The variety of modeling methods in the analysis of financial reporting of the borrower

Currently, the development of the efficiency of bank lending is directly related to ensuring sustainable economic growth. A significant increase in the efficiency of the credit process is achieved through the mechanism of preliminary credit analysis – a set of control and settlement measures aimed at identifying and assessing the risks of increasing the volume of loans provided by a credit institution to borrowers. The key disadvantage of classical methods of assessing the financial condition of an enterprise is the static nature of models, which leads to a decrease in their predictive power due to the action of regional, industry, and market specifics. The article presents the results of a study of the most common modeling methods in the analysis of the borrower’s financial statements for the algorithm of their compilation and accuracy in relation to small and medium-sized businesses in the Novosibirsk region. The research methodology includes formal logical methods – analysis, synthesis, induction, as well as methods of mathematical statistics - correlation analysis, attributive distribution, classification. The object of the study is models for assessing the financial condition of the borrower. The subject of the study is assessment tools and methods for assessing the financial condition of an enterprise. The purpose of the study is to develop a universal system of indicators included in the borrower’s preliminary assessment model.

1. Balikoev V.Z., Protas N.G. Istorija i metodologija nauki o den’gah, kredite i bankah. Uchebnoe posobie [History and methodology of the science of money, credit and banks. Textbook]. Novosibirsk: NSUEM, 2020.

2. Doncova L.V., Nikiforova N.A. Analiz finansovoj otchetnosti: Uchebnoe posobie [Analysis of financial statements and: Textbook], 2-e izd. Moscow: Izd-vo «Delo i Servis», 2004. 336 p.

3. Sotnikov A.A., Ershova I.G. Kojefficientnyj analiz finansovogo upravlenija predprijatiem [Coefficient analysis of financial management of the enterprise], Innovacionnaja jekonomika: informacija, analitika, prognozy [Innovative economy: information, analytics, forecasts], 2022, no. 1. Available at: https://cyberleninka.ru/article/n/koeffitsientnyy-analiz-finansovogo-upravleniya-predpriyatiem (accessed: 27.12.2022).

4. SPARK, Servis proverki kontragentov [Counterparty Verification Service]. [Electronic resource]. Available at: https://spark-interfax.ru (accessed: 25.12.2022).

5. Sultanov G.S., Kugushev T.R., Umailov U.M., Isagadzhiev M.A. Modeli i metody ocenki i analiza finansovogo sostojanija [Models and methods of assessment and analysis of financial condition], Zhurnal prikladnyh issledovanij [Journal of Applied Research], 2022, no. 3. Available at: https://cyberleninka.ru/article/n/modeli-i-metody-otsenki-ianaliza-finansovogo-sostoyaniya (accessed: 27.12.2022).

6. Test Firm, Spravochnik finansovyh pokazatelej otraslej Rossijskoj Federacii [Test Firm, Directory of financial indicators of industries of the Russian Federation]. [Electronic resource]. Available at: https://www.testfirm.ru/finfactor/ (accessed: 25.12.2022).

7. Chizh I.Ju., Rybjanceva M.S. Sravnitel’naja harakteristika metodov prognozirovanija bankrotstva predprijatij [Comparative characteristics of methods of forecasting bankruptcy of enterprises], Jekonomika i biznes: teorija i praktika [Economics and business: theory and practice], 2022, no. 10-2. Available at: https://cyberleninka.ru/article/n/sravnitelnaya-harakteristika-metodov-prognozirovaniya-bankrotstva-predpriyatiy (accessed: 11.03.2023).

8. Churikov A.B., Eliseeva D.A. Modeli prognozirovanija bankrotstva v organizacijah: analiz i kritika [Models of bankruptcy forecasting in organizations: analysis and criticism], Skif [Skif], 2022, no. 5 (69). Available at: https://cyberleninka.ru/article/n/modeliprognozirovaniya-bankrotstva-v-organizatsiyah-analiz-i-kritika (accessed: 11.03.2023).