This article examines the transformative role of neural networks in econometrics and financial decision-making, emphasizing their influence on personal finance, automation, healthcare, transportation, and human-computer interaction. Neural networks, inspired by the structure of the human brain, have the potential to revolutionize these sectors by enhancing efficiency, accuracy, and decision-making capabilities. In personal finance, they can optimize budgeting, savings, and expenditure management through automated models such as the McCulloch-Pitts neuron. In healthcare, neural networks improve diagnostic capabilities and enable predictive treatment. The article also highlights the applications of neural networks in econometrics to analyze financial patterns, detect fraud, and manage risks more effectively. However, it also addresses the ethical concerns related to data privacy, security, and biases in algorithmic decision-making, stressing the importance of responsible development. Ultimately, it concludes that, despite the challenges, the benefits of integrating neural networks into econometric models and financial systems are substantial and indispensable for modern advancements.

In the article, a study was conducted on the effectiveness of using econometrics in the analysis of tax benefits, and researches of foreign scientists were studied. The hypothesis that can be formed in the analysis of the relationship between tax benefits and the production of industrial products is considered and scientific conclusions are formed at the end of the topic.

The rapid development of the tourism industry is generating deep structural changes in the management of tourism infrastructure in Uzbekistan. This article provides a systematic analysis of the key components of tourism infrastructure, its development trends, and interactions with major economic factors. The study comparatively examines statistical data from 2016-2024 on the expansion of hotel capacity, improvements in transport and logistics systems, growth in investment flows, formation of regional tourism clusters, and service quality enhancements. Moreover, the impact of infrastructure development on tourism demand, the impulse of state policies and reforms on the sector, as well as pandemic-related disruptions and post-pandemic recovery dynamics, are assessed using econometric models. The findings contribute to the development of practical recommendations aimed at modernizing tourism infrastructure, increasing international tourist inflows, improving regional infrastructure efficiency, and ensuring sustainable economic growth.

This paper analyzes the structure of assets that ensure the stability of commercial banks and the factors affecting them using econometric methods. The main purpose of the study was to study such factors as the quality of banks' assets, liquidity indicators, the structure of the loan portfolio, as well as external economic factors. The results obtained using econometrics methods help commercial banks make important decisions to improve their sustainability. The practical significance of the research lies in the fact that it serves as a methodological basis for the formation of strategies aimed at the development of banking activities.

In this article, the concepts of developing econometric skills in students using the Case-study method. Econometric skills, particularly the use of the case study method in the analysis of correlation and regression equations, are presented as a method for developing econometric skills in students. Also in this article, the author focused on the selection of statistical data and determining the relationship between them.