Fuzzy ARTMAP Neural Network for Classifying the Financial Health of a Firm

  • Anatoli Nachev
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5027)


In this paper, an application, based on data from a popular dataset, shows in an empirical form the strengths and weaknesses of fuzzy ARTMAP neural networks as predictor of corporate bankruptcy. This is an advantageous approach enabling fast learning, self-determination of the network structure and high prediction accuracy. Experiments showed that the fuzzy ARTMAP outperforms statistical techniques and the most popular backpropagation MLP neural networks, all applied to the same dataset. An exhaustive search procedure over the Altman’s financial ratios leads to the conclusion that two of them are enough to obtain the highest prediction accuracy. The experiments also showed that the model is not sensitive to outliers of the dataset. Our research is the first to use fuzzy ARTMAP neural networks for bankruptcy prediction.


data mining neural networks fuzzy ARTMAP 


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  1. 1.
    Altman, E.: Financial Ratios, Discriminant Analysis, and the Prediction of Corporate Bankruptcy. Journal of Finance 23(4), 598–609 (1968)CrossRefGoogle Scholar
  2. 2.
    Bell, T., Ribar, G., Verchio, J.R.: Neural Nets vs. Logistic Regression: a Comparison of each Model’s Ability to Predict Commercial Bank Failures. In: Proc. of the 1990 Deloitte & Touche / University of Kansas Symposium on Auditing Problems, pp. 29–53 (1990)Google Scholar
  3. 3.
    Brigham, E.F., Gapenski, L.C.: Financial Management Theory and Practice. Dryden Press, New York (1991)Google Scholar
  4. 4.
    Carpenter, G., Grossberg, S., Reynolds, J.: ARTMAP: Supervised Real-Time Learning and Classification of Non-stationary Data by a Self-Organizing Neural Network. Neural Networks 6, 565–588 (1991)CrossRefGoogle Scholar
  5. 5.
    Carpenter, G.A., Grossberg, S., Markuzon, N., Reynorlds, J.H., Rosen, D.B.: Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Maps. IEEE Transaction on Neural Networks 3(5), 698–713 (1992)CrossRefGoogle Scholar
  6. 6.
    Coats, P., Fant, L.: Recognizing Financial Distress Patterns Using Neural Network Tool. Financial Management, 142–155 (November 1993)Google Scholar
  7. 7.
    Curram, S., Mingers, J.: Neural Networks, Decision Tree Induction and Discriminant Analysis: an Empirical Comparison. Journal Operational Research 45(4), 440–450 (1994)zbMATHGoogle Scholar
  8. 8.
    Gallinari, P., Thiria, S., Badran, F., Fogelman-Soulie, F.: On the Relations between Discriminant Analysis and Multilayer Perceptrons. Neural Networks 4, 349–360 (1991)CrossRefGoogle Scholar
  9. 9.
    Granger, E., Rubin, A., Grossberg, S., Lavoie, P.: A What-and-Where Fusion Neural Network for Recognition and Tracking of Multiple Radar Emitters. Neural Networks 3, 325–344 (2001)CrossRefGoogle Scholar
  10. 10.
    Grossberg, S.: Adaptive Pattern Recognition and Universal Encoding II: Feedback, expectation, olfaction, and illusions. Biological Cybernetics 23, 187–202 (1976)CrossRefMathSciNetGoogle Scholar
  11. 11.
    Hart, A.: Using Neural Networks for Classification Task. Some Experiments on Datasets and Practical Advice. Journal Operational Research Society 43(3), 215–266 (1992)zbMATHGoogle Scholar
  12. 12.
    Kumar, P., Ravi, V.: Bankruptcy Prediction in Banks and Firms via Statistical and Intelligent Techniques. European Journal of Operational Research 180(1), 1–28 (2007)zbMATHCrossRefGoogle Scholar
  13. 13.
    Lacher, R., Coats, P., Sharma, S., Fantc, L.L.F.: A Neural Network for Classifying the Financial Health of a Firm. European Journal of Operational Research 85, 53–65 (1995)zbMATHCrossRefGoogle Scholar
  14. 14.
    Odom, M., Sharda, R.L.: A Neural Network Model for Bankruptcy Prediction. In: Proceedings of the IEEE International Conference on Neural Networks, pp. 163–168 (1990)Google Scholar
  15. 15.
    Odom, M., Sharda, R.: A Neural Network Model for Bankruptcy Prediction. In: Trippi, R.R., Turban, E. (eds.) Neural Networks in Finance and Investing, Probus (1993)Google Scholar
  16. 16.
    Rahimian, E., Singh, S., Thammachacote, T., Virmani, R.: Bankruptcy prediction by neural networks. In: Trippi, R., Turban, E. (eds.) Neural Networks in Finance and Investing, Probus Publ., Chicago (1993)Google Scholar
  17. 17.
    Serrano-Cinca, C.: Self Organizing Neural Networks for Financial Diagnosis. Decision Support Systems 17, 227–238 (1996)CrossRefGoogle Scholar
  18. 18.
    Wilson, R., Sharda, R.: Bankruptcy prediction using neural networks. Decision Support Systems 11, 431–447 (1994)CrossRefGoogle Scholar
  19. 19.
    Yoon, Y., Swales, G., Margavio, T.: A Comparison of Discriminant Analysis versus Artificial Neural Networks. Journal Operational Research Society 44(1), 51–60 (1993)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Anatoli Nachev
    • 1
  1. 1.Information Systems, Dept. of Accountancy & FinanceNational University of IrelandGalwayIreland

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