IDEAS home Printed from https://ideas.repec.org/a/aes/dbjour/v3y2012i2p23-30.html
   My bibliography  Save this article

Clustering Analysis for Credit Default Probabilities in a Retail Bank Portfolio

Author

Listed:
  • Adela Ioana TUDOR

    (Economic Informatics Department, Academy of Economic Studies, Bucharest, Romania)

  • Adela BÂRA

    (Economic Informatics Department, Academy of Economic Studies, Bucharest, Romania)

  • Elena ANDREI (DRAGOMIR

    (Economic Informatics Department, Academy of Economic Studies, Bucharest, Romania)

Abstract

Methods underlying cluster analysis are very useful in data analysis, especially when the processed volume of data is very large, so that it becomes impossible to extract essential information, unless specific instruments are used to summarize and structure the gross information. In this context, cluster analysis techniques are used particularly, for systematic information analysis. The aim of this article is to build an useful model for banking field, based on data mining techniques, by dividing the groups of borrowers into clusters, in order to obtain a profile of the customers (debtors and good payers). We assume that a class is appropriate if it contains members that have a high degree of similarity and the standard method for measuring the similarity within a group shows the lowest variance. After clustering, data mining techniques are implemented on the cluster with bad debtors, reaching a very high accuracy after implementation. The paper is structured as follows: Section 2 describes the model for data analysis based on a specific scoring model that we proposed. In section 3, we present a cluster analysis using K-means algorithm and the DM models are applied on a specific cluster. Section 4 shows the conclusions.

Suggested Citation

  • Adela Ioana TUDOR & Adela BÂRA & Elena ANDREI (DRAGOMIR, 2012. "Clustering Analysis for Credit Default Probabilities in a Retail Bank Portfolio," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 3(2), pages 23-30, August.
    • Handle: RePEc:aes:dbjour:v:3:y:2012:i:2:p:23-30
    as

    Download full text from publisher

    File URL: http://dbjournal.ro/archive/8/8_3.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Emilia ?I?AN & Adela Ioana TUDOR, 2011. "Conceptual and Statistical Issues Regarding the Probability of Default and Modeling Default Risk," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 2(1), pages 13-22, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mirela Catalina Turkes, 2017. "Cluster Analysis Of Total Assets Provided By Banks From Four Continents," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 4, pages 54-58, August.
    2. Mirela Catalina Türkes, 2017. "Cluster Analysis of Total Assets Provided By Banks from Four Continents," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 3(4), pages 24-28, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:aes:dbjour:v:3:y:2012:i:2:p:23-30. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Adela Bara (email available below). General contact details of provider: https://edirc.repec.org/data/aseeero.html .

      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.