Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data

Evžen Kočenda and Martin Vojtek ()

Emerging Markets Finance and Trade, 2011, vol. 47, issue 6, 80-98

Abstract: Credit to the private sector has risen rapidly in European emerging markets, but its risk evaluation has been largely neglected. Using retail-loan banking data from the Czech Republic, we construct two credit risk models based on logistic regression and classification and regression trees. Both methods are comparably efficient and detect similar financial and socioeconomic variables as the key determinants of default behavior. We also construct a model without the most important financial variable (amount of resources), which performs very well. This way, we confirm significance of sociodemographic variables and link our results with specific issues characteristic to new EU members.

Keywords: banking sector; CART; credit scoring; discrimination analysis; European Union; pattern recognition; retail loans (search for similar items in EconPapers)
Date: 2011
References: Add references at CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://mesharpe.metapress.com/link.asp?target=contribution&id=J731L4122P636J00 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data (2011)
Working Paper: Default Predictors and Credit Scoring Models for Retail Banking (2009)
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:mes:emfitr:v:47:y:2011:i:6:p:80-98

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/MREE20

Access Statistics for this article

More articles in Emerging Markets Finance and Trade from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().