Published April 3, 2026 | Version v1
Dataset Open

SUN'IY INTELLEKT YORDAMIDA MOLIYAVIY HISOBOTLARNI TAHLIL QILISH

Description

Ushbu maqolada sun’iy intellekt texnologiyalaridan foydalanib moliyaviy hisobotlarni tahlil qilishning zamonaviy usullari o’rganilgan. Tadqiqot davomida mashinaviy o’rganish algoritmlari, tabiiy tilni qayta ishlash (NLP) va chuqur o’rganish (deep learning) texnologiyalarining moliyaviy ma’lumotlarni qayta ishlashdagi samaradorligi baholangan. Natijalar sun’iy intellektga asoslangan tahlil usullarining an’anaviy usullarga nisbatan 43% yuqori aniqlik ko’rsatkichiga ega ekanligini tasdiqladi. Bundan tashqari, ushbu yondashuv moliyaviy xatarlarni erta aniqlash va prognozlashda muhim ahamiyat kasb etishi isbotlangan.

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Additional details

References

  • 1.. Abdullayev J., Xolmatov R. (2023). O'zbekiston tijorat banklarida sun'iy intellekt texnologiyalarini joriy etishning iqtisodiy samaradorligi. O'zbekiston Iqtisodiy Jurnali.
  • 2. Bao, Y , Datta A. (2014). Simultaneously discovering and quantifying risk types from textual risk disclosures
  • 3.Goodfellow, I. Bengio, Y. Courville, A. (2016). Deep Learning. MIT Press.
  • 4.Huang, A. Wang H, Yang, Y. (2020). FinBERT: A large language model for extracting information from financial text. SSRN Working Paper.
  • 5.McKinsey Global Institute. (2023). The economic potential of generative AI: The next productivity frontier. McKinsey & Company.
  • 6.O'zbekiston Respublikasi Prezidentining 2020-yil 5-oktabrdagi PF-6079-sonli Farmoni. «Raqamli O'zbekiston – 2030» strategiyasi to'g'risida.
  • 7.Qian, B. Rasheed, K. (2014). Stock market prediction with multiple classifiers
  • 8.Vaswani, A. (2017). Attention is all you need.
  • 9.World Economic Forum. (2023). The Future of Financial Services: How Disruptive Innovations Are Reshaping Financial Services.