Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/6785
Title: An ontology driven credit risk scoring model
Authors: Arsovski S.
Markoski, Branko 
Pecev, Predrag 
Ratgeber L.
Petrović, Nemanja 
Issue Date: 30-Jan-2014
Journal: CINTI 2014 - 15th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings
Abstract: © 2014 IEEE. In this paper, the authors propose a model for credit risk management. Two main aspects of credit risk management are analyzed. The first aspect of this paper discusses techniques for reducing the risk of investments using standard commercial bank methods for client scoring. The second aspect deals with social, political and development components of investment. In this paper, ontology is used to enable the implementation of domain knowledge to support decision-making and client scoring in government development funds. Authors propose an integrated ontological model for evaluating client applications, which incorporates both: the default risk of investment and the development component of the investment.
URI: https://open.uns.ac.rs/handle/123456789/6785
ISBN: 9781479953387
DOI: 10.1109/CINTI.2014.7028694
Appears in Collections:TFZR Publikacije/Publications

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