Subject. The article discusses the structure of the banking market in Russia, its dynamics and determines how it deviates from its Pareto optimality. Objectives. We evaluate the efficiency of public administration, outline and develop economic and mathematical methods and techniques to support the decision-making process in the governmental regulation of Russia’s banking. Methods. The market power of a banking market actor is quantified with the amount of its balance sheet currency as a comprehensive indicator of its business performance and activity. Doing so, we quantify the economic potential of diverse market actors in banking, which have their own operational distinctions and working in different segments. We choose the traditional paradigm of structural evaluation methods as the key methodological principles. It ensures the corresponding result. The approach helps use official and publicly available statistics of the banking market (statistical data of the Central Bank of the Russian Federation) to assess the optimality of the overall banking structure in the Russian Federation by studying how certain market actors allocate their assets. Results. We did the ABC analysis of the banking market structure in Russia within 2007 through 2019, pointed out groups A, B and C and reviewed their composition. Conclusions and Relevance. We conclude that the banking market that has existed in Russia for the recent 13 years seems to fall short of the theoretically effective one as per the Pareto principle, with its dynamics being unfavorable and fueling the market concentration. The sustainability of the banking market requires more banks from group A, higher efficiency needs less banks from group C, which makes banking regulators intervene the market by setting and adopting respective requirements to market actors.

Subject. The article considers trends in different types of crimes committed in the Russian Federation from 2012 to 2019. Objectives. The purpose is to determine trends and the presence or absence of annual seasonality in the analyzed dynamics. Methods. The study draws on parametric modeling of trend-seasonal dynamics, using our own procedures, a set of models and methods for their identification by means of generalized ARMA models, the STL (Seasonal Transformation using LOESS) method, the Yeo-Johnson method based on standard libraries and applications of the R programming language. Results. The paper offers two methods to model seasonality: a "rough" assessment of its presence and a "fine" assessment, with obtaining quantitative estimates of model parameters and estimates of qualitative characteristics of modeling. We determine optimal smoothing settings to solve the problem of trend-seasonal modeling of crime dynamics, analyze the dynamics of eleven types of registered crimes, and identify the parameters of seasonal component for each of them. Conclusions. In nine out of eleven types of considered crimes, there is a pronounced annual seasonality, which is advisable to take into account, when organizing and planning the law enforcement activities.

This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 4.0 Unported License, permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.