Credit scoring for SME using a manifold supervised learning algorithm

Authors:
Armando Vieira;Bernardete Ribeiro;Ning Chen
Affiliations:
Instituto Superior de Engenharia do Porto, Porto, Portugal;Departamento Engenharia Informática, Universidade de Coimbra, Portugal;Instituto Superior de Engenharia do Porto, Porto, Portugal
Venue:
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Year:
2012

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Abstract

We propose a credit scoring algorithm based on the supervised ISOMAP to rate SME. By projecting the companies balance sheet data into a one dimensional component we obtain a smoother distribution of ratings while increasing the discriminatory capability of each rate in terms of the probability of default. The method is applied to a large dataset of French SME.