IDEAS home Printed from https://ideas.repec.org/a/ids/ijicbm/v32y2024i2p164-186.html
   My bibliography  Save this article

An intelligent multi-level optimisation model for retail loan portfolio

Author

Listed:
  • Srilatha Kappagantula
  • Vikas Srivastava

Abstract

The paper discusses the multi-level portfolio selection problem, which combines hierarchical optimisation of credit portfolio, incorporating regulatory and capital constraints, in the context of emerging retail-banking loans. The proposed model allows for twin objectives of risk minimisation, simultaneously providing scope for maximising returns. The present paper analyses the portfolio optimisation problem, as a holistic 2-level optimisation problem: 1) at loan level, to reduce the default risk; 2) at bank level, to decide the right capital allocation between loan classes. The current study develops a model for multi-level optimisation of loans, and solves the model using multi objective algorithm for allocation of loan data across four retail asset classes, namely small business loans, credit card loans, home loans and auto loans, using a dataset of 229,000 loan records. The multi-level optimised portfolio is compared against the original portfolio for potential gains.

Suggested Citation

  • Srilatha Kappagantula & Vikas Srivastava, 2024. "An intelligent multi-level optimisation model for retail loan portfolio," International Journal of Indian Culture and Business Management, Inderscience Enterprises Ltd, vol. 32(2), pages 164-186.
  • Handle: RePEc:ids:ijicbm:v:32:y:2024:i:2:p:164-186
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=139165
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijicbm:v:32:y:2024:i:2:p:164-186. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=235 .

    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.