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Bankruptcy Prediction for Russian Insurance Companies

Student: Kharis Sergey

Supervisor: Maria Veretennikova

Faculty: Faculty of Economic Sciences

Educational Programme: Economics and Statistics (Bachelor)

Year of Graduation: 2018

The purpose of this study consists in analyzing the factors and methods of forecasting the bankruptcy of insurance companies in Russia. In this work the cluster analysis is carried out to study the heterogeneity of insurance companies. Also in the work there are built the classificationmodels for forecasting bankruptcy . In particular, the ridge logistic regression and the Support vector Machine based model are constructed. The hypotheses about the importance of macroeconomic data and accounting for the heterogeneity of the sample for predicting bankruptcy are tested on basis of the obtained models. The accuracy of the models and the first type mistake are used as quality metrics.

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