Multilayer feedforward networks are universal approximators
Neural Networks
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
The nature of statistical learning theory
The nature of statistical learning theory
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Neural network credit scoring models
Computers and Operations Research - Neural networks in business
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks for Financial Forecasting
Neural Networks for Financial Forecasting
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Knowledge discovery techniques for predicting country investment risk
Computers and Industrial Engineering
Survival Analysis Methods for Personal Loan Data
Operations Research
Genetically Optimized Neural Network Classifiers for Bankruptcy Prediction- An Empirical Study
HICSS '96 Proceedings of the 29th Hawaii International Conference on System Sciences Volume 2: Decision Support and Knowledge-Based Systems
Selecting Bankruptcy Predictors Using a Support Vector Machine Approach
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Asymptotic behaviors of support vector machines with Gaussian kernel
Neural Computation
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
Forecasting stock market movement direction with support vector machine
Computers and Operations Research
Neural network ensemble strategies for financial decision applications
Computers and Operations Research
Computers and Operations Research
Expert Systems with Applications: An International Journal
Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
ACST'07 Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology
Predicting financial activity with evolutionary fuzzy case-based reasoning
Expert Systems with Applications: An International Journal
Support vector machines for credit scoring and discovery of significant features
Expert Systems with Applications: An International Journal
The individual borrowers recognition: Single and ensemble trees
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
The consumer loan default predicting model - An application of DEA-DA and neural network
Expert Systems with Applications: An International Journal
Detecting stock-price manipulation in an emerging market: The case of Turkey
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Credit risk evaluation using neural networks: Emotional versus conventional models
Applied Soft Computing
An application of locally linear model tree algorithm for predictive accuracy of credit scoring
MEDI'11 Proceedings of the First international conference on Model and data engineering
Expert Systems with Applications: An International Journal
Assessing scorecard performance: A literature review and classification
Expert Systems with Applications: An International Journal
Hi-index | 12.07 |
The commencement of the Basel II requirement, popularization of consumer loans and the intense competition in financial market has increased the awareness of the critical delinquency issue for financial institutions in granting loans to potential applicants. In the past few decades, the scheme of artificial neural networks has been successfully applied to the financial field. Recently, the Support Vector Machine (SVM) has emerged as the better neural network in dealing with classification and forecasting problems due to its superior features of generalization performance and global optimum. This study develops a loan evaluation model using SVM to identify potential applicants for consumer loans. In addition to conducting experiments on performance comparison via cross-validation and paired t test, we analyze misclassification errors in terms of Type I and Type II and their effect on selecting network parameters of SVM. The analysis findings facilitate the development of a useful visual decision-support tool. The experimental results using a real-world data set reveal that SVM surpasses traditional neural network models in generalization performance and visualization via the visual tool, which helps decision makers determine appropriate loan evaluation strategies.