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Формирование новой системы риск-менеджмента кредитных организаций

Формирование новой системы риск-менеджмента кредитных организаций

Abstract

The article is devoted to the research of prospects of analysis techniques of enhancement of bor-rowers credit scoring at the expense of functionality application of artificial neural networks at the analysis of an external environment of borrowers (business environment). Application of essentially new model for an estimation of level of credit scoring would allow, in partnership with the state, to perform institutional modeling of a business environment, proceeding from the valid requirements of the real sector of economy.

Статья посвящена исследованию перспектив совершенствования методик анализа кредитоспособности заемщика за счет использования функционала искусственных нейронных сетей при анализе внешней среды заемщиков (бизнес-среды). Использование принципиально новой модели оценки уровня кредитоспособности позволит, в партнерстве с государством, осуществлять институциональное моделирование бизнес-среды, исходя из действительных потребностей реального сектора экономики.

Keywords

БАНКИ, ГОСУДАРСТВО, БИЗНЕС, БИЗНЕС-СРЕДА, РИСКИ КРЕДИТОСПОСОБНОСТИ, ОЦЕНКА КРЕДИТОСПОСОБНОСТИ, НЕСТАНДАРТНОЕ СОБЫТИЕ, УПРАВЛЕНИЕ НАДЕЖНОСТЬЮ БАНКА, ИННОВАЦИОННОЕ РАЗВИТИЕ

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold