Modelling Default Risk of Credit Institutions Because of their Doubtful Transactions

Student: Dmitrieva Anastasia

Educational Programme: Economics (Bachelor)

Year of Graduation: 2018

The largest share of license revocation is explained by involvement of credit institutions in conducting doubtful transactions. The aim of this study is to model the probability of default of banks precisely because of doubtful transactions. The model is built on the basis of logistic regression. This study uses the sample consisting of observations for 390 Russian banks for the period 2007-2017. The paper’s originality is that, in addition to financial and macroeconomic variables, special indicators are built into the model. As a result, a significant influence of the general business activity ratio and the indicator of the fictitiveness of the loan portfolio on the probability of default was proved. Also, the model with indicators turned out to be more qualitative than the model, which does not include them. The model can be used by clients as a tool for selecting a servicing bank and by counterparties to monitor and minimize the risks of cooperation.

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