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Identification of failing banks using clustering with self-organising neural networks

conference contribution
posted on 2023-05-23, 08:13 authored by Michael NegnevitskyMichael Negnevitsky
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

Proceedings of INTELLI 2013: The Second International Conference on Intelligent Systems and Applications

Editors

M Negnevitsky, P Lorenz

Pagination

1-5

ISBN

9781627484817

Department/School

School of Engineering

Publisher

Curran Associates, Inc.

Place of publication

Red Hook, NY USA

Event title

INTELLI 2013: The Second International Conference on Intelligent Systems and Applications

Event Venue

Venice, Italy

Date of Event (Start Date)

2013-04-21

Date of Event (End Date)

2013-04-26

Rights statement

Copyright 2013 International Academy, Research, and Industry Association (IARIA)

Repository Status

  • Restricted

Socio-economic Objectives

Industrial energy efficiency

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