Purpose: The aim of this work is to investigate the moderating effects of audit quality on data analytics tools and integrated reporting (IR). In particular, the study seeks to investigate the relationship that visualization tools, programming/data processing tools, and AI-based analytics have on integrated reporting quality and their influences; and how audit quality enhances or strengthens this relationship via independence, competence, and technology adoption. Design/Methodology/Approach: The study employs the systematic literature review (SLR) design and follows the PRISMA framework. The study performed extensive searches on several major databases, including Scopus, Web of Science, ScienceDirect, IEEE Xplore, and Google Scholar, from 2019 to 2025, of peer-reviewed articles. The study screened, appraised the quality of our included studies, and coded them for key constructs: data analytics tools, audit quality, and integrated reporting. Findings: The review demonstrates that all three categories of data analytics tools (visualization, programming/data processing, AI) positively impact the integrated reporting quality. In particular, independent audit quality improves integrated reporting through auditor independence, auditor competence, and audit technologies. Interestingly, audit quality moderates the relationship between analytics tools and integrated reporting, enhancing the positive impact of analytics adoption. All main and sub-hypotheses (H1-H4; H1a-H4c) are held, emphasizing a positive synergistic effect between automation and audit quality to obtain credible, transparent, and decision-oriented integrated reports. Implications: This research provides empirical evidence combining analytical instruments, audit quality, and integrated reporting; this addition to the body of literature on an effective audit. In practical terms, this serves to encourage us to invest in sophisticated analytics solutions in addition to high-quality audits, in the direction of improving the credibility and reliability of reporting as well as trust among stakeholders.
Agyemang et al. (Thu,) studied this question.