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Published in: Soft Computing 16/2019

03-07-2018 | Methodologies and Application

A model towards global demographics: an application—a universal bank branch geolocator based on branch size

Author: Julia García Cabello

Published in: Soft Computing | Issue 16/2019

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Abstract

Branch size strongly depends on branch cash holdings. However, while any exhaustive study into branch cash holdings must include demographics around branches, there are major variations when defining demographics according to “local” parameters, as opposed to “internationally accepted” ones. This wide fluctuation in definitions makes cross-border comparisons very difficult. The present paper intends to overcome these difficulties by developing a global spatial model that uses cash holdings as a major determinant of branch size and where geographical concepts are replaced by “internationally accepted” notions. Specifically, the contributions of this paper are twofold: firstly, it presents a theoretical model (based on Markov and Gibbs random fields) to analyse the branch cash holdings from a global spatial standpoint. Secondly, it introduces a universal branch geolocator based around a decision model that redesigns the bank branch network according to branch size. Importantly, the model variables (including branch size as the main criterion) can be replaced/expanded as needed through the use of a highly versatile decision-making tool that can be applied to a wide range of contexts, even non-banking ones as long as they are influenced by demographics.

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Footnotes
1
A heavy retail area will require much more cash than a predominantly industrial area where firms do not deal with much cash.
 
2
As major determinant of branch size.
 
3
A week could be as an instance of time unit.
 
4
That means that the current study is not focused on the temporal stochastic process of cash holdings’ movements through time but on the spatial stochastic process, \(\{\hbox {CH}_b, b\in \hbox {BN}\}\).
 
5
We must bear in mind that there are many criteria to quantify the size of a branch amongst bank managers: maximum cash holdings allowed, volume of deposits, volume of credits, number of business/private clients, number of staff etc.
 
6
Size may be also replaced as the criterion used, as will be evidenced throughout the paper. This will increase the versatility of the proposed model so that it can be applied to a wider range of scenarios. Actually, the generality of the current approach is one of its best features, since it can be adjusted as required (see Sect. 6 for further details).
 
7
For example, the entity may need to reinforce their current set of branches with a given volume of cash holdings.
 
8
This is a future research project within a foreseeable period of time.
 
9
Recall that the neighbourhood of a branch is formed by those branches with the same/a very similar size, where the degree of similarity is defined by managers.
 
10
There are other ways of grouping branches such as configuring the branch network through multi-location operations in order to diversify business and hedge against risks.
 
11
Standing for all required branch features.
 
Literature
go back to reference Allahi S, Mobin M, Vafadarnikjoo A, Salmon C (2015) An integrated AHP-GIS-MCLP method to locate bank branches. In: Proceedings of the 2015 industrial and systems engineering research conference. ISBN: 978-098376244-7 Allahi S, Mobin M, Vafadarnikjoo A, Salmon C (2015) An integrated AHP-GIS-MCLP method to locate bank branches. In: Proceedings of the 2015 industrial and systems engineering research conference. ISBN: 978-098376244-7
go back to reference André M, Mahy G, Lejeune P, Bogaert J (2014) Toward a synthesis of the concept and a definition of the zones in the urban-rural gradient. Biotechnol Agron Soc 18(1):61–74 André M, Mahy G, Lejeune P, Bogaert J (2014) Toward a synthesis of the concept and a definition of the zones in the urban-rural gradient. Biotechnol Agron Soc 18(1):61–74
go back to reference Cinar N (2009) A decision support model for bank branch location selection. World Acad Sci Eng Technol 60:126–131 Cinar N (2009) A decision support model for bank branch location selection. World Acad Sci Eng Technol 60:126–131
go back to reference Wainwright MJ, Jordan MI (2008) Graphical models, exponential families, and variational inference. Found Trends\(^{\textregistered }\) Mach Learn 1(1–2):1–305 ISBN: 978-1-60198-184-4 Wainwright MJ, Jordan MI (2008) Graphical models, exponential families, and variational inference. Found Trends\(^{\textregistered }\) Mach Learn 1(1–2):1–305 ISBN: 978-1-60198-184-4
Metadata
Title
A model towards global demographics: an application—a universal bank branch geolocator based on branch size
Author
Julia García Cabello
Publication date
03-07-2018
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 16/2019
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3362-z

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