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Credit Risk Modeling for Different Groups of Borrowes

Student: Anfilova Aleksandra

Supervisor: Natalia V. Gorelaya

Faculty: Faculty of Economic Sciences

Educational Programme: Financial Markets and Financial Institutions (Master)

Year of Graduation: 2021

Credit risk modeling is still one of the most relevant, since there are not many methods and methods for predicting the level of credit risk. A large number of studies are devoted to various methods and methods for assessing and predicting the level of credit risk. At the same time, the question of how credit risk modeling changes from industry to industry remains poorly understood. Whether the same coefficients are affected, or whether there are significant differences. It is also unclear how the very fact of belonging to a particular industry affects the probability of credit risk realization. As part of this work, credit risk was modeled for several groups of corporate borrowers from different industries, and the ability of the constructed models to predict the bankruptcy of companies was tested. A number of differences between the constructed models were also revealed.

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