124530 - Identification of failing banks using clustering with self-organising neural networks.pdf (484.79 kB)
Identification of failing banks using clustering with self-organising neural networks
conference contribution
posted on 2023-05-24, 18:20 authored by Michael NegnevitskyMichael NegnevitskyThis 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 ScienceVolume
108CEditors
P Koumoutsakos, M Lees, V Krzhizhanovskaya, J Dongarra, P SlootPagination
1327-1333ISSN
1877-0509Department/School
School of EngineeringPublisher
Elsevier BVPlace of publication
NetherlandsEvent title
International Conference on Computational ScienceEvent Venue
Zurich, SwitzerlandDate of Event (Start Date)
2017-06-12Date of Event (End Date)
2017-06-14Rights 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/Repository Status
- Open