Statistical Methods in the Financial Risk Assessment

Student: Petrova Svetlana

Supervisor: Andrey M. Emelyanov

Faculty: Faculty of Economics, Management, and Business Informatics

Educational Programme: Economics (Bachelor)

Final Grade: 10

Year of Graduation: 2019

The main task of banks is the efficient allocation of capital, which is impossible without a qualitative assessment of risks. In this paper, the key components of financial risks are reviewed, and risk management methods applied in Sberbank are analyzed. The empirical part of the work is presented by constructing and measuring credit prediction models based on logistic regression and a neural network with consideration of the main advantages and disadvantages of each of the approaches. Thus, as a result of this study, key financial indicators were identified that have a significant impact on the company's probability of default, and a forecast was made of the probable creditworthiness of large and medium-sized borrowers, which will allow the bank to reduce the risks associated with the default on cash.

Full text (added May 20, 2019)

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