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Bio-inspired intelligence for credit scoring

Author

Listed:
  • Yorgos Goletsis
  • Themis P. Exarchos
  • Christos D. Katsis

Abstract

The application of quantitative techniques for the determination of credit worthiness, i.e., the credit scoring, is a major research field for bankers and academics as it can bring about significant savings to finance institutions whilst minimising their exposure to risk. In the current work, the applicability of recent developments in machine learning techniques is examined; specifically biologically inspired techniques mimicking natural ants, bird flocking and immune system cells are applied. Experimental results are presented on three real world credit scoring datasets. Comparative results with commonly used artificial intelligence and statistical classifiers verify the suitability of the newly examined methods.

Suggested Citation

  • Yorgos Goletsis & Themis P. Exarchos & Christos D. Katsis, 2011. "Bio-inspired intelligence for credit scoring," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 2(1/2), pages 32-49.
    • Handle: RePEc:ids:ijfmkd:v:2:y:2011:i:1/2:p:32-49
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