Modeling the efficiency of top Arab banks: A DEA-neural network approach

Authors:
Mohamed M. Mostafa
Affiliations:
Auburn University, College of Business, 415 West Magnolia Avenue, Auburn, AL 36849, United States
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

Citing 10
Cited 4

Probabilistic neural networks

Neural Networks
Symbolic and Neural Learning Algorithms: An Experimental Comparison

Machine Learning
The unpredictability of standard back propagation neural networks in classification applications

Management Science
Profitability and Marketability of the Top 55 U.S. Commercial Banks

Management Science - Special issue on the performance of financial Institutions
Dynamics of Data Envelopment Analysis: Theory of Systems Efficiency

Dynamics of Data Envelopment Analysis: Theory of Systems Efficiency
Benchmarks of the Efficiency of Bank Branches

Interfaces
A Data Envelopment Analysis of the Operational Efficiency of Bank Branches

Interfaces
Modelling small-business credit scoring by using logistic regression, neural networks and decision trees: Research Articles

International Journal of Intelligent Systems in Accounting and Finance Management
The use of data mining and neural networks for forecasting stock market returns

Expert Systems with Applications: An International Journal
Classification of freeway traffic patterns for incident detection using constructive probabilistic neural networks

IEEE Transactions on Neural Networks

Short Communication: A note on the modeling the efficiency of top Arab banks

Expert Systems with Applications: An International Journal
Measuring and categorizing technical efficiency and productivity change of commercial banks in Taiwan

Expert Systems with Applications: An International Journal
Measuring productive efficiency of horticultural greenhouses in Iran: A data envelopment analysis approach

Expert Systems with Applications: An International Journal
Measuring energy efficiency performance of China's transport sector: A data envelopment analysis approach

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	12.06

Visualization

Abstract

This study investigates the efficiency of top Arab banks using two quantitative methodologies: data envelopment analysis and neural networks. The study uses a probabilistic neural network (PNN) and a traditional statistical classification method to model and classify the relative efficiency of top Arab banks. Accuracy indices are used to assess the classification accuracy of the models. Results indicate that the predictive accuracy of NN models is quite similar to that of traditional statistical methods. The study shows that the NN models have a great potential for the classification of banks' relative efficiency due to their robustness and flexibility of modeling algorithms. From a policy perspective, this study highlights the economic importance of encouraging increased efficiency throughout the banking industry in the Arab world.