Article2000

Credit scoring using neural and evolutionary techniques

151 citations0/0 files storedIMA Journal of Management Mathematics

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Financial Distress and Bankruptcy Prediction Statistical Methods and Applications Imbalanced Data Classification Techniques

Abstract

This paper compares the predictive performance of linear discriminant analysis, neural networks, genetic algorithms and decision trees in distinguishing between good and slow payers of bank credit card accounts. Predictive models were built using the evolutionary techniques and the results compared with those gained from the discriminant analysis model published in Crook et al. (1992), The Service Industries Journal 12 which uses the same dataset. A range of parameters under the control of the investigator was investigated. We found that the predictive performance of linear discriminant analysis was superior to that of the other three techniques. This is consistent with some studies but inconsistent with others.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 151 citations exist upstream.

References

1996A comparison of neural networks and linear scoring models in the credit union environment 1997Credit-scoring models in the credit-union environment using neural networks and genetic algorithms

Cited by

2005A survey of the issues in consumer credit modelling research 2007A credit scoring model for Vietnam's retail banking market 2012A literature review on the application of evolutionary computing to credit scoring 2018Big Data techniques to measure credit banking risk in home equity loans 2011Credit risk evaluation using a weighted least squares SVM classifier with design of experiment for parameter selection 2011Does segmentation always improve model performance in credit scoring?2014An insight into the experimental design for credit risk and corporate bankruptcy prediction systems 2008Credit scoring using support vector machines with direct search for parameters selection

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.