Please use this identifier to cite or link to this item:
|Spatial correlation in credit risk and its improvement in credit scoring
|Fernandes, Guilherme Barreto
|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 (english terms):
Credit risk companies
regression with errors in variables
|Ciências Sociais Aplicadas
|O INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DO USUÁRIO VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITOR
|Appears in Collections:
|Coleção Insper Working Papers
Files in This Item:
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.