This paper presents experimental results of cluster analysis using self organising neural networks for identifying failing banks. The paper first describes major reasons and likelihoods of bank failures. Then it demonstrates an application of a self-organising neural network and presents results of the study. Findings of the paper demonstrate that a self-organising neural network is a powerful tool for identifying potentially failing banks. Finally, the paper discusses some of the limitations of cluster analysis related to understanding of the exact meaning of each cluster.
History
Publication title
Procedia Computer Science
Volume
108C
Editors
P Koumoutsakos, M Lees, V Krzhizhanovskaya, J Dongarra, P Sloot
Pagination
1327-1333
ISSN
1877-0509
Department/School
School of Engineering
Publisher
Elsevier BV
Place of publication
Netherlands
Event title
International Conference on Computational Science
Event Venue
Zurich, Switzerland
Date of Event (Start Date)
2017-06-12
Date of Event (End Date)
2017-06-14
Rights statement
Copyright 2017 The Authors. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) https://creativecommons.org/licenses/by-nc-nd/4.0/