CREDIT SCORING MODELING WITH STATE-DEPENDENT SAMPLE SELECTION: A COMPARISON STUDY WITH THE USUAL LOGISTIC MODELING

Autor: Carlos R. Diniz, P.H.D. Ferreira, Francisco Louzada

Publikováno v: Pesquisa Operacional, Vol 35, Iss 1, Pp 39-56 (2015)
Pesquisa Operacional, Volume: 35, Issue: 1, Pages: 39-56, Published: APR 2015
Pesquisa Operacional v.35 n.1 2015
Pesquisa operacional
Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification mod

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http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382015000100039&lng=en&tlng=en

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