A fuzzy credibility model to estimate the Operational Value at Risk using internal and external data of risk events
- Submitting institution
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De Montfort University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11062
- Type
- D - Journal article
- DOI
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10.1016/j.knosys.2018.06.007
- Title of journal
- Knowledge-Based Systems
- Article number
- -
- First page
- 98
- Volume
- 159
- Issue
- -
- ISSN
- 0950-7051
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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5
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Operational Risk (the possibility of suffering losses due to failed processes, inadequate human behaviour or external events; its consequences can lead to global financial crises) is currently tackled by only few select experts. Industry still lacks models based on qualitative information, risk management profiles and the ability to integrate different databases of events. We contribute significantly with a first model to estimate the operational value at risk of an organisation by working with two different databases that contain internal available data and external or observed data; allowing organisations to estimate and determine the behaviour of the risk value over time.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -