DocumentCode
1782826
Title
Fuzzy credibility for mixing different data sources in evaluating operational risk: Modelling operational risk
Author
Bonet, Isis ; Pena, P. Alejandro ; Lochmuller, Christian ; Patino, Alejandro
Author_Institution
Grupo de Investig. en Ing. del Software y Modelamiento Computacional (GISMOC), Escuela de Ing. de Antioquia - EIA Envigado, Envigado, Colombia
fYear
2014
fDate
18-21 June 2014
Firstpage
1
Lastpage
6
Abstract
After the global financial crisis of 2008 the banking sector has shown a strong interest, internationally and in Colombia, in developing models to manage and measure the risks of business processes and in particular the risk associated with the operations of an organization (operational risk). This article proposes a model based on fuzzy credibility theory in order to mix different data sources for evaluating operational risk. The results of calculating the OpVaR are compared using both, credibility theory and fuzzy credibility. It can be concluded that these results differ, when the membership of the internal data to the external data set is low. In this case the fuzzy model gives more weight to external data compared to the model that applies credibility theory.
Keywords
banking; fuzzy set theory; risk management; Colombia; OpVaR; banking sector; business process; credibility theory; data membership; data source mixing; fuzzy credibility; fuzzy credibility theory; operational risk; operational risk evaluation; operational risk modelling; operational value-at-risk; risk management; risk measurement; Abstracts; Computational modeling; Data models; Media; Silicon; Silicon compounds; Software; OpVaR; credibility theory; fuzzy logic; operational risk;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Systems and Technologies (CISTI), 2014 9th Iberian Conference on
Conference_Location
Barcelona
Type
conf
DOI
10.1109/CISTI.2014.6877030
Filename
6877030
Link To Document