Subject. The introduction of projects for digital economy development necessitates the improvement of the management efficiency of various elements of the financial system. Objectives. The aim of the study is to justify the need to use business analytics tools in managing the financial system in the digital economy, to show that in the model of financial outsourcing it is possible to apply the tools of predicative analysis, which is performed based on digital analytics platforms. Methods. The study rests on the use of one of the methods of predicative analysis, i.e. the method of correlation analysis. Results. Business analytics tools enable to unveil the most significant factors in the development of the income part of local budgets. The correlation matrix obtained through the analytical digital platform demonstrate that the strongest correlation in the income part of local budgets belongs not only to tax revenues, but also to inter-budget transfers. Business analytics tools help provide recommendations for increasing the amount of tax revenues to local budgets. The management cost can be reduced by using financial and tax outsourcing models. The paper shows that the use of modern predicative analysis tools will increase the management efficiency and enhance the effect of indirect financing by reducing the cost of tax administration. Conclusions. To accelerate the transition to the digital economy and to the digital region, it is important to actively use business analytics techniques and the methodology for modeling the innovative intelligent systems for decision-making, including the use of artificial intelligence tools.
Keywords: predictive analysis, financial outsourcing, correlation analysis, digital analytics platform
May M. Transformirovanie funktsii finansov [Transforming the Finance Function]. Moscow, INFRA-M Publ., 2005, 232 p.
Laktionova O.E. [Outsourcing of financial and accounting services in the global marketplace]. Finansovaya analitika: problemy i resheniya = Financial Analytics: Science and Experience, 2015, no. 23, pp. 22–33. URL: Link (In Russ.)
Laktionova O.E. [International financial outsourcing: Current trends]. Finansovaya analitika: problemy i resheniya = Financial Analytics: Science and Experience, 2015, no. 36, pp. 49–60. URL: Link (In Russ.)
Laktionova O.E. [Global finance and accounting outsourcing as an economic development driver]. Finansovaya analitika: problemy i resheniya = Financial Analytics: Science and Experience, 2016, no. 3, pp. 15–28. URL: Link (In Russ.)
Мінц О.Ю. Методологія моделювання інноваційних інтелектуальних систем прийняття рішень в економіці. Маріуполь, ПДТУ, 2017, 216 p.
Mints A.Yu. [The concept of modeling the intelligent automated decision-making systems in the management of economic objects]. Вісник Донецького національного університету. Серия В ‘Економіка і право’, 2015, no. 1, pp. 253–258.
Kim J.-O. et al. Faktornyi analiz: statisticheskie metody i prakticheskie voprosy. V kn.: Faktornyi, diskriminantnyi i klasternyi analiz [Factor Analysis: Statistical Methods and Practical Issues. In: Factor, Discriminant and Cluster Analysis]. Moscow, Finansy i statistika Publ., 1989, pp. 5–77.