Application of profit-based credit scoring models using R

Selcuk Bayraci
Additional contact information
Selcuk Bayraci: R&D Centre, C/S Information Technologies, Istanbul, Turkey

Romanian Statistical Review, 2017, vol. 65, issue 4, 3-28

Abstract: In this study, we applied a profit-based scoring system with using 10 different statistical and machine learning algorithms on a consumer credit data of a Turkish commercial bank. RStudio environment and R packages have been used in data cleaning, feature selection and model implementation processes. The results of the study reveal that artificial neural networks model seems to be superior to other techniques in terms of profit maximization.

Keywords: Data analytics; Credit scoring; Banking; Risk management (search for similar items in EconPapers)
JEL-codes: C01 C40 C87 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.revistadestatistica.ro/wp-content/uploads/2017/11/RRS-4_2017_A01.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rsr:journl:v:65:y:2017:i:4:p:3-28

Access Statistics for this article

More articles in Romanian Statistical Review from Romanian Statistical Review Contact information at EDIRC.
Bibliographic data for series maintained by Adrian Visoiu ().