LEVERAGING ADVANCED TECHNIQUES FOR CALCULATING SALES AND FINANCIAL RESULTS: CURRENT OPPORTUNITIES AND FUTURE PROSPECTS

Authors

  • Djumabaeva Nurzada a Master's student of Accounting of KarSU

Keywords:

Advanced Techniques, Sales Calculation, Financial Result Calculation, Predictive Analytics, Big Data Integration, Machine Learning Algorithms, Artificial Intelligence Applications, Business Decision-Making

Abstract

In the modern business landscape, the accurate calculation of sales and financial results plays a pivotal role in strategic decision-making and performance evaluation. This scientific article delves into the various opportunities presented by advanced techniques in the realm of sales and financial result calculations. It discusses methodologies such as predictive analytics, big data integration, machine learning algorithms, and artificial intelligence applications, highlighting their benefits and challenges. By shedding light on these opportunities, this article aims to provide businesses with insights that can enhance their ability to make informed decisions and optimize financial performance.

References

Chen, L., & Abu-Mostafa, Y. (2012). Sales Forecasting with Big Data. Journal of Big Data Analytics

Smith, J., & Johnson, A. (2018). Machine Learning Algorithms for Financial Performance Prediction. Journal of Finance and Analytics

Tan, C., & Leung, M. K. (2020). AI-driven Financial Fraud Detection: A Case Study in Banking Industry. Journal of Artificial Intelligence Research

Wu, X., & Zhang, X. (2019). Ethical Considerations in AI and Big Data: A Comprehensive Review. Journal of Business Ethics and Technology

Zhang, H., & Li, Y. (2021). Human-AI Collaboration in Financial Decision-Making: Opportunities and Challenges. International Journal of Human-Computer Interaction

Published

2023-09-21

How to Cite

Djumabaeva Nurzada. (2023). LEVERAGING ADVANCED TECHNIQUES FOR CALCULATING SALES AND FINANCIAL RESULTS: CURRENT OPPORTUNITIES AND FUTURE PROSPECTS. Ethiopian International Journal of Multidisciplinary Research, 10(09), 49–51. Retrieved from https://eijmr.org/index.php/eijmr/article/view/163