Title :
A fuzzy clustering approach for the measurement of operational risk
Author :
Scandizzo, Sergio
Author_Institution :
Canadian Imperial Bank of Commerce, Toronto, Ont., Canada
Abstract :
The article studies the application of fuzzy logic techniques to the analysis of operational risk in financial institutions. It suggests an operational risk measurement system which rates the riskiness of the various components of the bank, given an assessment of a set of “risk factors”. The system is based on the AHP methodology to derive appropriate weights for the risk factors involved and on a fuzzy algebra to generate a consistent classification of those components
Keywords :
bank data processing; fuzzy logic; fuzzy set theory; knowledge based systems; pattern clustering; risk management; AHP methodology; Analytic Hierarchy Process; bank; consistent classification; financial institutions; fuzzy algebra; fuzzy clustering approach; fuzzy logic techniques; operational risk measurement; risk factors; riskiness; Algebra; Banking; Business; Electric breakdown; Fuzzy logic; Fuzzy sets; Fuzzy systems; Humans; Risk analysis; Risk management;
Conference_Titel :
Knowledge-Based Intelligent Information Engineering Systems, 1999. Third International Conference
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-5578-4
DOI :
10.1109/KES.1999.820189
