<p>Digital public infrastructure (DPI) has made great strides in increasing financial inclusion; however, there is a continued resistance to adopting DPI from low-income and rural populations, as well as first-time digital finance users that are DPI specifically designed to serve. Current frameworks identify that risk perception and trust are predictors of adoption but do not address why financially rational people misperceive DPI’s well documented safety record. We present a new theoretical framework that integrates clinical psychology, behavioural economics and dual-process cognitive theory in an effort to address the mechanical link. The framework describes three cognitive distortions: catastrophizing, overgeneralization, and mental filtering, which are theorized to operate as System 1 mechanisms that bias risk perceptions beyond statistical reality through two parallel mediation processes. We recommend five testable propositions based on the framework and additionally develop a Matching Hypothesis, suggesting that use of effective communication strategies aligns with cognitive distortion mechanism, as opposed to using generic information campaign strategies. The AI components of DPI increase the activation of cognitive distortions among low-income, rural, and first-time users by creating algorithmic uncertainty, thereby compounding exclusion for the groups least capable of contextualising automated decision-making. The framework contributes a theoretically precise, falsifiable, and welfare-grounded account of distortion-driven financial exclusion, with direct implications for SDG 9-oriented DPI communication strategy, SDG 10’s mandate to reduce economic inequalities, and the sustainable livelihoods. The framework applies specifically to risk perceptions and distrust that are systematically decoupled from a system’s actual risk profile.</p>