The Impact of AI on Cross-Border Financial Operations in Fintech: A Legal and Ethical Perspective

Investigating how fintech professionals understand the operational, legal, and ethical repercussions associated with the employment of AI in cross-border financial industries enables this paper to evaluate whether or not fintech professionals support regulatory intervention. This research is built on the Technology Acceptance Model and Institutional Theory, and is based on a quantitative design involving 150 professionals from six countries who filled out a survey. The statistical analysis results suggest that familiarity with AI is a strong predictor of perceived operational benefits and support for regulation, and that concerns about ethics play a role in supporting regulation most strongly. Legal concerns, however, also influence regulatory preferences to a lesser extent. This highlights a disconnect between the operational optimism and governance apprehension, and indicates that an awareness of the capabilities of the AI does not circumvent professionals’ worries about the complexity of fairness, accountability, and compliance. These results highlight the need for harmonized, ethically aligned regulatory frameworks to both enable and steer the progression of AI-driven innovation and accountability in the global finance, in which the systems are deeply intertwined and dependent on each other.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-06-29
DOI
https://doi.org/10.30574/wjarr.2025.26.3.2445
Citations
1
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
2.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Impact of AI on Cross-Border Financial Operations in Fintech: A Legal and Ethical Perspective

Oladiipo Ishola Oladepo, Seye Amos Olawoyin
1 citations
World Journal of Advanced Research and Reviews
FinTech, Crowdfunding, Digital Finance
2.28
article

The Impact of AI on Cross-Border Financial Operations in Fintech: A Legal and Ethical Perspective

Oladiipo Ishola Oladepo, Seye Amos Olawoyin
article en
1 citations

Abstract

Investigating how fintech professionals understand the operational, legal, and ethical repercussions associated with the employment of AI in cross-border financial industries enables this paper to evaluate whether or not fintech professionals support regulatory intervention. This research is built on the Technology Acceptance Model and Institutional Theory, and is based on a quantitative design involving 150 professionals from six countries who filled out a survey. The statistical analysis results suggest that familiarity with AI is a strong predictor of perceived operational benefits and support for regulation, and that concerns about ethics play a role in supporting regulation most strongly. Legal concerns, however, also influence regulatory preferences to a lesser extent. This highlights a disconnect between the operational optimism and governance apprehension, and indicates that an awareness of the capabilities of the AI does not circumvent professionals’ worries about the complexity of fairness, accountability, and compliance. These results highlight the need for harmonized, ethically aligned regulatory frameworks to both enable and steer the progression of AI-driven innovation and accountability in the global finance, in which the systems are deeply intertwined and dependent on each other.

World Journal of Advanced Research and ReviewsVol. 26(3)
Openalex Percentile: Top 11%
FinTech, Crowdfunding, Digital Finance
2.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.