Modeling consumer loan default prediction using neural netware

In this paper a loan default prediction model was constricted using two attribute detection functions, resulting in two data-sets with reduced attributes and the original data-set. A supervised two-layer feed-forward network, with sigmoid hidden neurons and output neurons is used to produce the prediction model. Back propagation learning algorithm was used for the network. Furthermore three different training algorithms were used to train the neural networks. The neural networks are trained using real world credit application cases from the German bank datasets which has 1000 cases; each case with 24 numerical attributes; upon which the decision is based. The aim of this paper was to compare between the resulting models produced from using different training algorithms, scaled conjugate gradient backpropagation, Levenberg-Marquardt algorithm and One-step secant backpropagation (SCG, LM and OSS). This study show that although there is no great difference between LM and SCG but still LM gives better results. The attribute reduction function used helped to produced models quickly and more accurately.

I. Introduction

Credit risk is one of the most studied and researched areas in banking. An accurate lending decisions system is an important reason for the bank profitability. Although techniques of credit measurement had advanced still it is a large risk [1]. The aim of this paper is applying data mining technique on German bank real world credit application cases datasets which has 1000 cases; each case with 24 numerical attributes. The creditability of a customer for loan giving depend on several parameters, such parameters include credit history, Installment rate, employment&etc. The remaining parts of this paper are organized as follows. In section 2 “Related Work” a summary of related work and short definitions of data mining techniques used. In section 3 “Methodology”, it describes the methods and ways of applying the used technique. In section 4 “Experimental result” describes the data used in the study and introduce the results of the experiment. In section 5 “Discussion”, we discuss the results of the experiment. In section 6 “Conclusion” where the whole research is concluded.