Can Technology Make Fair Value More Verifiable? A Systematic Literature Review of Measurement Uncertainty, Data Analytics, and Audit Assurance
DOI:
https://doi.org/10.70142/jbl.v3i2.75Keywords:
Fair Value, Measurement Uncertainty, Data Analytics, Audit Assurance, VerifiabilityAbstract
This qualitative systematic literature review examines whether technology can make fair value (FV) more verifiable by integrating evidence on measurement uncertainty, data availability, data analytics, auditor expertise, and audit assurance. The review synthesizes prior research to identify recurring mechanisms through which technological development may influence FV verifiability. The findings indicate that technology does not eliminate fundamental measurement uncertainty, particularly for Level 3 FV estimates, but can improve verifiability by increasing access to relevant data, strengthening analytical capabilities, facilitating independent valuation procedures, and enhancing audit evidence. However, technological effectiveness depends critically on data quality, task-specific auditor expertise, professional judgment, and appropriate governance. The review further identifies a paradox whereby advanced analytics and artificial intelligence can reduce information uncertainty while introducing new risks related to reliability, explainability, bias, and auditor overreliance. Overall, technology can make FV more verifiable, but its effectiveness is conditional on the interaction of data, technology, expertise, evidence, and governance.
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