Title: Solvency analysis of Tunisian insurance companies using a neural approach

Authors: Nadia Benali; Rochdi Feki

Addresses: Research Unit in Development Economics, Higher School of Commerce, University of Sfax, Route de l'Aéroport Km 4, 3018 Sfax, Tunisia ' Research Unit in Development Economics, Higher School of Commerce, University of Sfax, Route de l'Aéroport Km 4, 3018 Sfax, Tunisia

Abstract: Insolvency within insurance companies has become an important purpose and a major issue of public debate. This reform can play a major role in protecting the general public from the consequences of insolvency. The research presented in this article aims to analyse the situation of Tunisian insurers' solvencies (solvency or insolvency). For this reason, we used the artificial neural network, especially Kohonen maps, in order to classify companies and to predict their financial health. In this paper, we use a sample of 15 insurance companies from 2007 to 2009 by using six financial ratios. It is supposed to realise the solvency of insurance companies. The classification using self-organising maps reflects a multitude of financial situation. The research, using maps outcomes, reveals a considerable contribution to the study of the business characteristics.

Keywords: insurance industry; solvency ratio; required solvency margin; available solvency margin; artificial neural networks; ANNs; Kohonen maps; Tunisia; insolvency; financial ratios; self-organising maps; SOM.

DOI: 10.1504/IJEBR.2015.070978

International Journal of Economics and Business Research, 2015 Vol.10 No.2, pp.112 - 124

Received: 26 Sep 2014
Accepted: 16 Dec 2014
Published online: 04 Aug 2015 *

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