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A time-dependent proportional hazards survival model for credit risk analysis / J.-K. Im in Journal of the operational research society (JORS), Vol. 63 N° 3 (Mars 2012) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 63 N° 3 (Mars 2012) . - pp. 306–321 Titre : A time-dependent proportional hazards survival model for credit risk analysis Type de document : texte imprimé Auteurs : J.-K. Im, Auteur ; D. W. Apley, Auteur ; C. Qi, Auteur Année de publication : 2012 Article en page(s) : pp. 306–321 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Risk  Predicting  consumer  credit  risk  Failure  models  Survival  analysis  for  credit  risk  modelling  Data  analysis  Estimating  survival  models Index. décimale : 001.424 Résumé : In the consumer credit industry, assessment of default risk is critically important for the financial health of both the lender and the borrower. Methods for predicting risk for an applicant using credit bureau and application data, typically based on logistic regression or survival analysis, are universally employed by credit card companies. Because of the manner in which the predictive models are fit using large historical sets of existing customer data that extend over many years, default trends, anomalies, and other temporal phenomena that result from dynamic economic conditions are not brought to light. We introduce a modification of the proportional hazards survival model that includes a time-dependency mechanism for capturing temporal phenomena, and we develop a maximum likelihood algorithm for fitting the model. Using a very large, real data set, we demonstrate that incorporating the time dependency can provide more accurate risk scoring, as well as important insight into dynamic market effects that can inform and enhance related decision making. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n3/abs/jors201134a.html [article] A time-dependent proportional hazards survival model for credit risk analysis [texte imprimé] / J.-K. Im, Auteur ; D. W. Apley, Auteur ; C. Qi, Auteur . - 2012 . - pp. 306–321. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 63 N° 3 (Mars 2012) . - pp. 306–321 Mots-clés : Risk  Predicting  consumer  credit  risk  Failure  models  Survival  analysis  for  credit  risk  modelling  Data  analysis  Estimating  survival  models Index. décimale : 001.424 Résumé : In the consumer credit industry, assessment of default risk is critically important for the financial health of both the lender and the borrower. Methods for predicting risk for an applicant using credit bureau and application data, typically based on logistic regression or survival analysis, are universally employed by credit card companies. Because of the manner in which the predictive models are fit using large historical sets of existing customer data that extend over many years, default trends, anomalies, and other temporal phenomena that result from dynamic economic conditions are not brought to light. We introduce a modification of the proportional hazards survival model that includes a time-dependency mechanism for capturing temporal phenomena, and we develop a maximum likelihood algorithm for fitting the model. Using a very large, real data set, we demonstrate that incorporating the time dependency can provide more accurate risk scoring, as well as important insight into dynamic market effects that can inform and enhance related decision making. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n3/abs/jors201134a.html