Spatial dependence in credit risk and its improvement in credit scoring

Guilherme Barreto Fernandes and Rinaldo Artes ()

European Journal of Operational Research, 2016, vol. 249, issue 2, 517-524

Abstract: Credit scoring models are important tools in the credit granting process. These models measure the credit risk of a prospective client based on idiosyncratic variables and macroeconomic factors. However, small and medium sized enterprises (SMEs) are subject to the effects of the local economy. From a data set with the localization and default information of 9 million Brazilian SMEs, provided by Serasa Experian (the largest Brazilian credit bureau), we propose a measure of the local risk of default based on the application of ordinary kriging. This variable has been included in logistic credit scoring models as an explanatory variable. These models have shown better performance when compared to models without this variable. A gain around 7 percentage points of KS and Gini was observed.

Keywords: Risk analysis; Spatial dependence; SME credit risk; Ordinary kriging; Credit scoring (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (28)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:249:y:2016:i:2:p:517-524

DOI: 10.1016/j.ejor.2015.07.013

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