This study explores the transformative potential of Artificial Intelligence (AI) in fostering trust and enhancing customer engagement within the investment banking sector. The primary aim is to analyze how AI-driven technologies—such as machine learning, predictive analytics, natural language processing, and blockchain—can go beyond operational efficiency to strengthen transparency, personalization, and client relationships.
The research is based on survey data evaluated using statistical tools, including normality testing, Mann-Whitney U, and Kruskal-Wallis tests, to reveal demographic variations in the acceptance of AI in financial services. Findings show that younger, urban populations are more receptive to AI-powered banking solutions, while older individuals and residents of rural or semi-urban areas remain more skeptical.
Key barriers to adoption include algorithmic bias, data privacy concerns, and limited transparency. The study recommends a hybrid approach that blends AI capabilities with human expertise to improve decision-making and customer trust. Moreover, financial institutions are urged to invest in digital literacy programs, enhance technological infrastructure, and collaborate with fintech innovators. Regulatory bodies are also called upon to establish clear and supportive frameworks that promote responsible AI adoption without compromising consumer protection.
Ultimately, the study concludes that AI holds immense potential to revolutionize investment banking. However, its success hinges on addressing critical trust-related issues, ensuring ethical implementation, and promoting financial inclusion through targeted engagement strategies.
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- P. Y. Radhika (Auteur), Sikhil Kumar Das (Auteur), Shelomith Agarwal (Auteur), Abidan Pillai (Auteur), Nama Jedidya Williams (Auteur), A. Pashupathinath (Auteur), M. Veera Swamy (Auteur), M. Arul Jothi (Auteur), 2024, Artificial Intelligence in Investment Banking. Building Trust and Enhancing Customer Engagement, Munich, GRIN Verlag, https://www.grin.com/document/1577607
