Bobyl' V.V.Dnepropetrovsk National University of Railway Transport Named After Academician V. Lazaryan, Dnepropetrovsk, Republic of Ukraine Vladimir_bobyl@list.ru
The article states that the current financial crisis dictates the objective need to further investigate the problem of identifying the credit risk of a borrower. It considers the use of a neuro-fuzzy scoring model in the assessment of individuals’ and legal entities’ solvency, and defines borrower’s solvency ratios in case of maximum and minimum credit risk. The author makes a conclusion that the application of neural networks in the scoring models of a bank is especially effective when historical data are not enough for a statistical model creation, or when qualitative factors are introduced into a model, which can be estimated only by expertise.
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