This paper gives a contribution in variable identification within credit scoring models using Random Forest. Specifically, we provide some insights about the behavior of the variable importance index based on random forests, focusing on the differences between “for-profit” and “not-for-profit” enterprises. We investigate two classical issues of variable selection: the first one is variable extraction for bankruptcy interpretation, whereas the second one is more restrictive and tries to design a good prediction model. Finally we provide an application to a real data set provided by Banca Popolare Etica.

Credit risk measurement and ethical issue: some evidences from the Italian banks

Nai Ruscone, Marta;
2013-01-01

Abstract

This paper gives a contribution in variable identification within credit scoring models using Random Forest. Specifically, we provide some insights about the behavior of the variable importance index based on random forests, focusing on the differences between “for-profit” and “not-for-profit” enterprises. We investigate two classical issues of variable selection: the first one is variable extraction for bankruptcy interpretation, whereas the second one is more restrictive and tries to design a good prediction model. Finally we provide an application to a real data set provided by Banca Popolare Etica.
2013
978-88-6787-117-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1013420
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