Assessing the Impact of Audit Quality on Financial Statement Reliability in Small and Medium Enterprises

Posted: Aug 02, 2021

• Diego Ford
• Kian Mitchell
• Addison Price

Abstract

The reliability of financial statements in Small and Medium Enterprises (SMEs) represents a critical yet understudied domain in accounting and financial computing research. While extensive literature exists on audit quality in large corporations, the unique characteristics of SMEs—including limited resources, simplified internal controls, and diverse ownership structures—create distinct challenges for financial reporting quality. Traditional audit quality metrics, predominantly developed for large public companies, often fail to capture the nuanced dynamics of SME financial reporting environments. This research addresses this gap by developing a computational framework that redefines how audit quality is measured and its impact on financial statement reliability in the SME context. Our approach diverges from conventional methodologies by integrating computational linguistics with machine learning to analyze both quantitative and qualitative aspects of audit quality. We propose that audit quality in SMEs should be conceptualized as a multi-dimensional construct encompassing not only technical competence and independence but also communication effectiveness, process transparency, and contextual adaptation. This perspective challenges the prevailing audit quality paradigms that emphasize auditor size and fee structures as primary indicators. This research addresses three fundamental questions: First, how can audit quality be effectively measured in SMEs given their unique operational constraints and reporting environments? Second, which dimensions of audit quality most significantly influence financial statement reliability in the SME context? Third, can computational methods provide more accurate predictions of financial statement reliability than traditional statistical approaches?