Auditors’ propensity and accuracy in issuing going‐concern modified audit opinions for charities

Yang, Yitang; Simnett, Roger; Carson, Elizabeth

doi:10.1111/acfi.12823

Cited by 3 publications

(2 citation statements)

References 40 publications

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“…Their discussion considers that the Big4 accounting firms 2 have embraced AI for auditing purposes with the aim of achieving greater accuracy. And Yang et al (2022) provide an empirical investigation into the accuracy of going-concern audits in charities, exploring the link between these opinions and any subsequent revocation of organisations' charitable status.…”

Section: Practical Applications Of Accounting Information System Rese...mentioning

confidence: 99%

Accounting and information systems

Smith

2024

Research Handbook on Accounting and Information Systems

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This research handbook brings together an eclectic mix of research output from a widely dispersed authorship, drawing on work from around the globe, including authors from across Europe, the United States and Asia. It draws upon existing literature, new empirical research and developing theories, to present the reader with insights into the world of accounting and information systems in a fast-moving and technologically challenging era. There are extensive reviews of recent and relevant literature, alongside fieldwork evidence from a diverse range of countries which, it is hoped, will provide the reader with views of geographical and research areas with which they were previously unfamiliar. Hopefully, the range of work presented here will prompt ideas for new research alongside future pathways for the accounting profession.The book is structured in six parts, the first of which includes this introduction. The title of the handbook deliberately separates the terms 'Accounting' and 'Information Systems' to show that these are two separate concepts, albeit which are often intertwined. As Jans et al. (2022, p.62) point out, 'accounting and AIS cannot be studied separately as they both form an integrated whole'. Accounting, here, is treated as the process of measuring and communicating multiple forms of information, or data, including that which is both quantitative and qualitative. Therefore this book takes a broad view of information, both of an accounting and non-accounting nature, and the way in which it is processed, managed and used in organisations. The information system is then taken to incorporate the processes within an organisation which allow that information to be effectively used for multiple purposes, with a variety of stakeholders in mind. The chapters presented in this handbook are illustrative of the nature of research in this area, and they have been chosen to show the variety of work that exists, from a worldwide trawl of experts in the field; therefore they provide both a useful introduction to the topic for the tyro who is unfamiliar with the field, whilst also highlighting a possible research agenda and emerging ideas for the expert.Recent published research on accounting contains numerous reviews of the extant literature. In exploring digitalisation in accounting, Jans et al. ( 2022) find that topics related to AIS (Accounting Information System) in accounting journals tend to focus on 'information disclosure', 'network technologies' and 'audit and control', whilst neglecting other relevant topics. Therefore, they suggest that there is a need to bring the disciplines of accounting and AIS closer together, and they conclude by actively encouraging researchers to 'bridge the gap between the AIS and accounting literature and to actively integrate AIS topics in established accounting research ' (Jans et al., 2022, p.82). Agostino et al. (2022 conduct a review of the literature on digitalisation, accountability and accounting in public services, highlighting, in particular, issues relating to the ...

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Section: Practical Applications Of Accounting Information System Rese...mentioning

confidence: 99%

Accounting and information systems

Smith

2024

Research Handbook on Accounting and Information Systems

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“…For example, charities form a very large and economic significant part of the global economy (Jones, 2023). As a result, the transparency, governance, financial reporting, auditing and financial health of these entities has frequently come under the spotlight in many jurisdictions (Keating et al ., 2005; Kober et al ., 2021; Yang et al ., 2022; Yang and Simnett, 2020; Johansson et al ., 2022; Yang et al ., 2022, 2022). Developing predictive models for these entities represents a potential fruitful but challenging area for future research, particularly in terms of defining and operationalising the concept of financial distress and developing viable samples with a host of data availability and data quality constraints.…”

Section: Conclusion and Directions For Future Researchmentioning

confidence: 99%

A literature survey of corporate failure prediction models

Jones

2023

JAL

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PurposeThis study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed.Design/methodology/approachThis study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987.FindingsThere are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention.Originality/valueThe study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.

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Comments of the AFAANZ Auditing and Assurance Standards Committee on Proposed International Standard on Auditing 570 (Revised) Going Concern

Harding,

Hay,

Dharmasiri

et al. 2024

Accounting & Finance

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The International Auditing and Assurance Standards Board (IAASB) issued for public comment Proposed International Standard on Auditing 570 (Revised) Going Concern. The Australian Auditing and Assurance Standards Board (AUASB) and New Zealand Auditing and Assurance Standards Board (NZAuASB) also called for comments. The Auditing and Assurance Standards Committee of AFAANZ prepared a submission, based on the findings reported in extant research, informing a number of the questions asked by the IAASB. This technical note presents the formal submission made to the IAASB.

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Auditors’ propensity and accuracy in issuing going‐concern modified audit opinions for charities

Cited by 3 publications

References 40 publications

Accounting and information systems

Accounting and information systems

A literature survey of corporate failure prediction models

Comments of the AFAANZ Auditing and Assurance Standards Committee on Proposed International Standard on Auditing 570 (Revised) Going Concern

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