The authors of the article test the hypothesis about the impact of digitalisation processes on the level of territories’ economic development. This hypothesis is based on the fact that in the Russian Federation digital transformation is considered as a conceptual model for improving the activities of intraregional economic units and the development of modern society, as well as a factor of economic and social breakthrough. The purpose of the study is to develop scientific and methodological support for the territories’ transformations management based on digital transformation. Systematization and generalization of methodological approaches to the assessment of digital transformation in the region have been carried out. For this purpose, a scientific approach to the design of indicators system characterizing the processes of digitalisation is proposed. To test the approach, a correlation analysis of the current state of digital development impact on the territories’ economic results was carried out. The analysis of the statistical dependence between the development and welfare level of Russian regions and the parameters of their digitalization showed a low (moderate) relationship. This means that with the current volume of funding for digital transformation and the use of information technologies, devices and special software, it is impossible to ensure the breakthrough development of regional economic systems and their production complexes.

Optimal allocation of deposits (resources) and facilities (expenditures) are among the most important strategies of banks. Optimal allocation of resources in various economic sectors leads to targeting of funds collected by banks. Optimal allocation of expenses, in addition to obtaining returns in excess of the cost of attracting resources, leads to rapid and timely response to bank customers. The purpose of this study is to provide linear programming models to determine the optimal combination of resources and expenditures of banks with the approach of reducing the cost of money. The tools used in this research are linear programming models and the data used is quantitative. The results of this study showed that all five factors (electronic banking, physical factors and conditions, service factors, communication and human factors and financial factors, respectively) were effective factors in attracting resources. They are influential in the bank, respectively.