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http://ssrn.com/abstract=1519792
 
 

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Default Predictors and Credit Scoring Models for Retail Banking


Evzen Kocenda


Charles University in Prague - CERGE-EI (Center for Economic Research and Graduate Education - Economics Institute); CESifo; University of Michigan at Ann Arbor - The William Davidson Institute; Osteuropa Institut; Centre for Economic Policy Research (CEPR)

Martin Vojtek


Charles University in Prague - CERGE-EI (Center for Economic Research and Graduate Education - Economics Institute)

December 2009

CESifo Working Paper Series No. 2862

Abstract:     
This paper develops a specification of the credit scoring model with high discriminatory power to analyze data on loans at the retail banking market. Parametric and non- parametric approaches are employed to produce three models using logistic regression (parametric) and one model using Classification and Regression Trees (CART, nonparametric). The models are compared in terms of efficiency and power to discriminate between low and high risk clients by employing data from a new European Union economy. We are able to detect the most important characteristics of default behavior: the amount of resources the client has, the level of education, marital status, the purpose of the loan, and the number of years the client has had an account with the bank. Both methods are robust: they found similar variables as determinants. We therefore show that parametric as well as non-parametric methods can produce successful models. We are able to obtain similar results even when excluding a key financial variable (amount of own resources). The policy conclusion is that socio-demographic variables are important in the process of granting credit and therefore such variables should not be excluded from credit scoring model specification.

Number of Pages in PDF File: 53

Keywords: credit scoring, discrimination analysis, banking sector, pattern recognition, retail loans, CART, European Union

JEL Classification: B41, C14, D81, G21, P43

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Date posted: December 7, 2009  

Suggested Citation

Kocenda, Evzen and Vojtek, Martin, Default Predictors and Credit Scoring Models for Retail Banking (December 2009). CESifo Working Paper Series No. 2862. Available at SSRN: http://ssrn.com/abstract=1519792

Contact Information

Evzen Kocenda (Contact Author)
Charles University in Prague - CERGE-EI (Center for Economic Research and Graduate Education - Economics Institute) ( email )
P.O. Box 882
7 Politickych veznu
Prague 1, 111 21
Czech Republic
+420 224005149 (Phone)
+420 22427143 (Fax)
HOME PAGE: http://www.cerge-ei.cz
CESifo
Poschinger Str. 5
Munich, DE-81679
Germany
University of Michigan at Ann Arbor - The William Davidson Institute
724 E. University Ave.
Wyly Hall
Ann Arbor, MI 48109-1234
United States
Osteuropa Institut
Landshuter Str. 4
93047 Regensburg
Germany
Centre for Economic Policy Research (CEPR)
77 Bastwick Street
London, EC1V 3PZ
United Kingdom
Martin Vojtek
Charles University in Prague - CERGE-EI (Center for Economic Research and Graduate Education - Economics Institute) ( email )
Politickych veznu 7
Prague 1, 111 21
Czech Republic
HOME PAGE: http://www.cerge-ei.cz
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