Operational Risk Management Using a Fuzzy Logic Inference System
Operational Risk (OR) results from endogenous and exogenous risk factors, as diverse and complex to assess as human resources and technology, which may not be properly measured using traditional quantitative approaches. Engineering has faced the same challenges when designing practical solutions to complex multifactor and non-linear systems where human reasoning, expert knowledge, and imprecise information are valuable inputs. One of the solutions provided by engineering is a Fuzzy Logic Inference System (FLIS). The choice of a FLIS for OR assessment results in a convenient and sound use of qualitative and quantitative inputs, capable of effectively articulating risk management’s identication, assessment, monitoring, and mitigation stages. Different from traditional approaches, the proposed model allows for evaluating mitigation efforts ex-ante, thus avoiding concealed OR sources from system complexity build-up and optimizing risk management resources. Furthermore, because the model contrasts effective with expected OR data, it is able to constantly validate its outcome, recognize environment’s shifts, and issue warning signals.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Volume (Year): 30 (2010)
Issue (Month): ()
|Contact details of provider:|| Postal: 77 Water Street, 10th Floor, New York NY 10005|
Phone: +1 212 284 8600
Web page: http://www.capco.com/
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Isabelle Huault & V. Perret & S. Charreire-Petit, 2007. "Management," Post-Print halshs-00337676, HAL.
When requesting a correction, please mention this item's handle: RePEc:ris:jofitr:1436. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Prof. Shahin Shojai)
If references are entirely missing, you can add them using this form.