STUDY APPLICATIONS IN FINANCIAL FIELDS: AN ANALYTICAL REVIEW OF TOOLS AND TRENDS
Keywords:
Financial applications, investment tools, financial forecasting, AI in finance, fintech, financial decision-making, risk analysis, study appsAbstract
In recent years, the intersection of data science, artificial intelligence, and financial analytics has led to the development of sophisticated study applications that support decision-making in the financial sector. This paper provides an in-depth review of study applications used in financial fields such as investment analysis, risk management, personal finance, and financial forecasting. Using a qualitative and comparative research method, this study explores the most widely used financial tools, evaluates their algorithms and features, and analyzes their impact on financial decision-making. The findings highlight the increasing importance of AI-driven and cloud-based financial applications and suggest future areas of development. The study also discusses the challenges such as data privacy, algorithmic bias, and over-reliance on automation.
References
Smith, A. (2021). The Rise of Fintech in Education. Journal of Financial Technology, 5(2), 112–130.
Johnson, L., & Wang, M. (2020). AI in Financial Planning. Financial Intelligence Quarterly, 7(4), 50–63.
Brown, T. (2019). Mobile Applications for Personal Finance. Fintech Review, 3(1), 75–89.
Investopedia (2024). Best Investment Simulators. https://www.investopedia.com
Bloomberg LP. (2023). Product Overview. Retrieved from https://www.bloomberg.com/professional
Khan Academy. (2024). Finance and Capital Markets. https://www.khanacademy.org
