IDEAS home Printed from https://ideas.repec.org/a/spt/apfiba/v7y2017i4f7_4_1.html
   My bibliography  Save this article

Branch Efficiency and Location Forecasting: Application of Ziraat Bank

Author

Listed:
  • Ilker Met
  • Guven Tunalı
  • Ayfer Erkoc
  • Sinan Tanrikulu
  • M. Ozgur Dolgun

Abstract

It is important to if you can’t measure you can’t manage it. With this respect to get qualified information we need a method to big data. The size of Bank and operational data make classical productivity measurement methods impractical. For this reason, the productivity is measured by using data mining approaches. In this project; an analytical solution that enables efficient and productive use of centralized management and sources as well as the automation of location based reporting has been established in order to provide support for branching strategies.JEL classification numbers: C13, C80, G02Keywords: Big Data, Data Mining, Clustering Analysis, Value and Potential Value Segmentation

Suggested Citation

  • Ilker Met & Guven Tunalı & Ayfer Erkoc & Sinan Tanrikulu & M. Ozgur Dolgun, 2017. "Branch Efficiency and Location Forecasting: Application of Ziraat Bank," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-1.
    • Handle: RePEc:spt:apfiba:v:7:y:2017:i:4:f:7_4_1
    as

    Download full text from publisher

    File URL: http://www.scienpress.com/Upload/JAFB%2fVol%207_4_1.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    big data; data mining; clustering analysis; value and potentialâ value segmentation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spt:apfiba:v:7:y:2017:i:4:f:7_4_1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Eleftherios Spyromitros-Xioufis (email available below). General contact details of provider: http://www.scienpress.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.