• Login
    • Login
    Advanced Search
    View Item 
    •   UoN Digital Repository Home
    • Theses and Dissertations
    • Faculty of Arts & Social Sciences, Law, Business Mgt (FoA&SS / FoL / FBM)
    • View Item
    •   UoN Digital Repository Home
    • Theses and Dissertations
    • Faculty of Arts & Social Sciences, Law, Business Mgt (FoA&SS / FoL / FBM)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A Prototype Artificial Neural Network to Assist in Credit Card Ii Applications Assessment at Visa Card

    Thumbnail
    Date
    1994
    Author
    Mulamula, Christian B
    Type
    Thesis
    Language
    en
    Metadata
    Show full item record

    Abstract
    This paper describes the construction of a prototype Artificial Neural Network to assist in credit card applications assessment for VISA card at the National Bank. ,The Artificial Neural Network was constructed using a neural network development \'tool, InfiNet, implemented in language C. Using the Backpropagation learning rule the network was able to learn from vector patterns it was exposed to. The project report is divided into five sections. Section One introduces the use and management of credit cards and hence the need to perform assessment on applications before issuing a credit card. Section Two is dedicated to literature review. The objective of the literature review is to give an overview of Neural Network theory which a number of readers may not be familiar with. Section Three describes the tools used in the development process and data collection. Section Four discusses howthe prototype Artificial Neural Network was designed and developed. It specifies all the ANN parameters. Section Five closes the discussion. One definite conclusion emerging from this work is that Neural Networks are a useful tool in modelling expert decision making without having to perform the very challenging and time consuming task of knowledge elucidation required to build an Expert system. However, unlike Expert Systems they do cannot explain their
    URI
    http://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/40403
    Citation
    Master of Bussiness Administration
    Publisher
    Univesity of Nairobi
     
    School of Bussiness
     
    Collections
    • Faculty of Arts & Social Sciences, Law, Business Mgt (FoA&SS / FoL / FBM) [24587]

    Copyright © 2022 
    University of Nairobi Library
    Contact Us | Send Feedback

     

     

    Useful Links
    UON HomeLibrary HomeKLISC

    Browse

    All of UoN Digital RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Copyright © 2022 
    University of Nairobi Library
    Contact Us | Send Feedback