دانلود مقاله ISI انگلیسی شماره 80376
ترجمه فارسی عنوان مقاله

مدل سازی سطح دانش برای مدیریت ریسک سیستماتیک در موسسات مالی

عنوان انگلیسی
Knowledge level modeling for systemic risk management in financial institutions
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
80376 2011 11 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 38, Issue 4, April 2011, Pages 3528–3538

ترجمه کلمات کلیدی
ریسک سیستماتیک؛ مدل سازی سطح دانش؛ هستی شناسی؛ حل مدل مشکل؛ بحران وام
کلمات کلیدی انگلیسی
Systemic risk; Knowledge level modeling; Ontology; Problem solving model; Subprime crisis
پیش نمایش مقاله
پیش نمایش مقاله  مدل سازی سطح دانش برای مدیریت ریسک سیستماتیک در موسسات مالی

چکیده انگلیسی

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.