TITLE

МЕТОДЫ ТЕОРИИ НЕЧЕТКИХ МНОЖЕСТВ В КРЕДИТНОМ СКОРИНГЕ

AUTHOR(S)
ВОЛКОВА, Елена Сергеевна; ГИСИН, Владимир Борисович; СОЛОВЬЕВ, Владимир Игоревич
PUB. DATE
September 2017
SOURCE
Finance & Credit;sep2017, Vol. 23 Issue 35, p2088
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Importance This article provides an overview of the current state of research related to the application of fuzzy set theory and fuzzy logic in credit scoring. Objectives The article aims to describe and classify fuzzy set theory and fuzzy logic methods used in modern credit scoring models. Methods To perform the tasks, we have studied relevant scientific publications on the article subject presented in Google Scholar. Results The article presents a description and analysis of the basic methods of fuzzy set theory used in credit scoring. Conclusions and Relevance The application of fuzzy sets and fuzzy logic in the models of credit scoring allows for flexible models that allow for a natural and comprehensible interpretation. The most promising direction is the use of fuzzy inference systems.
ACCESSION #
125477976

 

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