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Innovating Financial Services for Enhanced Customer Experience
Abstract
This paper explores the innovation of financial services for enhanced customer experience through AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing traditional banking practices, including customer service, fraud detection, and risk management. The study highlights the application of AI techniques such as machine learning, natural language processing, and predictive analytics in personalizing recommendations, detecting anomalies, and assessing creditworthiness. Additionally, it discusses the integration of AI with chatbots, robo-advisors, and blockchain technology to provide seamless, efficient, and secure financial services for customers. The paper also addresses challenges such as data privacy, regulatory compliance, and algorithmic bias in the deployment of AI-driven engineering solutions in the financial sector. It emphasizes the importance of transparency, fairness, and accountability in leveraging AI's potential to improve financial inclusion, accessibility, and trust in banking services.
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- Ayed, A., Kamoun, F., & Gammoudi, M. M. (2015). A review of machine learning approaches in financial fraud detection. Intelligent Data Analysis, 19(5), 1207-1230.
- Chen, Y., Wang, D., Li, X., Zhang, Y., & Sun, J. (2018). A survey of artificial intelligence in finance. Journal of Economic Surveys, 32(3), 745-776.
- Hudecheck, M., & Grosset, A. (2019). Robo-advisors and the role of technology in financial advisory services. Financial Counseling and Planning, 30(1), 53-68.
- Li, X., Wu, Q., & Liu, Z. (2017). Deep learning in financial big data analysis. Journal of Financial Engineering, 4(2), 1740004.
- McCallum, A., & Nigam, K. (1998). A comparison of event models for Naive Bayes text classification. In AAAI-98 Workshop on Learning for Text Categorization (Vol. 752, No. 1, pp. 41-48).
- Schuehly, W., & Pousttchi, K. (2019). The potential of blockchain technology in the context of future automotive business models. In Handbook of Blockchain, Digital Finance, and Inclusion (pp. 471-488). Academic Press.
- Zhang, Z., Zheng, Z., Zeng, D. D., Leung, V. C., & Zhang, C. (2017). Blockchain technology and its applications. IEEE Access, 4, 2292-2303.