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Title: Survival mixture models in behavioral scoring
Authors: Alves, B. C.
Dias, J. G.
Keywords: Credit risk
Behavioral scoring
Survival analysis
Mixture models
Issue Date: 2015
Publisher: Pergamon/Elsevier
Abstract: This paper introduces a general framework of survival mixture models (SMMs) that addresses the unobserved heterogeneity of the credit risk of a financial institution's clients. This new behavioral scoring framework contains the specific cases of aggregate and immune fraction models. This general methodology identifies clusters or groups of clients with different risk patterns. The parameters of the model can be explained by independent variables in a regression setting. The application shows the different risk trajectories of clients. Specifically, the time between the first delayed payment and default was best modeled by a three-segment log-normal mixture distribution and a multinomial logit link function. Each segment contains clients with similar risk profiles. The model predicts the most likely risk segment for each new client.
Peer reviewed: yes
DOI: 10.1016/j.eswa.2014.12.036
ISSN: 0957-4174
Accession number: WOS:000356904100008
Appears in Collections:BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica

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