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A New Novel Cluster based Analysis of Bank's Customer Data with Self-Organized Map Networks
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 82 - Number 7 |
| Year of Publication: 2013 |
| Authors: Seyeyd Reza Khaze, Emita Davoudi Takiyeh, Isa Maleki, Farhad Soleimanian Gharehchopogh |
10.5120/14127-1631
|
Seyeyd Reza Khaze, Emita Davoudi Takiyeh, Isa Maleki, Farhad Soleimanian Gharehchopogh . A New Novel Cluster based Analysis of Bank's Customer Data with Self-Organized Map Networks. International Journal of Computer Applications. 82, 7 ( November 2013), 13-18. DOI=10.5120/14127-1631
Abstract
In the current global competing environment, creation of knowledge base and the use of it have been advantageous for the banks and the financial institutions and accounting and are being transformed to a strategic tool for competing among them and so data mining has been understood more and more in this field lately. In the today competing globe, banks and the financial institutions are trying to reach the advantage and be better than the others. Also, except execution of the business processes, the creation of the data knowledge and the use of it advantageous for the bank is being transformed to a strategic tool for competing. Taking into consideration this necessity, we have applied the Self-Organized Map (SOM) network in some cases of citizens in the banks of West Azerbaijan Province located at Republic Islamic of Iran. It is essential to cluster based solidarity analysis among of the specifications of customers to find common behavior points of them. However, it could be used to maintain the customers and find the new ones by the high responsible of programming of the banks. This approach leads to higher benefits and efficiencies in extracting and mining the likes and the wants of the customers. The results of the clustering analysis showed that the perspective of the customer about bank services and the effect of the electronic banking in banks selection, hold very similar junction patterns.
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