This article provides an in-depth analysis of the rapidly developing artificial intelligence market, with a focus on robo-advisors in China. The authors do not limit themselves to simply describing technology, but comprehensively explore its technical foundations, including key aspects such as machine learning and especially deep learning, demonstrating their practical application in the rapidly growing financial sector. It examines not only the algorithmic structure but also the specific mechanisms of artificial intelligence functioning: how it processes information, makes forecasts, and forms investment recommendations. Special attention is paid to the regulatory component. The authors analyze the current regulatory framework in detail, focusing on the role of the China Securities Regulatory Commission (CSRC), including licensing procedures and requirements for robo-advisors in the Chinese market. In this context, both technical and ethical issues are addressed, taking into account the need for a high level of trust when working with financial instruments. Along with positive trends, the article identifies key problems and challenges related to the introduction of robo-advisors. Among them are: limited ability to fully trust client funds, the problem of information asymmetry (when algorithms have more information than investors), as well as insufficient transparency of algorithms, which complicates understanding the logic of decisions made by artificial intelligence. These aspects raise justified concerns regarding trust and potential risks for investors. In conclusion, specific measures are proposed to eliminate the identified problems aimed at developing balanced and sustainable regulation.
| Mualliflar | Otabek Narziev, Zarnigor Nabirayeva |
|---|---|
| Jurnal | Юридик фанлар ахборотномаси – Вестник юридических наук – Review of law sciences |
| Nashr sanasi | 2025-06-26 |
| Jild | 9 |
| Son | 2 |
| Betlar | 87-87 |
| Til | en |
| DOI | 10.51788/tsul.rols.2025.9.2./arjk7584 |
DOI: 10.51788/tsul.rols.2025.9.2./arjk7584 · Maqolaning asl sahifasi · PDF
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