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Spatial correlation in credit risk and its improvement in credit scoring

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  • Guilherme Barreto
  • Fernandes Rinaldo Artes

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.

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  • Guilherme Barreto & Fernandes Rinaldo Artes, 2013. "Spatial correlation in credit risk and its improvement in credit scoring," Business and Economics Working Papers 180, Unidade de Negocios e Economia, Insper.
    • Handle: RePEc:aap:wpaper:180
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