Publication: Artificial Intelligence in Data Governance for Financial Decision-Making: A Systematic Review
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Issued Date
2026-01-01
Resource Type
eISSN
25042289
Scopus ID
2-s2.0-105028472985
Journal Title
Big Data and Cognitive Computing
Volume
10
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Big Data and Cognitive Computing Vol.10 No.1 (2026)
Suggested Citation
Choowan P., Daovisan H. Artificial Intelligence in Data Governance for Financial Decision-Making: A Systematic Review. Big Data and Cognitive Computing Vol.10 No.1 (2026). doi:10.3390/bdcc10010008 Retrieved from: https://hdl.handle.net/20.500.14740/55330
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Abstract
Artificial intelligence (AI) has been increasingly embedded within data-driven financial decision-making; however, its effectiveness was found to remain dependent upon the maturity of data governance frameworks. This systematic review was conducted in accordance with PRISMA 2020 guidelines to synthesise evidence from 1155 Scopus-indexed studies published between 2015 and 2025. A mixed-methods design combining corpus analysis, quantile radar regression, and radar visualisation of structural equation modelling (SEM) was employed. Empirical validation was found to demonstrate a robust model fit (CFI = 0.947; RMSEA = 0.041). Governance maturity was confirmed as a mediating construct ((Formula presented.) = 0.73) linking AI integration ((Formula presented.) = 0.76) to financial outcomes ((Formula presented.) = 0.71). The findings were found to indicate that algorithmic capacity alone does not ensure decision quality without transparent, auditable, and ethically grounded governance systems. A quantile-sensitive radar visualisation is advanced in this review, offering conceptual and methodological novelty for explainable, responsible, and data-centric financial analytics. This study is found to contribute to the ongoing discourse on sustainable digital transformation within AI-enabled financial ecosystems.