OPERATIONAL IT RISK FORECASTING AND ANALYSIS BASED ON BAYESIAN BELIEF NETWORKS

This article provides the model for IT operational risk analysis, which is based on Bayesian networks. The model allows to predict IT risk losses depending on software quality, IT staff experience and utilized testing practices. The model is provided with hands-on example. In this example, predictiv...

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Autor principal:	Grant S. Petrosyan
Formato:	article
Lenguaje:	RU
Publicado:	Plekhanov Russian University of Economics 2018
Materias:	operational risk management it incident software testing operational value at risk bayesian network sensitivity analysis bayesian inference Economics as a science HB71-74
Acceso en línea:	https://doaj.org/article/ae543036cc634a179061cd0e9c95b013
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id	oai:doaj.org-article:ae543036cc634a179061cd0e9c95b013
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spelling	oai:doaj.org-article:ae543036cc634a179061cd0e9c95b0132021-11-15T05:20:46ZOPERATIONAL IT RISK FORECASTING AND ANALYSIS BASED ON BAYESIAN BELIEF NETWORKS2413-28292587-925110.21686/2413-2829-2018-2-154-160https://doaj.org/article/ae543036cc634a179061cd0e9c95b0132018-03-01T00:00:00Zhttps://vest.rea.ru/jour/article/view/471https://doaj.org/toc/2413-2829https://doaj.org/toc/2587-9251This article provides the model for IT operational risk analysis, which is based on Bayesian networks. The model allows to predict IT risk losses depending on software quality, IT staff experience and utilized testing practices. The model is provided with hands-on example. In this example, predictive Bayesian inference and sensitivity analysis are performed to get a visual representation of the impact of different input variables on the IT operational losses. The abductive Bayesian inference is performed to analyze risk events and to localize root sources of these events. The model is implemented by means of RStudio and AgenaRisk tools. Results of the work can be used in practical work of banks and its technical departments to predict IT operational losses.Grant S. PetrosyanPlekhanov Russian University of Economicsarticleoperational risk managementit incidentsoftware testingoperational value at riskbayesian networksensitivity analysisbayesian inferenceEconomics as a scienceHB71-74RUВестник Российского экономического университета имени Г. В. Плеханова, Vol 0, Iss 2, Pp 154-160 (2018)
institution	DOAJ
collection	DOAJ
language	RU
topic	operational risk management it incident software testing operational value at risk bayesian network sensitivity analysis bayesian inference Economics as a science HB71-74
spellingShingle	operational risk management it incident software testing operational value at risk bayesian network sensitivity analysis bayesian inference Economics as a science HB71-74 Grant S. Petrosyan OPERATIONAL IT RISK FORECASTING AND ANALYSIS BASED ON BAYESIAN BELIEF NETWORKS
description	This article provides the model for IT operational risk analysis, which is based on Bayesian networks. The model allows to predict IT risk losses depending on software quality, IT staff experience and utilized testing practices. The model is provided with hands-on example. In this example, predictive Bayesian inference and sensitivity analysis are performed to get a visual representation of the impact of different input variables on the IT operational losses. The abductive Bayesian inference is performed to analyze risk events and to localize root sources of these events. The model is implemented by means of RStudio and AgenaRisk tools. Results of the work can be used in practical work of banks and its technical departments to predict IT operational losses.
format	article
author	Grant S. Petrosyan
author_facet	Grant S. Petrosyan
author_sort	Grant S. Petrosyan
title	OPERATIONAL IT RISK FORECASTING AND ANALYSIS BASED ON BAYESIAN BELIEF NETWORKS
title_short	OPERATIONAL IT RISK FORECASTING AND ANALYSIS BASED ON BAYESIAN BELIEF NETWORKS
title_full	OPERATIONAL IT RISK FORECASTING AND ANALYSIS BASED ON BAYESIAN BELIEF NETWORKS
title_fullStr	OPERATIONAL IT RISK FORECASTING AND ANALYSIS BASED ON BAYESIAN BELIEF NETWORKS
title_full_unstemmed	OPERATIONAL IT RISK FORECASTING AND ANALYSIS BASED ON BAYESIAN BELIEF NETWORKS
title_sort	operational it risk forecasting and analysis based on bayesian belief networks
publisher	Plekhanov Russian University of Economics
publishDate	2018
url	https://doaj.org/article/ae543036cc634a179061cd0e9c95b013
work_keys_str_mv	AT grantspetrosyan operationalitriskforecastingandanalysisbasedonbayesianbeliefnetworks
_version_	1718428701214900224

OPERATIONAL IT RISK FORECASTING AND ANALYSIS BASED ON BAYESIAN BELIEF NETWORKS

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