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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">innovation</journal-id><journal-title-group><journal-title xml:lang="ru">Информация и инновации</journal-title><trans-title-group xml:lang="en"><trans-title>Information and Innovations</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1994-2443</issn><issn pub-type="epub">2949-2157</issn><publisher><publisher-name>МЦНТИ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.31432/1994-2443.2025.17</article-id><article-id custom-type="elpub" pub-id-type="custom">innovation-326</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ЭКОНОМИКА И ИННОВАЦИИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Economy and Innovations</subject></subj-group></article-categories><title-group><article-title>Трансформация российских финансовых и банковских сервисов через применение искусственного интеллекта: текущие тенденции и стратегические перспективы</article-title><trans-title-group xml:lang="en"><trans-title>Transformation of financial and banking services through the use of artificial intelligence: current trends and strategic prospects</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6370-3000</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Умаров</surname><given-names>Х. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Umarov</surname><given-names>K. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Хусан Сунатуллаевич Умаров, канд. экон. наук, доц.</p><p>проспект Вернадского, 76, Москва, 119454</p></bio><bio xml:lang="en"><p>Khusan Sunatullaevich Umarov, Cand. Sci. (Econ), Associate Prof.</p><p>76, Prospect Vernadskogo, Moscow, 119454</p></bio><email xlink:type="simple">khusan0000@bk.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Московский государственный институт международных отношений (университет) МИД Российской Федерации</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Moscow State Institute of International Relations, Ministry of Foreign Affairs of the Russian Federation (MGIMO University)</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>10</day><month>04</month><year>2026</year></pub-date><volume>20</volume><issue>4</issue><fpage>5</fpage><lpage>24</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Умаров Х.С., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Умаров Х.С.</copyright-holder><copyright-holder xml:lang="en">Umarov K.S.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://journal.icsti.int/jour/article/view/326">https://journal.icsti.int/jour/article/view/326</self-uri><abstract><p>Актуальность исследования обусловлена высоким интересом со стороны экономического и бизнес-сообщества, руководителей государственного и частного секторов к инновационному финансовому инструментарию, широким вводом искусственного интеллекта в десятках стран мира для решения разнообразного спектра задач. Цель. Изучение влияния искусственного интеллекта на развитие российского финансового сектора с помощью анализа возможностей, которые он способен предоставить не только представителям финансовых институтов, менеджерам по инновациям, риск-менеджерам. Методы. Использован комплекс теоретических методик, среди которых статистический анализ, формализация, абстрагирование, ретроспективный анализ. Результаты. Приведены не только конкурентные преимущества, но и потенциальные барьеры на пути успешной автоматизации бизнес-процессов в области управления инвестиционными активами, кредитования, страхования, риск-менеджмента. Проведена классификация инновационного инструментария по изучению структурированных и неструктурированных данных, включая современные антифрод-решения, инструменты для скоринга клиентов, средства автоматизации бизнес-процессов и персонализации финансовых услуг и решений. Выводы. Важно вдумчивое, поэтапное стратегическое внедрение средств искусственного интеллекта в российский финансовый сектор для разработки инновационных продуктов и решений. Необходимо следование инструментов интеллектуальной аналитики и финансового мониторинга правовым, юридическим, экономическим и этическим нормам. Одной из проблем внедрения средств искусственного интеллекта признается обеспечение надежности сохранения персональных данных пользователей и грамотное отражение участившихся кибератак.</p></abstract><trans-abstract xml:lang="en"><p>Purpose. The relevance of this study is driven by the high interest in innovative financial tools among the economic and business communities, as well as public and private sector leaders, and the widespread adoption of artificial intelligence in dozens of countries worldwide to solve a diverse range of problems. Objective: To study the impact of artificial intelligence on the development of the Russian financial sector by analyzing the opportunities it can offer not only to representatives of financial institutions, innovation managers, and risk managers. Methods: A combination of theoretical methods was used, including statistical analysis, formalization, abstraction, and retrospective analysis. Results: The study describes not only competitive advantages but also potential barriers to the successful automation of business processes in investment asset management, lending, insurance, and risk management. A classification of innovative tools for studying structured and unstructured data is provided, including modern anti-fraud solutions, customer scoring tools, business process automation tools, and personalization of financial services and solutions. Conclusions: A thoughtful, phased, strategic implementation of artificial intelligence tools in the Russian financial sector is essential for the development of innovative products and solutions. Intelligent analytics and financial monitoring tools must comply with legal, regulatory, economic, and ethical standards. Ensuring the secure storage of user personal data and the effective response to increasingly frequent cyberattacks are recognized as one of the challenges of implementing artificial intelligence tools.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>искусственный интеллект</kwd><kwd>финансовые услуги</kwd><kwd>нейронные сети</kwd><kwd>машинное обучение</kwd><kwd>мошенничество</kwd></kwd-group><kwd-group xml:lang="en"><kwd>artificial intelligence</kwd><kwd>financial services</kwd><kwd>neural networks</kwd><kwd>machine learning</kwd><kwd>fraud</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Farishy R. The Use of Artificial Intelligence in Banking Industry. International Journal of Social Service and Research. 2023;7(3):1724-1731. https://doi.org/10.46799/ijssr.v3i7.447</mixed-citation><mixed-citation xml:lang="en">Farishy R. 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