Decision‐making capabilities of a hybrid system applied to the auditor's going‐concern assessment

Lenard, Mary Jane; Alam, Pervaiz; Booth, David E.; Madey, Gregory R.

doi:10.1002/isaf.190

Cited by 27 publications

(24 citation statements)

References 41 publications

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“…The model suggests that auditors are less likely to issue a modified opinion when the financial prospects of the company are not clear and when auditors are faced with incentives to delay or avoid a modified opinion. Research study on auditor's going-concern assessment focuses on the hybrid systems as a decision support model (Lenard et al, 2001). They find that the bankruptcy prediction is an important component of the going-concern decision.…”

Section: Audit Qualification Opinionmentioning

confidence: 99%

Audit Qualification, Firm Litigation, and Financial Information: an Empirical Analysis in Greece

Spathis¹

2003

Int J Auditing

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In this study, we test the extent to which combinations of financial and non-financial information can be used to enhance the ability to discriminate between the choices of a qualified or unqualified (clean) audit report. Several models have been developed to explain qualifications in audit reports. The general consensus of these models has been that financial and non-financial factors dominate the audit opinion decision. In the USA, the Statement of Auditing Standards (SAS) No. 59 provides guidance for auditors to provide more critical evaluations to identify the possibility of qualifications problems. It identifies the conditions that an auditor should consider in evaluating going-concern status. These conditions include financial problems and operating problems. The standards also provide guidance on two other types of information, negative trends (operating losses) and other indicators, including internal matters, e.g., losses, and external matters (legal proceedings). For the most part, prior studies have not used any other qualitative variable(s) as indicators when developing audit opinion models. These qualitative indicators of potential solvency problems indicate year's losses and bad news characteristics, as firm litigation. TheIn this study, we test the extent to which combinations of financial and non-financial information can be used to enhance the ability to discriminate between the choices of a qualified or unqualified (clean) audit report. We examined the financial statements, the opinions of the auditors, and the notes to financial statements for companies that received a qualified audit report and for those that received an unqualified audit report. The data are taken from a sample of 100 Greek companies. Logistic and OLS regression models were estimated to assess the effect of firm litigation and financial information on audit qualification opinion. The qualification decision is associated by financial information such as financial distress and by non-financial information such as firm litigation. The model developed is accurate in classifying the total sample correctly with rate 78%. This study has implications for internal and external auditors and company decision makers.importance of these other qualitative indicators (firm litigation) in the auditor's decision has not been tested.The objective of the study was to develop a model based on financial information and other indicators, such as firm litigation, to explain qualifications in audit reports of Greek companies. The model will provide information on the likelihood of a company's receiving a qualification given its financial data and firm litigation data. This kind of model can serve as a decision aid for auditors when predicting what opinion other auditors would issue in similar circumstances, when evaluating potential clients, in determining the scope of an audit for existing clients, in peer reviews, to control quality within firms, and as a defence in lawsuits.Univariate tests (t-tests and chi-squared tests) and logistic and OLS ...

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Section: Audit Qualification Opinionmentioning

confidence: 99%

Audit Qualification, Firm Litigation, and Financial Information: an Empirical Analysis in Greece

Spathis¹

2003

Int J Auditing

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“…These systems performed well on test cases but their performance declined on actual audit situations (Smith and McDuffie, 1996;Collier et al, 1999;Lenard et al, 2001;Murphy and Yetmar, 1996;Hornik and Ruf, 1997;Lenard, 2003). Furthermore, previous studies ignored the role of users in developing a knowledge base and building an explanation facility (Akoka and Comyn-Wattiau, 1996;Akoka and Comyn-Wattiau, 1997;Mak et al, 1997;Bayraktar, 1998).…”

Section: Knowledge-based Systems In Auditingmentioning

confidence: 89%

When will a Computer Write the Auditor's Report?

et al. 2005

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Most corporations are required by law to produce annual reports on their financial positions. These financial reports are accompanied by an auditor's report, which is an independent auditor's opinion on the fairness of the financial statements. To formulate their reports, auditors use a "personal-judgement" approach that heavily depends on their experience and expertise. This approach may be (1) ineffective and may lead to (2) different decisions, (3) personal bias, and (4) misleading judgements. These four drawbacks of a human auditor are a source of doubt and hesitation for every corporation. Therefore, the challenging question is: Can a computer do a better job? This paper focuses on the construction and implementation of a knowledge-based system, called the "Auditor's Report EXpert" (AREX), that is capable of formulating the opinion on financial statements, as expressed in the auditor's report. The knowledge used by AREX is acquired from the literature, and from a slate of practicing and academic auditors by means of questionnaires and in-depth interviews. A preliminary validation of AREX indicates that AREX is successful in performing the auditor's report task. Hence, we tentatively conclude that currently a computer program can support an auditor in his/her task. Moreover, in the foreseeable future (maybe in 2030), it is to be expected that a computer program can produce idiosyncratic auditor's reports that are effective, universal in their decisions, do not show a personal bias, and do not have misleading statements.

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“…Depending on the research objectives as well as on data availability, some studies distinguish between going concern and non-going concern opinions (Koh and Killough, 1990;Lenard et al, 1995Lenard et al, , 2001, others between fraud (or falsified financial statements-FFS) and non-fraud (non-FFS) (Bonchi et al, 1999;Spathis et al, 2002), and others distinguish in general between qualified and unqualified opinions (Laitinen and Laitinen, 1998;Spathis et al, 2003;Gaganis et al, 2005aGaganis et al, , 2005bDoumpos et al, 2005;Pasiouras et al, 2006). Over the years various techniques have been proposed such as discriminant analysis (Koh and Killough, 1990), probit analysis (Dopuch et al, 1987), logit analysis (Laitinen and Laitinen, 1998;Spathis, 2002), artificial neural networks (Lenard et al, 1995;Fanning et al, 1995;Fanning and Cogger, 1998), hybrid systems (Lenard et al, 2001), multicriteria decision aid Pasiouras et al, 2006), nearest neighbours (Gaganis et al, 2005a), probabilistic neural networks (Gaganis et al, 2005b), and support vector machines (Doumpos et al, 2005). Most of these studies achieve satisfactory classification accuracies and conclude that the models could be useful to auditors in forming their opinion.…”

Section: Models For Auditing Decisions In the Private Sectormentioning

confidence: 99%

Auditing models for the detection of qualified audit opinions in the UK public services sector

Gaganis¹,

Pasiouras

2006

IJAAPE

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We develop classification models that could assist auditors during the examination of firms operating in the public services sector. The sample consists of 228 firms from the Health and Social work and the Education UK sectors. The models, both sector-specific and general ones, are developed with discriminant and logit analysis through a 10-fold cross-validation procedure. The models achieve a satisfactory accuracy in classifying financial statements as qualified or unqualified. The variables that are important across all models are the logarithm of total assets, the return on capital employed, and whether the auditor is one of the big four or not. Copyright © 2006 Inderscience Enterprises Ltd

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Decision‐making capabilities of a hybrid system applied to the auditor's going‐concern assessment

Cited by 27 publications

References 41 publications

Audit Qualification, Firm Litigation, and Financial Information: an Empirical Analysis in Greece

Audit Qualification, Firm Litigation, and Financial Information: an Empirical Analysis in Greece

When will a Computer Write the Auditor's Report?

Auditing models for the detection of qualified audit opinions in the UK public services sector

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