Methods of Rating IT -Sector Companies by Level of Risks of Creditworthiness
https://doi.org/10.26794/2587-5671-2022-26-4-124-138
Abstract
The subject of the research are the companies of the IT sector, as a strategically important sector in the information age. Their development of companies in the IT sector is associated with high risks and requires large volumes of investments, including attracting bank loans. In this regard, the purpose of the study was to develop an adequate sectoral methodology for rating companies in the IT sector by the level of creditworthiness risks using mathematical and statistical tools that make it possible to reliably assess the potential risks of investors. To achieve this goal, the study proposes a methodology for assessing the creditworthiness of IT companies based on a system of risk factors, which makes it possible to quantify the exposure of companies to two generalized risk groups: financial risk and business risks. Based on the cluster analysis, a rating table has been developed, according to which, depending on the calculated score, the category of the company’s creditworthiness is determined. The study concluded that the key factors affecting the creditworthiness of companies are: indicators of financial stability, return on assets, liquidity ratio, online advertising market size, as well as the share of intangible assets in the structure of assets and the amount of research costs. development and capital investments. The constructed scoring model was tested on the Mail.ru Group company (from 12.10.2021 — VK). Practical significance of the research results includes in the fact that the developed model can be applied not only for assessing creditworthiness, but also as one of the express methods of risk management in an organization.
About the Authors
E. I . Gabova
Plekhanov Russian University of Economics
Russian Federation
Competing Interests:
Russian Federation
Ekaterina I. Gabova - master, research analyst
Moscow
Competing Interests:
The authors have no conflicts of interest to declare
N. A. Kazakova
Plekhanov Russian University of Economics
Russian Federation
Competing Interests:
Russian Federation
Natalia A. Kazakova - Dr. Sci. (Econ.), professor
Moscow
Competing Interests:
The authors have no conflicts of interest to declare
References
1. Ivanter V. V., Porfiryev B. N., Sorokin D. E., Eskindarov M. A., Maslennikov V. V., Shirov A. A. et al. How to boost the development of the Russian economy: Priority actions (suggestions for the Main activities of the State until 2024). Finance: Theory and Practice. 2018;22(7):4–15. DOI: 10.26794/2587–5671–2018–0–0–4–15
2. Kazakova N. A., Bolvachev A. I., Gendon A. L., Golubeva G. F. Monitoring economic security in the region based on indicators of sustainable development Studies on Russian Economic Development. 2016;27(6):650–660. DOI: 10.1134/S 1075700716060058 (In Russ.: Problemy prognozirovaniya. 2016;(6):42–55.).
3. Karminsky A. M., Khromova E. Increase of banks’ credit risks forecasting power by the usage of the set of alternative models. Russian Journal of Economics. 2018;4(2):155–174.
4. Karminsky A. M. Credit ratings and their modeling. Moscow: NRU HSE Publ.; 2017. 351 p. (In Russ.).
5. Karminsky A. M., Khromova E. Extended modeling of banks’ credit ratings. Procedia Computer Science. 2016;91:201–210. DOI: 10.10’16/j.procs.2016.07.058
6. Karminsky A. M., Khromova E. Modelling banks’ credit ratings of international agencies. Eurasian Economic Review. 2016;6(3):341–363. DOI: 10.1007/s40822–016–0058–5
7. Fedotova M. A., Tazikhina T. V., Nadezhdina Y. V., Raeva I. V. Problems of determining the cost of collateral in the conditions of implementation Basel II, III Standards in Russia. Journal of Reviews on Global Economics. 2018;7:662–667. DOI: 10.6000/1929–7092.2018.07.60
8. Novikova N. Yu. Topical issues of managing the bank’s corporate credit risk in the conditions of coronacrisis. Finansovyi biznes = Financial Business. 2020;(6):155–156. (In Russ.).
9. Munguti V. M., Ngali R. M. Evaluating credit worthiness of small and growing technology businesses. The University Journal. 2020;2(1):81–91. URL: https://daea.or.ke/wp-content/uploads/2020/03/TUJ-21_Munguti-Ngali-81-91.pdf
10. Safi R., Lin Z. Using non-financial data to assess the creditworthiness of businesses in online trade. In: Proc. 19th Pacific Asia conf. on information systems (PACIS 2014). 2014. URL: https://core.ac.uk/download/pdf/301363028.pdf
11. Kazakova N. A., Kuzmina-Merlino I. Financial benchmarking as an airline competitiveness assessment tool. In: Proc. 15th Int. strategic management conf. (ISMC 2019). (Poznan, 27–29 June, 2019). London: European Publisher Ltd; 2019:288–298. (European Proceedings of Social and Behavioural Sciences. Vol. 71). DOI: 10.15405/ epsbs.2019.10.02.26
12. Zhevaga A. A., Karminskii A. M., Kuznetsov I. V., Morgunov A. V. Modeling the probability of default of corporate borrowers. Upravlenie korporativnymi finansami. 2016;(1):64–78. (In Russ.).
13. Tatarinova L. V., Kravchenko A. E. Optimization of the loan portfolio of a commercial bank through industry diversification. Biznes. Obrazovanie. Pravo = Business. Education. Law. 2021;(1):119–124. (In Russ.). DOI: 10.25683/VOLBI.2020.54.108
14. Rakhaev V. A. Developing credit risk assessment methods to make loss provisions for potential loans. Finance: Theory and Practice. 2020;24(6):82–91. DOI: 10.26794/2587–5671–2020–24–6–82–91
15. Kazakova N. The use of analytical procedures in audit and assessment of economic activities. Vestnik Finansovogo universiteta = Bulletin of the Financial University. 2017;21(2):113–120. (In Russ.).
16. Beugelsdijk S., Ambos B., Nell P. C. Conceptualizing and measuring distance in international business research: Recurring questions and best practice guidelines. Journal of International Business Studies. 2018;49(9):1113–1137. DOI: 10.1057/s41267–018–0182–4
17. Harjadi D., Yuniawan A., Abdurrahman A., Dananjoyo R., Filatrovi E. W., Arraniri I. Product characteristics, market competitive strategies, and SMEs performance: Testing their relationships. The Journal of Asian Finance, Economics and Business. 2020;7(10):613–620. DOI: 10.13106/jafeb.2020.vol7.no10.613
18. Cherkasova V. A., Slepushenko G. A. The impact of digitalization on the financial performance of Russian companies. Finance: Theory and Practice. 2021;25(2):128–142. DOI: 10.26794/2587–5671–2021–25–2–128–142
19. Teplova T. V., Sokolova T. V., Teplov A. S. Intellectual capital of Russian companies as a driver of reducing the cost of debt. Zhurnal Novoi ekonomicheskoi assotsiatsii = Journal of the New Economic Association. 2017;(4):107–134. (In Russ.). DOI: 10.31737/2221–2264–2017–36–4–5
20. Artemenko D. A., Zenchenko S. V. Digital technologies in the financial sector: Evolution and major development trends in Russia and abroad. Finance: Theory and Practice. 2021;25(3):90–101. DOI: 10.26794/2587–5671–2021–25–3–90–101
Review
For citations:
Gabova E.I., Kazakova N.A. Methods of Rating IT -Sector Companies by Level of Risks of Creditworthiness. Finance: Theory and Practice. 2022;26(4):124-138. https://doi.org/10.26794/2587-5671-2022-26-4-124-138
Views:
491
Email this article 