Comparing classification accuracy of neural networks, binary logit regression and discriminant analysis for insolvency prediction of life insurers

Ernest Goss, Harish Ramchandani

Research output: Contribution to journal › Article

16 Citations (Scopus)

Abstract

Past studies have documented the failure of the Insurance Regulatory Information System (IRIS) to provide adequate warning of insurer financial distress or insolvency. As a result, scholars have examined alternative parametric and non-parametric models to predict insurer insolvency. This study uses a neural network, a non-parametric alternative to past techniques, and shows how this methodology predicts insurer insolvency more effectively than parametric models.

Original languageEnglish
Pages (from-to)1-18
Number of pages18
JournalJournal of Economics and Finance
Volume19
Issue number3
DOIs
StatePublished - Sep 1995

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Insurer
Prediction
Insolvency
Logit regression
Discriminant analysis
Neural networks
Regression analysis
Methodology
Financial distress
Nonparametric model
Insurance
Warning
Information systems
Parametric model

All Science Journal Classification (ASJC) codes

  • Economics, Econometrics and Finance(all)
  • Finance
  • Economics and Econometrics

Cite this

Comparing classification accuracy of neural networks, binary logit regression and discriminant analysis for insolvency prediction of life insurers. / Goss, Ernest; Ramchandani, Harish.

In: Journal of Economics and Finance, Vol. 19, No. 3, 09.1995, p. 1-18.

Research output: Contribution to journal › Article

Goss, E & Ramchandani, H 1995, 'Comparing classification accuracy of neural networks, binary logit regression and discriminant analysis for insolvency prediction of life insurers', Journal of Economics and Finance, vol. 19, no. 3, pp. 1-18. https://doi.org/10.1007/BF02920611
Goss E, Ramchandani H. Comparing classification accuracy of neural networks, binary logit regression and discriminant analysis for insolvency prediction of life insurers. Journal of Economics and Finance. 1995 Sep;19(3):1-18. https://doi.org/10.1007/BF02920611
Goss, Ernest ; Ramchandani, Harish. / Comparing classification accuracy of neural networks, binary logit regression and discriminant analysis for insolvency prediction of life insurers. In: Journal of Economics and Finance. 1995 ; Vol. 19, No. 3. pp. 1-18.
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