Template-type: ReDIF-Paper 1.0
Author-Name: María Jesús Segovia Vargas
Author-Workplace-Name:
 Departamento de Economía Financiera y Contabilidad I (Economía Financiera y Actuarial). Universidad Complutense 
	de Madrid.
Author-Workplace-Homepage:
 https://www.ucm.es/economia-financiera-y-actuarial
Author-Name: José Antonio Gil Fana
Author-Workplace-Name:
 Departamento de Economía Financiera y Contabilidad I (Economía Financiera y Actuarial). Universidad Complutense 
	de Madrid.
Author-Workplace-Homepage:
 https://www.ucm.es/economia-financiera-y-actuarial
Author-Name: Antonio José Heras Martínez
Author-Workplace-Name:
 Departamento de Economía Financiera y Contabilidad I (Economía Financiera y Actuarial). Universidad Complutense 
	de Madrid.
Author-Workplace-Homepage:
 https://www.ucm.es/economia-financiera-y-actuarial
Author-Name: José Luis Vilar Zanón
Author-Workplace-Name:
 Departamento de Economía Financiera y Contabilidad I (Economía Financiera y Actuarial). Universidad Complutense 
	de Madrid.
Author-Workplace-Homepage:
 https://www.ucm.es/economia-financiera-y-actuarial
Author-Name: Alicia Sanchis Arellano
Author-Workplace-Name:
 Facultad de Ciencias Económicas y Empresariales. Universidad Complutense de Madrid.
Title: Using rough sets to predict insolvency of Spanish non-life insurance companies 
Abstract: Insolvency of insurance companies has been a concern of several parties stemmed from the perceived need to protect the 
	general public and to try to minimize the costs associated to this problem such as the effects on state insurance guaranty 
	funds or the responsibilities for management and auditors. Most methods applied in the past to predict business failure in 
	insurance companies are techniques of statistical nature and use financial ratios as explicative variables. These variables do 
	not normally satisfy statistical assumptions so we propose an approach to predict insolvency of insurance companies based on 
	Rough Set Theory. Some of the advantages of this approach are: first, it is a useful tool to analyse information systems 
	representing knowledge gained by experience; second, elimination of the redundant variables is got, so we can focus on minimal 
	subsets of variables to evaluate insolvency and the cost of the decision making process and time employed by the decision maker 
	are reduced; third, a model consisted of a set of easily understandable decision rules is produced and it is not necessary the 
	interpretation of an expert and, fourth, these rules based on the experience are well supported by a set of real examples so 
	this allows the argumentation of the decisions we make.
	This study completes previous researches for bankruptcy prediction based on Rough Set Theory developing a prediction model for 
	Spanish non-life insurance companies and using general financial ratios as well as those that are specifically proposed for 
	evaluating insolvency of insurance sector.
	The results are very encouraging in comparison with discriminant analysis and show that Rough Set Theory can be a useful tool 
	for parties interested in evaluating insolvency of an insurance firm.
Keywords: Business failure; Insolvency; Insurance companies; Rough set; Discriminant analysis.
Length: 21 pages

Creation-Date: 2003 
Number: 03-02
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doctra03-02.txt
File-URL: https://eprints.ucm.es/id/eprint/6801/1/0302.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doctra:03-02