PREDICTING BANK FAILURES: A NEURAL NETWORK APPROACH
作者:
KARYAN TAM,
MELODY KIANG,
期刊:
Applied Artificial Intelligence
(Taylor Available online 1990)
卷期:
Volume 4,
issue 4
页码: 265-282
ISSN:0883-9514
年代: 1990
DOI:10.1080/08839519008927951
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
The purpose of this paper is to present a neural network approach to predicting bank failures and to compare it with existing prediction methods. The task of constructing a prediction model is cast as one of training a network with a set of bankruptcy cases. Empirical results show that neural network is a competitive method among existing ones in assessing the likelihood of bank failures, especially in reducing type I misclassification rate. Issues relating to the potential and limitations of.neural network as a modeling tool are also addressed.
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