INSURTECH TEXNOLOGIYALARINI QO‘LLASH ORQALI SUG‘URTA TO‘LOVLARINING TEZKORLIGI VA SAMARADORLIGINI OSHIRISH

Mualliflar

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https://doi.org/10.5281/zenodo.21870095

Kalit so‘zlar:

InsurTech, sug‘urta to‘lovlari, sun’iy intellekt, OCR, API integratsiyasi, raqamli platforma, avtomatlashtirish, sug‘urta bozori.

Abstrak

Maqolada InsurTech texnologiyalarini sug‘urta to‘lovlari jarayoniga joriy etishning ahamiyati tahlil qilingan. Elektron FNOL, OCR, API integratsiyasi, sun’iy intellekt va avtomatlashtirilgan to‘lov tizimlarining to‘lovlar tezkorligi, shaffofligi va operatsion samaradorligiga ta’siri yoritilgan. Shuningdek, sug‘urta to‘lovlari tizimini takomillashtirish bo‘yicha amaliy takliflar ishlab chiqilgan.

Библиографические ссылки

1. Gallagher Re. Global InsurTech Report for Q4 2025 [Elektron resurs]. – London: Gallagher Re, 2026. – URL: https://www.ajg.com/gallagherre/news-and-insights/global-insurtech-report-q4-2025

2. Gallagher Re. Global InsurTech Report: Q4 2024. The Role of AI in the (Re)insurance Industry [Elektron resurs]. – London: Gallagher Re, 2025. – 120 p. – P. 8–9. – URL: https://www.ajg.com/gallagherre/-/media/files/gallagher/gallagherre/news-and-insights/2025/february/gallagherre-global-insurtech-report-q4.pdf

3. Eckert C., Osterrieder K. How digitalization affects insurance companies: overview and use cases of digital technologies // Zeitschrift für die gesamte Versicherungswissenschaft. – 2020. – Vol. 109. – P. 333–360. – DOI: 10.1007/s12297-020-00475-9.

4. Eling M., Nuessle D., Staubli J. The impact of artificial intelligence along the insurance value chain and on the insurability of risks // The Geneva Papers on Risk and Insurance – Issues and Practice. – 2022. – Vol. 47. – P. 205–241. – DOI: 10.1057/s41288-020-00201-7.

5. Aslam F., Hunjra A., Ftiti Z., Louhichi W., Shams T. Insurance fraud detection: Evidence from artificial intelligence and machine learning // Research in International Business and Finance. – 2022. – Vol. 62. – Art. 101744. – DOI: 10.1016/j.ribaf.2022.101744.

6. Rawat S., Rawat A., Kumar D., Sabitha A. S. Application of machine learning and data visualization techniques for decision support in the insurance sector // International Journal of Information Management Data Insights. – 2021. – Vol. 1, No. 2. – Art. 100012. – DOI: 10.1016/j.jjimei.2021.100012.

7. Poufinas T., Gogas P., Papadimitriou T., Zaganidis E. Machine Learning in Forecasting Motor Insurance Claims // Risks. – 2023. – Vol. 11, No. 9. – Art. 164. – 19 p. – DOI: 10.3390/risks11090164.

8. Atanasious M. M. H., Becchetti V., Giuseppi A. et al. An Insurtech Platform to Support Claim Management Through the Automatic Detection and Estimation of Car Damage from Pictures // Electronics. – 2024. – Vol. 13, No. 22. – Art. 4333. – 14 p. – DOI: 10.3390/electronics13224333.

9. O‘zbekiston Respublikasi Istiqbolli loyihalar milliy agentligi. Sug‘urta bozori statistikasi va tahlili – Toshkent: O‘zbekiston Respublikasi Istiqbolli loyihalar milliy agentligi. – URL: https://napp.uz/ru/pages/statistics-and-analysis-for-im

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Nashr qilingan

2026-08-07