Credit Prediction Using Transfer of Learning via Self-Organizing Maps to Neural Networks

Abstract

For financial institutions, the ability to predict or forecast business failures is crucial, as incorrect decisions can have direct financial consequences. Credit prediction and credit scoring are the two major research problems in the accounting and finance domain. A variety of pattern recognition techniques including neural networks, decision trees and support vector machines have been applied to predict whether borrowers are in danger of bankruptcy and whether they should be considered a good or bad credit risk.