{"title":"基于概率模型的操作风险估计","authors":"Trofimchuk Oleksandr, Prosiankina-Zharova Tetyana, Bidiuk Petro, Terentiev Oleksandr","doi":"10.1109/AICT50176.2020.9368630","DOIUrl":null,"url":null,"abstract":"Operational risks remain one of the most difficult and relevant issues of risk management for companies which is interested in profitable operation and sustainable development. The aim of the work is analysis of existing solutions and proposes an effective method of forecasting losses from operational risks. Suggested methods are used retrospective analysis of data. Standard methods don’t take into account the causal relationships and uncertainties which are typical for individual enterprises and ineffective. The paper proposes information technology based on the adaptive approach for construction of mathematical models, in particular using Bayesian belief networks, which in turn allow processing the uncertainties caused by the random nature of risk factors.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"282 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Operational risk estimation using probabilistic model\",\"authors\":\"Trofimchuk Oleksandr, Prosiankina-Zharova Tetyana, Bidiuk Petro, Terentiev Oleksandr\",\"doi\":\"10.1109/AICT50176.2020.9368630\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Operational risks remain one of the most difficult and relevant issues of risk management for companies which is interested in profitable operation and sustainable development. The aim of the work is analysis of existing solutions and proposes an effective method of forecasting losses from operational risks. Suggested methods are used retrospective analysis of data. Standard methods don’t take into account the causal relationships and uncertainties which are typical for individual enterprises and ineffective. The paper proposes information technology based on the adaptive approach for construction of mathematical models, in particular using Bayesian belief networks, which in turn allow processing the uncertainties caused by the random nature of risk factors.\",\"PeriodicalId\":136491,\"journal\":{\"name\":\"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)\",\"volume\":\"282 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AICT50176.2020.9368630\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICT50176.2020.9368630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Operational risk estimation using probabilistic model
Operational risks remain one of the most difficult and relevant issues of risk management for companies which is interested in profitable operation and sustainable development. The aim of the work is analysis of existing solutions and proposes an effective method of forecasting losses from operational risks. Suggested methods are used retrospective analysis of data. Standard methods don’t take into account the causal relationships and uncertainties which are typical for individual enterprises and ineffective. The paper proposes information technology based on the adaptive approach for construction of mathematical models, in particular using Bayesian belief networks, which in turn allow processing the uncertainties caused by the random nature of risk factors.