Introduction to Econometrics
Advanced algorithms for neural networks: a C++ sourcebook
Advanced algorithms for neural networks: a C++ sourcebook
Neural network credit scoring models
Computers and Operations Research - Neural networks in business
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Credit Scoring and Its Applications
Credit Scoring and Its Applications
Building credit scoring models using genetic programming
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Managing loan customers using misclassification patterns of credit scoring model
Expert Systems with Applications: An International Journal
A new two-stage hybrid approach of credit risk in banking industry
Expert Systems with Applications: An International Journal
Support vector machine based multiagent ensemble learning for credit risk evaluation
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Behavioral assessment of recoverable credit of retailer's customers
Information Sciences: an International Journal
Business intelligence for delinquency risk management via cox regression
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
The construction of an individual credit risk assessment method: based on the combination algorithms
ICICA'10 Proceedings of the First international conference on Information computing and applications
Driving factors' identification based on derivative process of subjective default credit risk
ICICA'10 Proceedings of the First international conference on Information computing and applications
Is grey relational analysis superior to the conventional techniques in predicting financial crisis?
Expert Systems with Applications: An International Journal
Using data mining to improve assessment of credit worthiness via credit scoring models
Expert Systems with Applications: An International Journal
Credit risk evaluation using neural networks: Emotional versus conventional models
Applied Soft Computing
Probabilistic and discriminative group-wise feature selection methods for credit risk analysis
Expert Systems with Applications: An International Journal
Assessing scorecard performance: A literature review and classification
Expert Systems with Applications: An International Journal
Machine learning-based classifiers ensemble for credit risk assessment
International Journal of Electronic Finance
| Hi-index | 12.06 |
Neural nets have become one of the most important tools using in credit scoring. Credit scoring is regarded as a core appraised tool of commercial banks during the last few decades. The purpose of this paper is to investigate the ability of neural nets, such as probabilistic neural nets and multi-layer feed-forward nets, and conventional techniques such as, discriminant analysis, probit analysis and logistic regression, in evaluating credit risk in Egyptian banks applying credit scoring models. The credit scoring task is performed on one bank's personal loans' data-set. The results so far revealed that the neural nets-models gave a better average correct classification rate than the other techniques. A one-way analysis of variance and other tests have been applied, demonstrating that there are some significant differences amongst the means of the correct classification rates, pertaining to different techniques.