Algorithmic Inclusion Paradox Access Expansion, Capability Erosion, and Financial Precarity in Digital Banking Environments: A Capability-Governance Framework

Abstract

The rapid diffusion of algorithmic decision systems in retail banking has significantly expanded access to formal financial services, particularly among previously underserved populations. However, emerging empirical evidence suggests that expanded access does not uniformly translate into improved financial outcomes. This study advances the concept of the Algorithmic Inclusion Paradox, which captures the counterintuitive dynamic in which algorithmic banking systems simultaneously enhance financial access while undermining users' capabilities and exacerbating conditions of financial precarity. Drawing on the capability approach and contemporary scholarship on algorithmic governance, the study develops a Capability-Governance Framework to explain how automated credit assessment, opaque scoring mechanisms, and weak institutional safeguards interact to erode financial capability despite increased inclusion. The framework theorizes that access expansion operates through distinct structural pathways—mediated by borrower capability and moderated by governance quality—that shape household vulnerability, risk exposure, and resilience within digital banking environments. By integrating human capability considerations with institutional governance mechanisms, this study contributes a theory-building perspective that extends existing financial inclusion and fintech literature beyond access-centric models. The proposed framework offers a basis for empirical testing. It provides policy-relevant insights for regulators and financial institutions seeking to design responsible, human-centered algorithmic banking systems that promote sustainable inclusion rather than financial precarity.