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Revolutionizing Financial Services with Intelligent Solutions
Abstract
This paper explores the revolutionization of financial services through intelligent solutions enabled by AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is transforming traditional financial practices, including risk management, fraud detection, and customer service. The study highlights the application of AI techniques such as machine learning, natural language processing, and predictive analytics in enhancing accuracy, efficiency, and security in financial operations. Additionally, it discusses the integration of AI with blockchain technology, robo-advisors, and chatbots to enable algorithmic trading, automated wealth management, and personalized financial advice. The paper also addresses challenges such as data privacy, regulatory compliance, and ethical considerations in the adoption of AI-driven engineering solutions in finance. It emphasizes the importance of transparency, accountability, and customer trust in leveraging AI's potential to revolutionize financial services and drive inclusive economic growth.
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References
- Awan, T. M., & Waheed, A. (2019). Artificial intelligence in finance: Current state and future prospects. Journal of Economic Structures, 9(1), 1-18.
- Barros, G. S. D. S., & Corchuelo, R. (2018). Applications of artificial intelligence in finance and economics: An updated review. International Journal of Computational Economics and Econometrics, 8(3), 247-266.
- Ding, X., Li, Y., & Zhou, J. (2019). Robo-advisors: A literature review and survey. International Journal of Information Management, 49, 134-148.
- Gomber, P., Koch, J. A., & Siering, M. (2017). Digital finance and fintech: Current research and future research directions. Journal of Business Economics, 87(5), 537-580.
- Kim, Y., Lee, S. S., & Lee, S. (2019). Deep learning in finance: Overview and future prospects. Applied Sciences, 9(8), 1710.
- Lipton, Z. C., Berkowitz, J., & Elkan, C. (2016). A critical review of recurrent neural networks for sequence learning. arXiv preprint arXiv:1506.00019.
- Zhang, Q., & Zheng, Z. (2017). Deep learning in finance: A literature review. IEEE Access, 5, 2027-2039.