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.
Nai Ruscone, M., Bramante, R., Spani, P., Credit risk measurement and ethical issue: someevidences from the italian banks, in Cladag 2013. 9th Meeting of the Classification and Data Analysis Group. Book of Abstracts, (Milano, 18-20 September 2013), Cleup, Modena 2013: 1-4 [http://hdl.handle.net/10807/53341]
Credit risk measurement and ethical issue: some evidences from the italian banks
Nai Ruscone, Marta;Bramante, Riccardo;
2013
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.
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