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INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN COMMERCE, MANAGEMENT & SOCIAL SCIENCE (IJARCMSS) [ Vol. 9 | No. 1 (II) | January - March, 2026 ]

AI-Driven Predictive Auditing and Financial Misstatement Detection through Algorithmic Transparency in Indian Listed Firms

Shikha Kothari & Dr. Mohammed Abid

Financial misstatements are still a major challenge to corporate transparency and investor confidence, especially in the emerging markets where audit effectiveness is still not uniform. The paper at hand explores AI-based predictive auditing and its advantages in improving the detection of financial misstatements by mediating the concept of algorithmic transparency in Indian listed companies. The research is based on the Agency Theory and Technology Acceptance Model, to explore how AI-enabled auditing systems affect the outcomes of audit performances. The quantitative research design was used based on the survey data on 312 auditors and financial professionals in India and analyzed the model through PLS-SEM. The findings suggest that AI-based predictive auditing influences the financial misstatement detection significantly and positively, and the transparency of the algorithms has a powerful mediating role. The mediation effect is significant (p < 0.01) and it proves that transparent AI systems contribute to the effectiveness and reliability of the audits. This research expands the literature by presenting the concept of algorithmic transparency as an important tool and offers an insightful idea on how organizations can enhance the quality of audits and detect fraud by applying AI.

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