• DocumentCode
    253455
  • Title

    An ontology driven credit risk scoring model

  • Author

    Arsovski, Sasa ; Markoski, Branko ; Pecev, Predrag ; Ratgeber, Ladislav ; Petrov, Nikola

  • fYear
    2014
  • fDate
    19-21 Nov. 2014
  • Firstpage
    301
  • Lastpage
    305
  • Abstract
    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.
  • Keywords
    decision making; financial management; investment; ontologies (artificial intelligence); public finance; risk management; client application evaluation; client scoring; credit risk management; decision-making support; default risk; development components; domain knowledge; government development fund; integrated ontological model; investment risk; ontology driven credit risk scoring model; political components; social components; standard commercial bank methods; Cognition; Decision making; Decision support systems; Government; Investment; Mathematical model; Ontologies; Credit scoring model; Ontology; decision support systems; development funds;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Informatics (CINTI), 2014 IEEE 15th International Symposium on
  • Conference_Location
    Budapest
  • Type

    conf

  • DOI
    10.1109/CINTI.2014.7028694
  • Filename
    7028694