Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12258/2481
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dc.contributor.authorKunitsyna, N. N.-
dc.contributor.authorКуницына, Н. Н.-
dc.contributor.authorKunitsyn, I. I.-
dc.contributor.authorКуницын, И. И.-
dc.date.accessioned2018-07-26T11:50:09Z-
dc.date.available2018-07-26T11:50:09Z-
dc.date.issued2018-
dc.identifier.citationKunitsyna, N; Britchenko, I; Kunitsyn, I. REPUTATIONAL RISKS, VALUE OF LOSSES AND FINANCIAL SUSTAINABILITY OF COMMERCIAL BANKS // ENTREPRENEURSHIP AND SUSTAINABILITY ISSUES. - 2018. - Том 5. - Выпуск 4. - Стр.: 943-955ru
dc.identifier.urihttp://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=6&SID=E1UydfjF9YiY38ek5xJ&page=1&doc=1-
dc.identifier.urihttps://dspace.ncfu.ru:443/handle/20.500.12258/2481-
dc.description.abstractCurrently, under the conditions of permanent financial risks that hamper the sustainable economic growth in the fmancial sector, the development of evaluation and risk management methods both regulated by Basel II and III and others seem to be of special importance. The reputation risk is one of significant risks affecting reliability and credibility of commercial banks. The importance of reputation risk management and the quality of their assessment remain relevant as the probability of decrease in or loss of business reputation influences the financial results and the degree of customers', partners' and stakeholders' confidence. By means of imitating modeling based on Bayesian Networks and the fuzzy data analysis, the article characterizes the mechanism of reputation risk assessment and possible losses evaluation in banks by plotting normal and lognormal distribution functions. Monte-Carlo simulation is used to calculate the probability of losses caused by reputation risks. The degree of standardized histogram similarity is determined on the basis of the fuzzy data analysis applying Hamming distance method. The tree-like hierarchy based on the OWA-operator is used to aggregate the data with Fishburne's coefficients as the convolution scales. The mechanism takes into account the impact of criteria, such as return on equity, goodwill value, the risk assets ratio, the share of the productive assets in net assets, the efficiency ratio of interest bearing liabilities, the risk ratio of credit operations, the funding ratio and reliability index on the business reputation of the bank. The suggested methods and recommendations might be applied to develop the decision-making mechanism targeted at the implementation of reputation risk management system in commercial banks as well as to optimize risk management technologiesru
dc.language.isoenru
dc.publisherENTERPRENEURSHIP & SUSTAINABILITY CENTERru
dc.relation.ispartofseriesENTREPRENEURSHIP AND SUSTAINABILITY ISSUES-
dc.subjectReputation risksru
dc.subjectCommercial bankru
dc.subjectBusiness reputationru
dc.subjectSustainable developmentru
dc.subjectValue of lossesru
dc.subjectEconomic modelingru
dc.subjectRisk levelru
dc.titleREPUTATIONAL RISKS, VALUE OF LOSSES AND FINANCIAL SUSTAINABILITY OF COMMERCIAL BANKSru
dc.typeСтатьяru
vkr.amountСтр.: 943-955ru
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