Analysis of financial and economic indicators of agricultural enterprises in the region based on open data sources

. The article presents and tested a new technique that allows performing financial and economic analysis of enterprises in a given industry in order to optimize its management, based on open internet data sources, using licensed software, as well as on the basis of classical methods of intellectual data mining (further - IDM), as well as systems of fuzzy logic conclusions. The main advantages of this technique are independence in obtaining data and its universality. With a little improvement, this technique can be used to analyze enterprises in almost any sectors of OKVED. In the future, it is planned to develop a new software package that allows you to perform financial and economic analysis of enterprises in a given sector in automatic mode.


Introduction
The analysis of financial and economic indicators of agricultural production in the region, based on the analysis of industry enterprises, is of great importance both for government authorities that form investment and tax policy, and for potential investors and partners, as well as for the heads of companies. The method of integral estimates [1][2][3][4][5][6][7][8]11], which takes into account the relationship between various indicators of the enterprise, allows to track the possible dynamics of its development, currently is quite widespread. However, it has significant disadvantages associated with a subjective approach to determining expert assessments and does not take into account the specific (sectors) features of the enterprise [10][11][12][13][14]. The main tool for analysis is often financial coefficients, which allow to identify both the dynamics of indicators, and the limits of acceptable values (restrictions) and ratios of indicators. The available criteria, based on which coefficients give a qualitative assessment of the financial condition of the enterprise, are most often based on integral point estimates [3]. Points are awarded automatically, but most indicators have an equal or random weight, and when adding new indicators, entire order of the account has to be changed. These models are difficult to modify, and a significant problem in them is taking into account the opinions of individual experts, as well as the uncertainty of external conditions. For evaluating financial and economic state of a particular sectors in a particular region, there are techniques that are usually based on the analysis of some aggregate indicators and do not allow for analysis of financial and economic condition of the sector in the region based on performance of individual enterprise is taken from open internet sources. The purpose of this research is to develop and test a new methodology that allows performing financial and economic analysis of enterprises in a particular industry based on open Internet data sources, using classical methods of intellectual data mining (IDM) and a system of fuzzy logical conclusions [2,5,13]. To achieve this purpose, the following tasks have been set and solved.

Technique for analyzing the financial conditions of the enterprise
The technique developed by us for collecting data on the financial and economic condition of individual enterprises that are suitable for analyzing the condition of the OKVED sectors in the region from open internet sources includes three steps. At the first step, a database of enterprises was formed in accordance with the specified classifier code, which allows identifying enterprises in all-Russian data systems by name and TIN.
The site of the Russian and CIS enterprise' database ExportBase was used [4]. The database was formed by selecting OKVED-01 on the example of the region -Rostov region. The formed base included 683 enterprises of the Rostov region OKVED-01.
At the second step, open data on enterprises was collected using specially developed software from the sites: "For honest business" [6] and "Your financial analyst" [1]. The enterprise's TIN was used to find the enterprise's page.
At the third step, the received reports are analyzed for their suitability for analysis. It was found that from the list of 683 agricultural enterprises in the Rostov region: 8 enterprises were liquidated; 41 are in the process of liquidation. Among the remaining enterprises, 379 enterprises completely lack data. The remaining 255 enterprises are considered suitable (or partially suitable) for the analysis.
Based on the made database, a statistical analysis of financial statements of enterprises was performed and their clustering was carried out by subgroups of OKVED: 01.1 "The Cultivation of one-year crops"; 01.2 "The Cultivation of multiyear crops", 01.3 "The Cultivation of seedlings"; 01.4. "Livestock"; 01.5 "Mixed agriculture"; 01.6 "Provision of services in the field of agriculture". Table 1 shows the calculated total tax values, by type, for the OKVED 01.1 "subgroup "growing one-year crops". The graphical analysis of the structure of the amount of paid taxes is shown in Fig. 1. The data is presented in rubles.     This analysis allows us to analyze the distribution of the tax burden by type of tax, as well as to evaluate the distribution of social benefits by type of insurance.
Thus, the developed technique allows to study the financial and economic indicators of the industry based on open sources of internet data.
In general, the experiment showed the possibility of a comprehensive study of the financial and economic condition of agricultural enterprises in the region based on open internet data using specialized software. This data analysis requires additional work to "clean" the data. The development of this direction can be significantly enhanced in the process of improving the corresponding automatic systems and services. The developed methodology can be automated in the future by creating appropriate programs and web services, which will allow for a more detailed and accurate analysis of the situation in a given sector: identify the main trends, determine the structure, calculate aggregate indicators of the sector, summarizing enterprises by the number of employees, profits, taxes, etc.

Conclusion
The new technique has been developed that allows performing financial and economic analysis of enterprises in a given sector, based on open data (internet sources), using appropriate software, as well as on the basis of system methods for managing complex multi-factor systems based on fuzzy analog controllers [7]. Testing of the technique was carried out at the enterprises of the Rostov region OKVED-01 (Crop and Livestock production, Hunting and Provision of appropriate services in these areas) and showed its sufficient effectiveness. The main advantages of this technique are independence in obtaining data and its universality. With a little improvement, this technique can be used to analyze enterprises in almost any sectors of OKVED. In the future, it is planned to develop a new software package that allows you to perform financial and economic analysis of enterprises in a given sector in automatic mode.