A multi-objective approach for the prediction of loan defaults

  • Authors:

  • Oluwarotimi Odeh;Praveen Koduru;Sanjoy Das;Allen M. Featherstone;Stephen M. Welch

  • Affiliations:

  • Kansas State University, Manhattan, KS;Kansas State University, Manhattan, KS;Kansas State University, Manhattan, KS;Kansas State University, Manhattan, KS;Kansas State University, Manhattan, KS

  • Venue:
  • Proceedings of the 9th annual conference on Genetic and evolutionary computation
  • Year:
  • 2007

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Abstract

Credit institutions are seldom faced with problems dealing with single objectives. Often, decisions involving optimizing two or more competing goals simultaneously need to be made, and conventional optimization routines and models are incapable of handling the problems. This study applies Fuzzy dominance based Simplex Genetic Algorithm (a multi-objective evolutionary optimization algorithm) in generating decision rules for predicting loan default in a typical credit institution.