A multiple discriminant analysis of the auditor's going concern opinion: the case of audit opinions in Italy. Issue 6 (9th June 2020)

• Record Type: Journal Article
• Authors: Maffei, Marco; Fiondella, Clelia; Zagaria, Claudia; Zampella, Annamaria
• Is Part Of: Meditari accountancy research. Volume 28:Issue 6(2020)
• Page Start: 1179
• Page End: 1208
• Publication Date: 2020-06-09
• Subjects: Going concern -- Audit opinion -- Multiple linear discriminant analysis; Accounting -- Periodicals; Finance -- Periodicals; 657.05
• DOI: 10.1108/MEDAR-06-2019-0514
• Languages: English
• ISSNs: 2049-372X

Abstract

Abstract : Purpose: The purpose of this paper is to develop a model for assessing the audit evidence of the going-concern (GC) assumptions underlying the preparation of financial statements. Design/methodology/approach: This research analyses 678 audit opinions of Italian listed firms from 2007 to 2016 and uses a multiple linear discriminant analysis to create a GC score, which includes variables suggested by the international standards on auditing (ISA) 570 and by literature on GC. Findings: The model provides three cut-off scores which can orient auditors towards issuing the most appropriate GC audit opinions (unmodified opinion, unmodified opinion, which includes emphases of matter, qualified opinion or disclaimer of opinion). Research limitations/implications: The development of the model is mainly based on public data and does not assess confidential information that is not disclosed in audit opinions. Practical implications: This model can enable auditors to identify the most appropriate GC opinion and align auditor's opinions in similar circumstances, thereby reducing their reliance on discretion and increasing the reliability of their judgement with a higher degree of accuracy. Moreover, this research lists additional events or conditions that may individually or collectively cast significant doubt on GC assumptions. Originality/value: This study goes beyond the traditional decision-making process, apparently binary in nature, between "continuity" and "failure" or between "unmodified" and "modified" opinions. It is conceived to detect the different degrees of uncertainty that affect GC evaluations to orient auditors' professional judgements.