Exposición al default: estimación para un portafolio de tarjeta de crédito

Exposure to default: estimation for a credit card portfolio

Carlos Bambino-Contreras and Víctor Morales-Oñate

MPRA Paper from University Library of Munich, Germany

Abstract: This work estimates the exposure at default of a credit card portfolio of an Ecuadorian bank without using the credit conversion factor, a common mechanism used in the expected loss distribution estimation literature and suggested by the Basel Committee. To achieve this goal, the probability distribution of this variable (exposure at default) has been identified so that it can be used in the context of generalized linear models. The results show that the model can be used to make predictions based on assumptions closer to the reality of customer behavior based on the variables used in the regression.

Keywords: Expected loss; Credit risk; Exposure at default; Generalized linear models; Gamma Distribution; Machine Learning (search for similar items in EconPapers)
JEL-codes: C1 G32 (search for similar items in EconPapers)
Date: 2021-12
New Economics Papers: this item is included in nep-big, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/112333/1/MPRA_paper_112333.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:112333

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().