BANK XIZMATLARIDA SUNʼIY INTELLEKT TEXNOLOGIYALARIDAN FOYDALANISH ISTIQBOLLARI: RISKLAR VA IMKONIYATLAR

Mualliflar

DOI:

https://doi.org/10.60078/2992-877X-2025-vol3-iss11-pp163-169

Annotasiya

Ushbu maqolada tijorat banklarida sun’iy intellekt texnologiyalarini joriy etish jarayonlari, ularning operatsion samaradorlikka, kredit risklarini baholash sifatiga va mijozlarga xizmat ko‘rsatish tizimiga ta’siri ilmiy jihatdan tahlil qilindi. Xalqaro tajribalar O‘zbekiston bank tizimi amaliyoti bilan taqqoslab o‘rganildi. Tadqiqot natijalari SI texnologiyalari bank xarajatlarini kamaytirishi, firibgarlikni aniqlash samaradorligini oshirishi, xizmat ko‘rsatish tezligini yaxshilashi bilan birga, ma’lumotlar sifati, algoritmik shaffoflik va kiberxavfsizlik kabi muammolar mavjudligini ko‘rsatdi. Maqolada ushbu muammolarni bartaraf etish bo‘yicha taklif va tavsiyalar ishlab chiqilgan.

Kalit so‘zlar:

sun’iy intellekt tijorat banklari raqamli transformatsiya kredit risklari

Bibliografik manbalar

Abdukarimov A.E. (2022) Bank tizimida raqamli transformatsiya jarayonlari: muammolar va istiqbollar. – Toshkent: Iqtisodiyot va taʼlim nashriyoti. – 154 b.

Accenture (2022). AI in Banking: Transforming Customer Experience. – Dublin: Accenture Research. – 59 p.

Arner D., Barberis J., Buckley R. (2019) The evolution of fintech: A new post-crisis paradigm? // Georgetown Journal of International Law. – Vol. 48. – P. 1271–1319.

Basel Committee on Banking Supervision (2021) Artificial intelligence and machine learning in financial services: potential implications. – Basel: BIS Publications. – 45 p.

Böhme R. (2018) Cybersecurity in finance: Risks and policy implications. // Journal of Cybersecurity. – Vol. 4(2). – P. 1–15.

Brynjolfsson E., McAfee A. (2017) Machine, Platform, Crowd: Harnessing Our Digital Future. – New York: W.W. Norton & Company. – 312 p.

Deloitte (2021). Digital Banking Maturity and Customer Experience Report. – London: Deloitte Insights. – 65 p.

Goodfellow I., Bengio Y., Courville A. (2016) Deep Learning. – Cambridge, MA: MIT Press. – 800 p.

IBM (2020). Fraud Detection and AI-Based Risk Management Report. – Armonk, NY: IBM Corporation. – 54 p.

Iqtisodiy tadqiqotlar va islohotlar markazi (ITIM) (2023). Tijorat banklarida raqamli texnologiyalar samaradorligi bo‘yicha tahliliy hisobot. – Toshkent: ITIM. – 36 b.

McKinsey & Company (2022). Global Banking Review: Artificial Intelligence in Finance. – New York: McKinsey Publications. – 78 p.

Ngai E.W.T., Liu M. (2020) Customer credit scoring using artificial intelligence techniques: A survey of current research. // Expert Systems with Applications. – Vol. 141. – P. 112–127.

O‘zbekiston Respublikasi Markaziy banki (2023). Raqamli moliya va bank xizmatlaridagi transformatsiya sharhi. – Toshkent: MB Nashriyoti. – 47 b.

Rakhimova G. (2021) Raqamli bank xizmatlarida mijozlar bilan o‘zaro aloqalar samaradorligi. // Iqtisodiyot va innovatsion texnologiyalar jurnali. – №3. – Б. 45–53.

Sobirov Sh. (2023) Sun’iy intellekt asosida kredit risklarini baholash mexanizmlari. // O‘zbekiston banklari jurnali. – №6. – Б. 18–27.

World Bank (2023). Digital Finance and AI Adoption in Emerging Markets. – Washington, D.C.: World Bank Group. – 112 p.

Yuklashlar

Nashr qilingan

Qanday qilib iqtibos keltirish kerak

Normo‘minov , T. (2025). BANK XIZMATLARIDA SUNʼIY INTELLEKT TEXNOLOGIYALARIDAN FOYDALANISH ISTIQBOLLARI: RISKLAR VA IMKONIYATLAR . Iqtisodiy Taraqqiyot Va Tahlil, 3(11), 163-169. https://doi.org/10.60078/2992-877X-2025-vol3-iss11-pp163-169