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Искусственный интеллект в банковском деле: обзор применения и потенциал для развития

Искусственный интеллект в банковском деле: обзор применения и потенциал для развития

Abstract

В статье рассматриваются вопросы применения инструментов искусственного интеллекта в условиях развивающейся банковской системы в России и зарубежных странах. Показан рост применения технологий на основе искусственного интеллекта в банкинге, приведены примеры их текущего состояния и модификации, изменений в зависимости от требований времени (кибер-мошенничества, угроз интернет-преступности). Представлены точки зрения различных исследователей на роль и значение, место применения технологий искусственного интеллекта в банках, перечислены также реальные и возможные негативные последствия от внедрения методов и технологий искусственного интеллекта в банковском деле. Выявлено, что технологии искусственного интеллекта используются в банковской системе России, прежде всего, в кредитном процессе, в организации инструментов самообслуживания для клиентов (например, при организации работы банкоматов, создании виртуальных помощников и чат-ботов, позволяющих подобрать персональные предложения по запросу клиентов), и в коммерческих процессах (например, кросс-продажи). В статье приведены предполагаемые направления дальнейшего развития искусственного интеллекта в банковском деле, включая совершенствование методов самообслуживания клиентов банка. Указана возрастающая роль искусственного интеллекта в предупреждении мошеннических действий и мошеннического поведения клиентов, включая виртуальные трансакции, в улучшении обратной связи между банком и клиентом, а также в вопросах предсказания возможных клиентских решений, идентификации их в режиме удаленного доступа.

The article discusses the use of artificial intelligence tools in the conditions of the developing banking system in Russia and foreign countries. The growth in the use of technologies based on artificial intelligence in banking is shown, examples of their current state and modifications, changes depending on the requirements of the time (cyber fraud, threats of Internet crime) are given. The points of view of various researchers on the role and importance, place of application of artificial intelligence technologies in banks are presented, and real and possible negative consequences from the introduction of artificial intelligence methods and technologies in banking are also listed. It has been revealed that artificial intelligence technologies are used in the Russian banking system, primarily in the credit process, in organizing self-service tools for clients (for example, when organizing the operation of ATMs, creating virtual assistants and chat bots that allow you to select personal offers at the request of clients), and in commercial processes (e.g. cross-selling). The article presents the proposed directions for the further development of artificial intelligence in banking, including improving self-service methods for bank clients. The increasing role of artificial intelligence in preventing fraudulent actions and fraudulent behavior of clients, including virtual transactions, in improving feedback between the bank and the client, as well as in predicting possible client decisions and identifying them in remote access mode is indicated.

Keywords

искусственный интеллект, банковское дело, клиент, банковская сфера, данные, банк

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citations
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
Green