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The Analysis of Corporate Borrowers’ Creditworthiness with the Application of Scoring Models

Student: Ivchenkova Irina

Supervisor: Natalia V. Gorelaya

Faculty: Faculty of Economic Sciences

Educational Programme: Bachelor

Year of Graduation: 2014

The paper is devoted to the problem of the corporate borrowers’ creditworthiness estimation. The most part of the bank’s revenue consists of the provision of credit services; consequently, in order to derive the maximum profit from this source of income it is essential to estimate all possible ways of credit deal development at the initial stage. The experience of the financial crisis of 2008, the cause of which was the mortgage crisis in the USA, which emerged due to a great deal of outstanding credits with a high risk, makes ponder about the importance of the correct estimation of the borrower’s creditworthiness. Moreover, corporate credit granting occurs in much greater amounts in comparison to private persons’ lending; besides, it makes up a considerable proportion of the overall loans provided by Russian banks.This paper considers the approaches to the corporate borrowers’ creditworthiness estimation as well as describes the genesis of the scoring and widely distributed methods of the scoring model development.In order to find out which of the liquidity ratios have the highest influence on the probability of the bankruptcy, the author develops three scoring models based on the logistic regression, each of which includes only one ratio of this group. Furthermore, these models take into account the companies’ industry on the basis of the industry average return on capital employed. The results of the empirical study demonstrate that among the liquidity ratios the most impact on the bankruptcy probability has the absolute liquidity ratio, whereas the least – the current liquidity ratio. In turn, the factor of the companies’ industry is significant in all three models and in two of them influences the probability of the potential borrower’ bankruptcy the most. Such results indicate the necessity of the scoring models elaboration for each industry individually or for the group of the adjacent industries.Contact information:Tel.: +7 (916) 007-72-72E-mail: i.ivchenkova@gmail.com

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