Экономика региона (Mar 2020)
Implementation of Digital Technologies in Financial Management
Abstract
The transition to digital economy based on new technologies becomes one of the main tools of innovative technological development in Russia. This research examines the means for implementing digital technologies that effectively enable rapid innovative development of the Russian economy. I hypothesise it is necessary to develop a methodological system of techniques and algorithms of artificial intelligence filling neural networks of digital technologies for managing finance in the conditions of uncertainty and risk. A wide variety of methods was used in the study, including dialectic and integrated approaches, fundamental economic laws, deductive and inductive methods, statistical comparisons, descriptive methods of analysis. Moreover, I apply such methodologies as the theory of constraints (TOC), methods of lean manufacturing, Kanban-methods as a tool of IT-management, scrum methodology for software development, and other. The statistical and empirical data confirm the validity of the conclusions and results. The paper considers how to create capital in the form of innovative products and technologies in the digital environment. As a result, the study has revealed relations between digital technologies and engineering account, economic analysis, material production, highly skilled creative work, environmental protection, and sustainable development. The article explains how to include automated information and analytical functions for the compensation and generation of missing information into digital technologies. The transition from the database to the knowledge base, which fills neural networks with the artificial intelligence, provides the generation of management decisions and sustainable innovative development in the conditions of uncertainty and risk. The paper recommends currencies for digital payments. I conclude that applying the suggested recommendations is necessary for providing digital technologies with the algorithms of extraction and implementation of knowledge from the data asset, as well as for compensating for the missing information, generating information flows, and making decisions in the conditions of uncertainty and risk. The research can be of use for PhD students, doctoral students, scholars and practitioners in the field of economy.
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