Reject inference in survival analysis by augmentation / J. Banasik in Journal of the operational research society (JORS), Vol. 61 N° 3 (Mars 2010)  

Public ISBD [article]  inJournal of the operational research society (JORS) > Vol. 61 N° 3 (Mars 2010) . - pp. 473–485 Titre : Reject inference in survival analysis by augmentation Type de document : texte imprimé Auteurs : J. Banasik, Auteur ; J. Crook, Auteur Année de publication : 2011 Article en page(s) : pp. 473–485 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Credit scoring Reject inference Augmentation Survival analysis Proportional hazard Index. décimale : 001.424 Résumé : The literature suggests that the commonly used augmentation method of reject inference achieves no appreciable benefit in the context of logistic and probit regression models. Ranking is not improved and the ability to discern a correct cut-off is undermined. This paper considers the application of augmentation to profit scoring applicants by means of survival analysis and by the Cox proportional hazard model, in particular. This new context involves more elaborate models answering more specific questions such as when will default occur and what will be its precise financial implication. Also considered in this paper is the extent to which the rejection rate is critical in the potential usefulness of reject inference and how augmentation meets that potential. The conclusion is essentially that augmentation achieves negative benefits only and that the scope for reject inference in this context pertains mainly to circumstances where a high proportion of applicants have been rejected. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n3/abs/jors2008180a.html [article] Reject inference in survival analysis by augmentation [texte imprimé] / J. Banasik, Auteur ; J. Crook, Auteur . - 2011 . - pp. 473–485. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 61 N° 3 (Mars 2010) . - pp. 473–485 Mots-clés : Credit scoring Reject inference Augmentation Survival analysis Proportional hazard Index. décimale : 001.424 Résumé : The literature suggests that the commonly used augmentation method of reject inference achieves no appreciable benefit in the context of logistic and probit regression models. Ranking is not improved and the ability to discern a correct cut-off is undermined. This paper considers the application of augmentation to profit scoring applicants by means of survival analysis and by the Cox proportional hazard model, in particular. This new context involves more elaborate models answering more specific questions such as when will default occur and what will be its precise financial implication. Also considered in this paper is the extent to which the rejection rate is critical in the potential usefulness of reject inference and how augmentation meets that potential. The conclusion is essentially that augmentation achieves negative benefits only and that the scope for reject inference in this context pertains mainly to circumstances where a high proportion of applicants have been rejected. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n3/abs/jors2008180a.html

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