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Time varying and dynamic models for default risk in consumer loans
Author(s) -
Crook Jonathan,
Bellotti Tony
Publication year - 2010
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/j.1467-985x.2009.00617.x
Subject(s) - econometrics , default , covariate , markov chain , portfolio , kalman filter , factor analysis , economics , computer science , panel data , dynamic factor , financial economics , artificial intelligence , machine learning , finance
Summary. We review the incorporation of time varying variables into models of the risk of consumer default. Lenders typically have data which are of a panel format. This allows the inclusion of time varying covariates in models of account level default by including them in survival models, panel models or ‘correction factor’ models. The choice depends on the aim of the model and the assumptions that can be plausibly made. At the level of the portfolio, Merton‐type models have incorporated macroeconomic and latent variables in mixed (factor) models and Kalman filter models whereas reduced form approaches include Markov chains and stochastic intensity models. The latter models have mainly been applied to corporate defaults and considerable scope remains for application to consumer loans.