dorsal/arxiv
View SchemaBayesian networks for enterprise risk assessment
| Authors | C. E. Bonafede, P. Giudici |
|---|---|
| Categories | |
| ArXiv ID | physics/0607226 |
| URL | https://arxiv.org/abs/physics/0607226 |
| DOI | 10.1016/j.physa.2007.02.065 |
Abstract
According to different typologies of activity and priority, risks can assume diverse meanings and it can be assessed in different ways. In general risk is measured in terms of a probability combination of an event (frequency) and its consequence (impact). To estimate the frequency and the impact (severity) historical data or expert opinions (either qualitative or quantitative data) are used. Moreover qualitative data must be converted in numerical values to be used in the model. In the case of enterprise risk assessment the considered risks are, for instance, strategic, operational, legal and of image, which many times are difficult to be quantified. So in most cases only expert data, gathered by scorecard approaches, are available for risk analysis. The Bayesian Network is a useful tool to integrate different information and in particular to study the risk's joint distribution by using data collected from experts. In this paper we want to show a possible approach for building a Bayesian networks in the particular case in which only prior probabilities of node states and marginal correlations between nodes are available, and when the variables have only two states.
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"abstract": "According to different typologies of activity and priority, risks can assume\ndiverse meanings and it can be assessed in different ways. In general risk is\nmeasured in terms of a probability combination of an event (frequency) and its\nconsequence (impact). To estimate the frequency and the impact (severity)\nhistorical data or expert opinions (either qualitative or quantitative data)\nare used. Moreover qualitative data must be converted in numerical values to be\nused in the model. In the case of enterprise risk assessment the considered\nrisks are, for instance, strategic, operational, legal and of image, which many\ntimes are difficult to be quantified. So in most cases only expert data,\ngathered by scorecard approaches, are available for risk analysis. The Bayesian\nNetwork is a useful tool to integrate different information and in particular\nto study the risk\u0027s joint distribution by using data collected from experts. In\nthis paper we want to show a possible approach for building a Bayesian networks\nin the particular case in which only prior probabilities of node states and\nmarginal correlations between nodes are available, and when the variables have\nonly two states.",
"arxiv_id": "physics/0607226",
"authors": [
"C. E. Bonafede",
"P. Giudici"
],
"categories": [
"physics.soc-ph"
],
"doi": "10.1016/j.physa.2007.02.065",
"title": "Bayesian networks for enterprise risk assessment",
"url": "https://arxiv.org/abs/physics/0607226"
},
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