Banking architecture and algorithmic intelligence in asset management: The precision–discretion paradox in UITF and mutual fund institutions
Christian Anthony R. Flores
Abstract
This study examines how banking architecture and algorithmic intelligence influence asset management outcomes in banking-managed Unit Investment Trust Funds (UITFs) and mutual fund institutions, with particular focus on the Precision–Discretion Paradox. Specifically, it investigates the effects of algorithmic intelligence on professional decision discretion and asset management outcomes, as well as the moderating role of governance structures. A quantitative explanatory research design was employed using survey data collected from 214 professionals involved in asset management, including fund managers, analysts, and investment officers. Data were analyzed using correlation, regression, mediation, and moderation techniques to test the proposed relationships among variables. The results indicate that algorithmic intelligence has a significant positive effect on asset management outcomes (β = 0.62, p < 0.001), reflecting improvements in decision consistency and effectiveness. However, it also exhibits a significant negative effect on professional decision discretion (β = –0.41, p < 0.01), suggesting reduced managerial autonomy. Mediation analysis reveals that professional discretion partially mediates the relationship between algorithmic intelligence and asset management outcomes, while moderation results show that strong banking architecture weakens the negative impact of algorithmic intelligence on discretion (β = 0.28, p < 0.05). While algorithmic intelligence enhances performance, its effectiveness depends on governance structures that preserve professional judgment. These findings highlight the importance of balancing technological precision with institutional oversight in asset management.
Keywords
unit investment trust funds, governance structures, managerial autonomy, professional judgement
Author information & Contribution
Christian Anthony R. Flores. Licensed Professional Teacher. Doctor in Business Administration. Business Scientist, La Consolacion University Philippines. Email: doc.chrisflores@gmail.com
Disclosure statement
No potential conflict of interest was reported by the author.
Funding
This work was not supported by any funding.
Institutional Review Board Statement
This study was granted ethical clearance by the Institutional Ethics Review Committee of La Consolacion. The study complied with established ethical standards for research involving human participants, including voluntary participation, informed consent, confidentiality, and data privacy protection.
Data and Materials Availability
The data supporting the findings of this study are available from the corresponding author upon reasonable request.
AI Declaration
AI-assisted tools were used solely for grammar checking, and language refinement. All conceptualization, interpretation, analysis, and scholarly arguments presented in this study remain the sole responsibility of the author.
Notes
Acknowledgement
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Cite this article:
Flores, C.A.R. (2026). Banking architecture and algorithmic intelligence in asset management: The precision–discretion paradox in UITF and mutual fund institutions. International Journal of Academe and Industry Research, 7(2), 28-55. https://doi.org/10.53378/ijair.353360
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