Legitimidad percibida de la fiscalización digital: efectos del sistema Falcon en confianza institucional y comportamiento tributario.

Abstract

The implementation of automated tax audit systems using artificial intelligence generates tensions between revenue collection efficiency and democratic legitimacy. This study examines how the Falcon system of Ecuador's Internal Revenue Service (SRI) affects institutional trust and taxpayer behavior. Using a mixed-methods design that combines document analysis, surveys (n=20) of taxpayers in Bolívar state, perceptions of legitimacy, transparency, and procedural fairness are analyzed. The most significant findings reveal a predominance of taxpayers aged 46-55 (40%), 60% of participants with higher education/university studies, and a crisis of institutional trust: 60% distrust data confidentiality, 55% question the ethical use of the system, and 50% perceive opacity in risk allocation criteria. Furthermore, 55% perceive that their personal data is not adequately protected, and 40% are concerned about the use of their personal data. The research identifies four critical dimensions: a lack of algorithmic transparency that erodes procedural legitimacy, a perception of arbitrariness that reduces voluntary compliance, risks of automated discrimination that undermine tax equity, and cybersecurity insecurity that compromises fundamental rights. It concludes that technological efficiency without democratic safeguards generates counterproductive effects, weakening the tax culture it seeks to strengthen. The study proposes an algorithmic governance framework based on five pillars: technical explainability, independent audits, rectification mechanisms, enhanced data protection, and citizen participation in digital policy design. The objective of the study was to analyze the perceived legitimacy of digital tax audits and the effects of the FALCON system on institutional trust and tax behavior.