Credit scoring analysis

• Autor(a) principal: Puertas Medina, Rosa
• Data de Publicação: 2013
• Outros Autores: Selva, Maria Luisa Martí
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista de Administração de Empresas
• Texto Completo: https://bibliotecadigital.fgv.br/ojs/index.php/rae/article/view/30041
• topic: Credit scoring; logit; discriminant analysis; classification trees; cross-validation; Clasificación crediticia; logit; análisis discriminante; árboles de clasificación; validación cruzada; Classificação de crédito; logit; análise discriminante; árvores de classificação; validação cruzada

The problem of unpaid bank debts is becoming increasingly important in developed countries. Many empirical works are being published in an attempt to find a model capable of determining as accurately as possible whether an individual requesting a loan will be able to pay it back. This paper analyses the predicting capability of one non-parametric and two parametric models. As regards the former, the often-overlooked problem of overlearning is also tackled using the cross-validation technique. Furthermore, a three-level grading of loan applications is proposed depending on their likely performance: grant, refuse, or doubtful hence subject to manual consideration by bank staff.