Title: Credit risk assessment: a comparison of the performances of the linear discriminant analysis and the logistic regression

Authors: Aldo Levy; Riad Baha

Addresses: Interdisciplinary Laboratory for Research in the Science of Action, Conservatoire National des Arts et Métiers, 40, Rue des Jeuneurs, 75002 Paris, France ' Interdisciplinary Laboratory for Research in the Science of Action, Conservatoire National des Arts et Métiers, 40, Rue des Jeuneurs, 75002 Paris, France

Abstract: The prediction of credit risk and borrowers solvency has been widely discussed in the financial and accounting literature whatever the international financial accounting standards (Levy et al., 2016). Various methods are used to build prediction models and can be adapted according to the country, the sector of activity and the nature of the data used. These methods have shown their effectiveness compared to traditional financial analysis for companies classification. This paper aims to compare the classification performances of the logistic regression (LR) model with those of the linear discriminant analysis (LDA) one on a SMEs sample belonging to the Algerian private sector.

Keywords: credit risk; solvency of borrowers; SMEs failure; performances; classification; linear discriminant analysis; LDA; logistic regression.

DOI: 10.1504/IJESB.2021.112265

International Journal of Entrepreneurship and Small Business, 2021 Vol.42 No.1/2, pp.169 - 186

Accepted: 13 Jun 2019
Published online: 06 Jan 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article