Architecting financial well-being in algorithmic credit systems: The roles of human capability and institutional design
Christian Anthony R. Flores
Abstract
The rapid diffusion of algorithmic credit systems has transformed lending decisions, yet their implications for financial well-being remain theoretically fragmented and empirically contested. Existing studies often adopt technologically deterministic perspectives, emphasizing access and efficiency while overlooking the roles of borrower capability and institutional governance. This study advances a socio-technical and architectural systems perspective by examining how algorithmic credit systems influence financial well-being and how these effects are conditioned by human capability and institutional design. Using a quantitative, explanatory, cross-sectional design, data were collected from 400 users of algorithmic and digitally mediated credit platforms. Multiple regression and moderation analyses were employed to assess the direct and conditional relationships among algorithmic credit systems, human capability, institutional design, and multidimensional financial well-being outcomes, including repayment behavior, financial stress, and financial resilience. Measurement reliability and validity were established through Cronbach’s alpha and principal component analysis. The results indicate that algorithmic credit systems are positively associated with repayment behavior and financial resilience but are also linked to higher levels of financial stress. Moderation analysis reveals that these effects are significantly shaped by contextual factors: higher levels of human capability and stronger institutional design amplify positive outcomes and mitigate adverse effects. These findings suggest that financial well-being is not an automatic byproduct of automated credit efficiency but an emergent outcome of architectural alignment among technology, borrower capability, and governance structures. The study contributes to theory by empirically integrating technological, human, and institutional dimensions within a single architectural framework, moving beyond isolated analyses of digital credit.
Keywords
digital finance, socio-technical systems, financial resilience, financial stress
Author information & Contribution
Doctor in Business Administration. Researcher/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
Not Applicable
Data and Materials Availability
The data supporting the findings of this study are available from the corresponding author upon reasonable request.
AI Declaration
AI tools were not used in writing this paper.
Notes
Acknowledgement
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Cite this article:
Flores, C.A.R. (2026). Architecting financial well-being in algorithmic credit systems: The roles of human capability and institutional design. International Review of Social Sciences Research, 6(1), 255-276. https://doi.org/10.53378/irssr.353331
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This work is licensed under a Creative Commons Attribution (CC BY 4.0) International License.
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