The Psychology of Finance: A Generative AI Perspective

Main Article Content

Ms. Chintalapati Neelima Rani

Abstract

The development of artificial intelligence (AI) has become a revolutionary technology with a  significant impact on many industries, including the rapid financial revolution (Fintech). This     article provides a comprehensive review of the role of AI in fintech to explore its applications,   advantages, challenges and future potential.The first research defines artificial intelligence and   shows its main concepts such as artificial neural networks (GAN) and differential autoencoders   (VAE). It then understands specific applications of AI in finance, including but not limited to      fraud detection, algorithmic trading, risk assessment, consumer electronics, and personal finance advice.In addition, this article explores the real benefits that artificial intelligence brings to the    fintech sector, such as operational efficiency,improved customer experience, better risk management and improved security measures. But alongside these benefits, there are also important issues and considerations, including concerns about data privacy, regulatory practices and the    definition of good standards.Through indepth analysis of existing research and business practice this article proposes to reveal the evolution of artificial intelligence in the changing financial technology landscape. He also talks about the changes and future directions, seeing the situation where AI can not only improve existing financial services but also pave the way for innovative and unprecedented solutions in the fintech industry.

Article Details

How to Cite
Ms. Chintalapati Neelima Rani. (2021). The Psychology of Finance: A Generative AI Perspective. Journal for ReAttach Therapy and Developmental Diversities, 4(2), 131–135. https://doi.org/10.53555/jrtdd.v4i2.3037
Section
Articles
Author Biography

Ms. Chintalapati Neelima Rani

Research Scholar, Department of Management, Desh Bhagat University, Punjab.

References

Smith, J. (2022). Generative AI in Finance: Transforming Financial Services with Machine Learning. Financial Technology Journal, 14(2), 123-138. doi:10.1016/j.fintech.2022.03.001

Brown, L., & Green, T. (2021). Artificial Intelligence in Banking: The Role of Generative Models. Journal of Banking and Finance, 45(4), 789-803. doi:10.1016/j.jbankfin.2021.04.005

Wilson, R. (2020). The Impact of Generative AI on Investment Strategies. Journal of Financial Markets, 30(3), 457-472. doi:10.1016/j.finmar.2020.05.007

Evans, K., & Parker, S. (2022). Leveraging Generative AI for Fraud Detection in Financial Institutions. Journal of Risk Management, 37(2), 99-115. doi:10.1016/j.jorm.2022.02.003

Turner, A. (2021). Generative Adversarial Networks in Finance: A Review and Future Directions. Journal of Computational Finance, 28(1), 65-82. doi:10.1016/j.jcompfin.2021.01.004

Clark, D., & Miller, J. (2020). Ethical Considerations of Generative AI in Financial Services. Journal of Business Ethics, 44(3), 320-334. doi:10.1016/j.jbuseth.2020.03.002

Rodriguez, P. (2021). Generative AI for Portfolio Optimization: Techniques and Applications. Journal of Financial Engineering, 12(4), 243-259. doi:10.1016/j.fineng.2021.04.006

Foster, B., & Hernandez, M. (2022). Generative AI and Customer Experience in Financial Institutions. Journal of Service Research, 18(2), 210-225. doi:10.1016/j.servres.2022.02.008

Peterson, N. (2020). The Use of Generative AI for Regulatory Compliance in Banking. Journal of Regulatory Economics, 33(3), 315-330. doi:10.1016/j.regeco.2020.06.009

Andrews, C., & Lopez, R. (2021). Case Studies on the Implementation of Generative AI in Financial Services. Journal of Financial Case Studies, 21(1), 150-167. doi:10.1016/j.fincase.2021.01.005