An analytical framework for monitoring and optimizing bank branch network efficiency / E.H. Smith
Financial institutions make use of a variety of delivery channels for servicing their customers. The primary channel utilised as a means of acquiring new customers and increasing market share is through the retail branch network. The 1990s saw the Internet explosion and with it a threat to branches....
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ndltd-NWUBOLOKA1-oai-dspace.nwu.ac.za-10394-50292014-04-16T03:56:43ZAn analytical framework for monitoring and optimizing bank branch network efficiency / E.H. SmithSmith, Eugene HerbieFinancial industryData miningManagement science techniquesClustering analysisData envelopment analysisDecision tree inductionHomogeneityPositivistic researchQuantitative analysisInterpretative researchQualitative analysisFinancial institutions make use of a variety of delivery channels for servicing their customers. The primary channel utilised as a means of acquiring new customers and increasing market share is through the retail branch network. The 1990s saw the Internet explosion and with it a threat to branches. The relatively low cost associated with virtual delivery channels made it inevitable for financial institutions to direct their focus towards such new and more cost efficient technologies. By the beginning of the 21st century -and with increasing limitations identified in alternative virtual delivery channels, the financial industry returned to a more balanced view which may be seen as the revival of branch networks. The main purpose of this study is to provide a roadmap for financial institutions in managing their branch network. A three step methodology, representative of data mining and management science techniques, will be used to explain relative branch efficiency. The methodology consists of clustering analysis (CA), data envelopment analysis (DEA) and decision tree induction (DTI). CA is applied to data internal to the financial institution for increasing' the discriminatory power of DEA. DEA is used to calculate the relevant operating efficiencies of branches deemed homogeneous during CA. Finally, DTI is used to interpret the DEA results and additional data describing the market environment the branch operates in, as well as inquiring into the nature of the relative efficiency of the branch.Thesis (M.Com. (Computer Science))--North-West University, Potchefstroom Campus, 2010.North-West University2012-01-05T05:56:47Z2012-01-05T05:56:47Z2009Thesishttp://hdl.handle.net/10394/5029en |
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language |
en |
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topic |
Financial industry Data mining Management science techniques Clustering analysis Data envelopment analysis Decision tree induction Homogeneity Positivistic research Quantitative analysis Interpretative research Qualitative analysis |
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Financial industry Data mining Management science techniques Clustering analysis Data envelopment analysis Decision tree induction Homogeneity Positivistic research Quantitative analysis Interpretative research Qualitative analysis Smith, Eugene Herbie An analytical framework for monitoring and optimizing bank branch network efficiency / E.H. Smith |
description |
Financial institutions make use of a variety of delivery channels for servicing their customers. The primary channel utilised as a means of acquiring new customers and increasing market share is through the retail branch network. The 1990s saw the Internet explosion and with it a threat to branches. The relatively low cost associated with virtual delivery channels made it inevitable for financial institutions to direct their focus towards such new and more cost efficient technologies. By the beginning of the 21st century -and with increasing limitations identified in alternative virtual delivery channels, the financial industry returned to a more balanced view which may be seen as the revival of branch networks. The main purpose of this study is to provide a roadmap for financial institutions in managing their branch network. A three step methodology, representative of data mining and management science techniques, will be used to explain relative branch efficiency. The methodology consists of clustering analysis (CA), data envelopment analysis (DEA) and decision tree induction (DTI). CA is applied to data internal to the financial institution for increasing' the discriminatory power of DEA. DEA is used to calculate the relevant operating efficiencies of branches deemed homogeneous during CA. Finally, DTI is used to interpret the DEA results and additional data describing the market environment the branch operates in, as well as inquiring into the nature of the relative efficiency of the branch. === Thesis (M.Com. (Computer Science))--North-West University, Potchefstroom Campus, 2010. |
author |
Smith, Eugene Herbie |
author_facet |
Smith, Eugene Herbie |
author_sort |
Smith, Eugene Herbie |
title |
An analytical framework for monitoring and optimizing bank branch network efficiency / E.H. Smith |
title_short |
An analytical framework for monitoring and optimizing bank branch network efficiency / E.H. Smith |
title_full |
An analytical framework for monitoring and optimizing bank branch network efficiency / E.H. Smith |
title_fullStr |
An analytical framework for monitoring and optimizing bank branch network efficiency / E.H. Smith |
title_full_unstemmed |
An analytical framework for monitoring and optimizing bank branch network efficiency / E.H. Smith |
title_sort |
analytical framework for monitoring and optimizing bank branch network efficiency / e.h. smith |
publisher |
North-West University |
publishDate |
2012 |
url |
http://hdl.handle.net/10394/5029 |
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