Mortgage data mining

Abstract

This paper reports a preliminary investigation of the use of modern data mining tools for mortgage scoring. Using IBM's Intelligent Miner (a data mining toolbox), we built a model of serious delinquency on a sample of data from Mortgage Information Corporation's Loan Performance System, which contains over 20 million loans with a volume of over $1.6 trillion. Currently, two technologies prevail in mortgage scoring: logistic regression, a very old and very simple method, and neural networks, newer and more complex types of models that can be extremely difficult to interpret. The radial basis function (RBF) algorithm in Intelligent Miner combines the mathematical complexity and generality of neural networks with a comprehensible visualization that explains the RBF model. Due to the performance and understandability of the RBF model, as well as other unique technologies not described here, the Intelligent Miner should be a useful tool for mortgage bankers, facilitating development of customized systems for mortgage scoring and other mortgage banking applications.