The Effect of Gender and Gender-Dependent Factors on the Default Risk
Autori:
Begum CIGSAR, Deniz UNAL
Cod: ISSN: 1583-3410 (print), ISSN: 1584-5397 (electronic)
Dimensiuni: pp. 28-41
How to cite this article:Cigsar, B., Unal, D. (2018). The Effect of Gender and Gender-Dependent Factors on the Default Risk. Revista de Cercetare si Interventie Sociala, 63, 28-41. |
Abstract:
The concept of gender created by the society referencing to biological sex,
and the rules, sanctions, anticipations, offi cials put on it, is a question that crowns
injustice towards women today. This problem has caused and sustained great
injustices and losses not only in daily life but also in economical area. In this
study, it was tried to draw attention to the fact that the study that we are currently
doing are shared so that the society should be shaken as soon as possible and away
from the “gender” perception. The purpose of this study is to identify data mining
classifi cation algorithms that can be used to predict default risks using data on
demographic and socioeconomic characteristics of individuals, to avoid possible
payment diffi culties and to reduce the problems that may arise when lending. Also
going into default risks for women and men are examined and so indeed it was
found that women are more sensitive to their repayments. From this point of view,
variables aff ecting the going into default rate of women were examined.
Keywords:
Big Data, gender, default risk, WEKA, data mining, logistic regression.
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