Monetary loss surveillance for credit models.
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Data
2016
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Resumo
There is a vast collection of statistical methodologies devoted to
measure the customer’s credit risk.Well-knownstatistical techniques are
logistic regression, genetic algorithms, and support vector machines,
among others. However, there is a lack of statistical tools for monitoring
monetary losses implied by a given credit model in operation. This
article introduces a sequential procedure to favor such monitoring. Our
method favors early detection of increased expected monetary losses.
Analytical expressions are derived for the calculation of the statistical
power performance of the proposed method. An application for a credit
portfolio of a German bank is offered.
Descrição
Palavras-chave
Hypothesis testing, Risk management, Sequential analysis
Citação
SILVA, I. R.; BARROS, V. B. M. Monetary loss surveillance for credit models. Sequential Analysis-Design Methods and Applications, v. 35, p. 347-357, 2016. Disponível em: <http://www.tandfonline.com/doi/abs/10.1080/07474946.2016.1206379?journalCode=lsqa20>. Acesso em: 16 jan. 2018.