Agentic systems as catalysts for innovation in FinTech: exploring opportunities, challenges and a research agenda
Ibrahim A. Elgendy et al.
What the paper says
Purpose Agentic artificial intelligence (AI) systems, which feature autonomous decision-making and adaptive intelligence, can potentially revolutionize financial technology (FinTech) by combining algorithmic accuracy with human knowledge. This study aims to examine the opportunities, challenges and transformational potential of agentic systems in FinTech and suggests a thorough research agenda for directing their sustainable and ethical integration. Design/methodology/approach This study conceptualizes the changing environment of agentic systems by combining insights from technical whitepapers, industrial case studies and scholarly literature. It assesses how they are changing conventional financial frameworks and determines key factors that affect their adoption. Findings The sentiment analysis of 170 social media posts revealed an overwhelmingly positive public perception (85%) of agentic AI in FinTech. In addition, the study finds that agentic systems fundamentally alter FinTech by providing autonomous, adaptive and context-aware financial services in trade, fraud detection, customer interaction and regulation. However, their widespread implementation presents challenges such as transparency, ethical alignment, system robustness and regulatory supervision. Research limitations/implications This paper provides a fundamental paradigm to help stakeholders navigate the FinTech industry’s adoption of agentic systems. It examines the many facets of these systems’ challenges and novel opportunities, especially automation, personalization and risk management. It also presents a research agenda for the future that aims to direct future investigations and promote cooperation among industry, academia and regulatory agencies. Originality/value To the best of the authors’ knowledge, this research is one of the first comprehensive evaluations of agentic systems in FinTech. It emphasizes how multidisciplinary cooperation is essential to ensuring that these systems promote reasonable, long-term advancements in financial digitalization.
16 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.64 × 0.4 = 0.26 |
| M · momentum | 0.90 × 0.15 = 0.14 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.