposed innovative model can be used as a methodology for developing a set of rational methods for assessing informational influences of management decisions in production systems or marketing research. The results of the research can be used to evaluate the business processes of any market or system.Keywords: business processes, Granger test, informational management, informational model, insurance key driver, services market, regulation tools, scaling, vector autoregression.