A Discriminant Analysis of Insurance Companies in Ukraine
Journal Title: Financial Markets, Institutions and Risks - Year 2017, Vol 1, Issue 4
Abstract
Determining and forecasting the financial situation of insurance companies of Ukraine has become an important issue of financial supervision in view of the need to ensure the sustainability of the financial sector and reduce the negative impact of the insolvency of insurance companies. Given the significant number of bankruptcies of insurance companies in Ukraine in recent years, a discriminatory method may be applied to improve off-site financial supervision. The paper analyzes the advantages and disadvantages of discriminatory models developed for companies producing goods and providing non-financial services to banking institutions and insurance companies. It is substantiated that in order to improve the quality of estimation and forecasting of the financial state of insurance companies in Ukraine, the development of a discriminant model should take into account the domestic specificity of the insurance business. The scientific work defines the stages of development and testing of the quality of a discriminant model for determining the financial status of insurance companies in Ukraine. For the development of a discriminant model, taking into account the existing statistical base, 31 indicators of activity of 12 insurance companies for 2015 were selected. The selection of statistical indicators for use as factors in a discriminant model was performed on the basis of a two-choice F-test, a Farrar-Globard algorithm, a matrix of pair coefficients of correlation. A discriminatory model for determining the financial status of insurance companies in Ukraine included net returns on equity, asset turnover ratios, insurance risk rates, and changes in equity. The application of the model allows you to determine whether the insurance company has a satisfactory or unsatisfactory financial condition. Approval of the developed discriminant model has proven its high quality.
Authors and Affiliations
Viktoriia Riashchenko, Tetiana Bochkarova
Keywords
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- EP ID EP522926
- DOI 10.21272/fmir.1(4).65-73.2017
- Views 71
- Downloads 0
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