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This paper proposes a conceptual model for human-centered AI (HCAI) in FinTech, addressing the need for AI systems prioritizing human interests. The model was developed through an interactive management workshop with FinTech experts, exploring ongoing research, challenges, and future research priorities. The study identifies key areas for HCAI focus, including ethics, fairness, transparency, regulation, cost, cybersecurity, trust, malicious AI, climate change, and AI developer expertise.
FinTech's AI future hinges on addressing ethical and societal concerns like bias, transparency, and cybersecurity, not just chasing performance gains.
The introduction of human-centered artificial intelligence (HCAl) in the financial technology (Fin Tech) industry was borne out of the need to have an AI system that has the interest of humans at its heart. The deployment of HCAl thus heralded a new ease of doing work. This paper presents a conceptual model on the applications of human-centered AI within the Fin Tech domain, drawing on insights from an interactive management workshop. Three trigger questions were raised with experts in the field in developing a conceptual model for applying HCAl in the FinTech industry to understand the ongoing research efforts; current challenges, limitations and gaps that are restricting research in this domain; and key areas that should be prioritized in developing a strategic research agenda for HCAl in Fin Tech. Our findings, based on the output from the 1M session revealed that focus in HCAl should focus more on areas such as ethics, fairness and bias, transparency and accountability, regulation and governance, cost of implementing AI-driven systems, cybersecurity, trust, maliciously developed AI systems, climate change challenges, and expertise of AI model developer.
