<![CDATA[This study aims to synthesize the literature on cognitive bias in auditor decision-making from 2015–2025. Using the Systematic Literature Review (SLR) method guided by the PRISMA framework, 50 scientific articles were systematically analyzed. A multi-level analysis was conducted to identify dominant types of biases, their influencing factors at the individual, organizational, and institutional levels, and effective mitigation strategies. The findings reveal four primary cognitive biases: anchoring, confirmation, overconfidence, and availability bias. Factors influencing the emergence of these biases include auditor experience and professional skepticism (micro-level), time pressure and organizational culture (meso-level), as well as professional regulations and the adoption of technology like AI (macro-level), which gives rise to automation bias. Identified mitigation strategies include bias-awareness training, the use of decision support tools, and strengthening professional skepticism through a supportive organizational culture. This review provides a comprehensive understanding of the dynamics of cognitive bias and offers practical implications for the development of training programs, professional policies, and audit system design in the digital era to enhance audit quality and objectivity.]]>
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