Constant innovations in finance and technology and different levels of their development worldwide necessitate investigating universal integrated indexes. It will enable a general assessment of the digitization of financial services and allow carrying out a comparative inter-nation analysis. The authors proposed to evaluate the level of digitalization of financial services (DFSI) based on three components: digital inclusion, financial inclusion, and digital financial services. The suggested approach includes several steps: 1) forming an array of input data by eight indicators; 2) establishing the priority of indicators and calculating their weights by using the Fishburne formula; 3) calculating the integral index of digitization of financial services by using the weighted sum method. According to the obtained DFSI values, the European countries were divided into four groups: with a high, medium, low, and critically low level of digitalization of financial services. Countries with a high level of DFSI are

This paper considers an algorithm for constructing an integrated assessment of the environmental risk of enterprises based on risk indicators. An overview of risk assessment methods is given. To find and process the research results, the method of expert assessments and elements of the fuzzy logic method were used. The membership function is constructed for the classification of the current value of the environmental risk factor. Based on the obtained numerical results, the ranking of the studied variables is given. A generalized indicator of the level of environmental risk of an oil and gas enterprise is found.

In the dynamic, unpredictable and so changeable modern world, all spheres of life are facing changes. The banking system was not left aside. Implementing innovative fintech solutions was the only option for traditional banking institutions to stay afloat. That's why the new types of banking institutions - neobanks appeared. The term “neobank”, which originated in 2017, refers to a new type of financial institution that provides modern, fast, and flexible services right in a smartphone or messenger. White-label financial services allow fintech and third parties to showcase a stylish, company-branded front end using an established bank license, regulatory compliance, and back-end technology to offer core banking features that compete with large institutions. The article analyzes the advantages and further prospects of the development of neobanks, the difference between white-label and baas solutions, as well as the principle of operation of each of the systems. An analysis of the modern market of platform developers for neobanks was carried out, which made it possible to identify the largest market players from European and Scandinavian countries. As a result of the study, the features of each of the developers of platforms for neobanks and their contribution to the development of the world economy were determined. Also, the article highlights the factors that make white-label solutions the future of online banking. The article mentions important conditions for the development of white-label solutions for neobanks, traditional and non-traditional banks – the improvement of the regulatory framework that would determine the legal status of such kinds of institutions, as well as the conditions for licensing and regulation of their activities. In the article, the most popular providers of neobanks are described. The conducted comparative analysis gave the opportunity to highlight the factors that provide these companies success, as well as to name the current market leaders. Overall, the study made it possible to identify the advantages, disadvantages, and risks of neobanks, and determine factors that provide stable growth for white-lable neobanks as well as prospects for their development.

The article proposes a methodology for the formation of a combined model of the equilibrium values of pricing and the volume of electricity production, taking into account green and traditional sources of electricity production on the example of Ukraine. In accordance with the projected price and volume of electricity production in 2021, a model for redistributing electricity sources were considered, taking into account the minimization of budgetary resources and the risk of electricity production with appropriate restrictions in the production of various types of electricity and their impact on minimizing the price for the end user. The studies have shown that important factors in the formation of electricity prices are indicators of the cost and volume of production, distribution and transportation of electricity to consumers, which largely depends on the formation and further development of the energy market in Ukraine. Also, the redistribution of the volumes of traditional and non-traditional electricity in the common 40 "pot" is of great importance while minimizing risks and budgetary constraints. Balancing the system for generating electricity from various sources will help not only optimize long-term electricity prices and minimize tariffs for the end user, but also allow planning profit in the form of long-term market return on investment. The analysis of the results showed that the optimal distribution of energy production makes it possible to obtain energy resources in the required volume with lower purchase costs and with minimal risk.

The article analyzes the current state and trends of e-sports in the world by studying the time series of the number of requests from Internet users, obtained through the use of Google Trends. The positive and negative consequences of e-sports development in the world have been identified. The forecasting of world tendencies of e-sports by means of methods of data mining is carried out. Using the application of multivariate adaptive regression splines (MARSplines), a model of the relationship between the predictor - a time indicator and the dependent variable - the time series of the number of requests of Internet users, which are non-monotonic in nature and provide the possibility of regression switching points. The adequacy of the constructed model is proved by means of regression statistics and histogram of correspondence of residuals to the normal distribution law. The expediency of using the method of multivariate adaptive regression splines (MARSplines) before other statistical methods is substantiated.