Neural Network for Predicting the Performance of Credit Card Accounts
Ilona Jagielska and
Janusz Jaworski
Computational Economics, 1996, vol. 9, issue 1, 77-82
Abstract:
This paper reports the interim results of an experimental project using neural networks as a decision support tool for credit card risk assessment within a major bank. Two prototype neural network systems have been developed: one which emulates the decisions of the current risk assessment system and another which attempts to predict the performance of credit card accounts based on the accounts historical data. This paper focuses on the development of the neural network model for credit card account performance prediction. The study has shown that such a tool can help in discovering the potential problems with credit card applicants at the very early stage of the credit account life cycle. Citation Copyright 1996 by Kluwer Academic Publishers.
Date: 1996
References: Add references at CitEc
Citations: View citations in EconPapers (2)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:9:y:1996:i:1:p:77-82
Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2
Access Statistics for this article
Computational Economics is currently edited by Hans Amman
More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().