Knowledge level modeling for systemic risk management in financial institutions

  • Authors:

  • Kang Ye;Jiaqi Yan;Shanshan Wang;Huaiqing Wang;Baiqi Miao

  • Affiliations:

  • Research Center, Shanghai Stock Exchange, 528 Pudong Road, Shanghai, 200120, China;Department of Information Systems, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong;College of Computer Science, Inner Mongolia University, Inner Mongolia, China;Department of Information Systems, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong;Department of Finance and Statistics, University of Science and Technology of China, 96 Jinzhai Road, Hefei, China

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

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Abstract

The current subprime mortgage crisis is a typical case for systemic risk in financial institutions. In order to further our understanding and communication about systemic risk management (SRM) in financial institutions, this paper proposes a knowledge level model (KLM) for systemic risk management in financial institutions. There are two parts considered in the proposed KLM: ontologies and problem solving method (PSM). Ontologies are adopted to represent a knowledge base of KLM, which integrates top level ontology and domain level ontologies. And then the problem solving method is given to show the reasoning process of this knowledge. The symbol level of KLM is also discussed which integrates OWL, SWRL and JESS. Further, the discussion about Lehman Brother's Minibonds case in 2008 is provided to illustrate how proposed KLM is used in practice. With these, first, they will enhance the interchange of information and knowledge sharing for SRM within a financial institution. Second, they will assist knowledge base development for SRM design, for which a prototype of financial systemic risk management decision support system is given in this study. Third, they will support coordination among different institutions by using standardized vocabularies. And finally, from the design science perspective, the whole proposed framework could be meaningful to models in other domains.