Banking in the era of artificial intelligence: a survey of the economic, social and strategic implications

Santiago Carbó Valverde & Francisco Rodríguez Fernández

International Journal of Banking, Accounting and Finance2025https://doi.org/10.1504/ijbaaf.2025.146534article
AJG 2ABDC C
Weight
0.50

What the paper says

Integrating artificial intelligence (AI) into banking platforms represents a transformative shift in the financial services industry, driven by the need for enhanced efficiency, improved customer experience, and robust security measures. This article analyses the economic, social, and strategic implications of AI adoption in banking. Through a comprehensive literature review, the study examines the impact of AI on operational efficiency, customer experience, security, and financial inclusion. It also addresses the ethical and regulatory challenges associated with AI, including algorithmic bias, transparency, and compliance. The findings underscore the importance of developing ethical guidelines and regulatory frameworks to ensure the responsible use of AI in banking. Strategic recommendations for banks include investing in AI talent, fostering collaborations, adopting a customer-centric approach, and ensuring ethical AI deployment. Future research directions are also suggested to explore further the potential of AI in enhancing banking services and promoting financial inclusion.

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https://doi.org/https://doi.org/10.1504/ijbaaf.2025.146534

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@article{santiago2025,
  title        = {{Banking in the era of artificial intelligence: a survey of the economic, social and strategic implications}},
  author       = {Santiago Carbó Valverde & Francisco Rodríguez Fernández},
  journal      = {International Journal of Banking, Accounting and Finance},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijbaaf.2025.146534},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 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.