Article
Article name Designing a simulation model of lending to individuals on the basis of the scoring mechanism
Authors
Bibliographic description
Category Economics
DOI 338.45
DOI 10.21209/2227-­9245-­2018-­24-­2-99-107
Article type Scientific
Annotation The paper conducts a critical analysis of the concepts of “credit rating” and “scoring system”. On its basis the structure of the credit rating, which includes five factors: payment history, current debt, length of credit history, new credit and types of loans. As a research tool using simulation, the chosen concept of discrete-event simulation, and the tool – AnyLogic. The paper presents a mathematical model providing a formula for calculation of factors that make up a credit rating. The simulation model consists of two main agents. The agent “Customer” mimics the behavior of individuals when applying for a loan. Basically, the agent presents the logic model the process of customer interaction. The calculation of the credit rating simulation model is carried out using charts of action. The model calculates the main indicators, which include all components of the credit rating, the total amount of the loans, the share of Bank failures in the credit, failure of the client to loan and received proposals for the credit
Key words simulation modeling; discrete event modeling; scoring system; credit rating; business processes; financial-credit system; market mechanism; critical analysis model
Article information Kislitsyn E. Designing a simulation model of lending to individuals on the basis of the scoring mechanism // Transbaikal State University Journal, 2018, vol. 24, no. 2, pp. 99-107
References 1. Gavrilovskaya S. V. Akademicheskij vestnik (Academic Bulletin), 2012, no. 2 , pp. 232–238. 2. Zadorozhnaya T. M. Rossijskoe predprinimatel\'stvo (Journal of Russian entrepreneurship), 2012, no. 14, pp. 85–89. 3. Zakirova E. R., Filippov S. D., Fed\'kovich G. N. Vestnik Buryatskogo gosudarstvennogo universiteta. Ehkonomika i menedzhment (Bulletin of the Buryat state University. Economy and management), 2017, no. 3, pp. 3–8. 4. Maramygin M. S., Tereshkin M. L. Fundamental\'nye issledovaniya (Fundamental research), 2016, no. 9-1, pp. 151–155. 5. Maramygin M. S., Tereshkin M. L. Kant (Kant), 2017, no. 4, pp. 214–219. 6. Sazanova L. A. Izvestiya Ural\'skogo gosudarstvennogo ehkonomicheskogo universiteta (Bulletin of the Ural state University of Economics), 2016, no. 5, pp. 141–147. 7. Silin Y. P., Animica E. G., Novikova N. V. Upravlenec (Manager), 2017, no. 2, pp. 2–11. 8. Surnina N. M., Ilyuhin A. A., Ilyuhina S. V. Izvestiya Ural\'skogo gosudarstvennogo ehkonomicheskogo universiteta (Bulletin of the Ural state University of Economics), 2016, no. 5, pp. 54–65. 9. Amoretti M., Grazioli A., Zanichelli F. Simulation Modelling Practice and Theory (Simulation Modelling Practice and Theory), 2015, vol. 58, pp. 140–156. 10. Durante D., Rossi E., Colagrossi A., Graziani G. Communications in Nonlinear Science and Numerical Simulation (Communications in Nonlinear Science and Numerical Simulation), 2017, vol. 48, pp. 18–38. 11. Yavas D. Y., Hokelek I., Gunsel B. Simulation Modelling Practice and Theory (Simulation Modelling Practice and Theory), 2018, vol. 80, pp. 128–144.
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