dc.contributor.author | Ndungu, Eric T. | |
dc.date.accessioned | 2013-06-26T15:15:12Z | |
dc.date.issued | 2008 | |
dc.identifier.citation | M.Sc (Mathematical Statistics) | en |
dc.identifier.uri | http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/40722 | |
dc.description.abstract | Credit scoring systems are based on statistical and operations research models
that seek to establish the likelihood of future credit behaviour based on information
from past borrowers. Given that the cost of credit risk involves exposures and credit
lifetimes, and that these exposures are amortized through this lifetime, it is important
to understand not just if, but also when credit events are expected.
This paper focuses on the lifetimes of credit exposures relative to voluntary account
closure by borrowers. It also seeks to determine whether a lifetime model can
compete with the logistic model in modeling account closures.
I have shown how the classic Pearson correlation and the Gini coefficient could be
applied to assess model fit, and that the log-logistic survival model performs better
than the logistic model based on the available data. | en |
dc.description.sponsorship | University of Nairobi | en |
dc.language.iso | en | en |
dc.title | A comparison of log-logistic survival model to logistic model in credit risk modelling | en |
dc.type | Thesis | en |
local.publisher | School of Mathematics, University of Nairobi | en |