Kamil Omoteso and Musa Obalola
This chapter adopts Porter’s ‘audit trinity’ approach comprising internal audit, external audit and audit committee to discuss the role auditing can play in the management of…
Abstract
Purpose
This chapter adopts Porter’s ‘audit trinity’ approach comprising internal audit, external audit and audit committee to discuss the role auditing can play in the management of corporate fraud.
Design/methodology/approach
The chapter maps the historical background of and the developments in external audit as an assurance service, the internal audit function and the audit committee. Based on this, it explains the nature, types and possible causes of corporate fraud within the context of business risk with a view to establishing how auditing can help in managing such frauds.
Findings
The chapter highlights the relationships that should exist between the three audit types in order to support a sound internal control system as a tool for preventing and detecting corporate fraud.
Research limitations/implications
The chapter identifies cost, opportunity, connivance and managerial override as factors that could limit the ability of auditing to manage corporate fraud. It also suggests ways of addressing these limitations.
Practical implications
As the current upward trend in IT adoption for corporate operations continue to open new sets of corporate fraud windows, this chapter examines how an entity’s internal controls can be used to prevent and detect these growing fraud schemes.
Originality/value
The chapter’s unique strength is its adoption of a holistic approach to auditing to suggest ways of managing corporate fraud – a novelty in the corporate fraud literature. It is hoped that future research in the area will bring empirical insights to the issues raised and perspectives covered in the chapter.
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W.S Hopwood, D. Sinason and R.R Tucker
Emphasizes that although electronic commerce continues to grow, with it come many problems including the worry of security over the Internet. Presents a systematic approach to…
Abstract
Emphasizes that although electronic commerce continues to grow, with it come many problems including the worry of security over the Internet. Presents a systematic approach to developing and continuously improving Web security systems — allowing for enterprise‐wide controls regarding security risks. Goes into much detail regarding systems, security and design.
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William Hopwood and James C. McKeown
This study presents theoretical and empirical analyses to suggest a previously‐unknown size‐related contingency in the relationship between market variables and various…
Abstract
This study presents theoretical and empirical analyses to suggest a previously‐unknown size‐related contingency in the relationship between market variables and various commonly‐used financial ratios, including Net Income/Total Assets, Current Assets/Sales, Current Assets/Current Liabilities, Current Assets/Total Assets, Cash/Total Assets, Long‐Term Debt/Total Assets, Accounts Receivable/Sales. The size contingency in this relationship is shown to be due to the cross‐sectional variability of the ratios themselves. Moreover, simply adding a size dummy to the model will not correct for the problem. Empirical results show that the effect is very strong and subjects to severe misinterpretation any study that uses financial ratios on the right‐hand‐side of a linear model.
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William S. Hopwood and James C. McKeown
This study investigates the time‐series properties of operating cash flows per share and earnings per share for all manufacturing firms on the Compustat Quarterly Industrial tape…
Abstract
This study investigates the time‐series properties of operating cash flows per share and earnings per share for all manufacturing firms on the Compustat Quarterly Industrial tape for which sufficient data are available. Both individually‐identified and “premier” models are compared on the basis of their relative fit and forecasting accuracy. The empirical results suggest that for both accounting variables the individually‐identified models outperform the premier models, although this advantage is larger for earnings, and for forecast horizons beyond one quarter ahead. A major conclusion of the study is that the time‐series properties of cash flows are quite different than those of earnings. In particular, the cash flow series are considerably less predictable, as shown by their relatively high incidence of white‐noise series and relatively large forecast errors.
Annual changes in financial ratio values are susceptible to ambiguous interpretation because of different applications of generally accepted accounting principles and different…
Abstract
Annual changes in financial ratio values are susceptible to ambiguous interpretation because of different applications of generally accepted accounting principles and different numerator/denominator component selections. The paper investigates financial ratio disclosure within annual reports, and the extent to which the underlying ratio components vary within and between companies, within industries and over time. Financial ratios disclosed voluntarily within the annual reports of 101 listed public companies in Hong Kong between 1988–1992 were examined. Findings indicate numerator‐denominator inconsistency between companies and industries at a point in time, but generally consistent within companies across time. Also, sets of ratios reported between years are not constant. Ten potential research questions about financial ratios have been identified.
Professionals who carry out the forensic accounting profession must have an extensive knowledge of accounting, as well as an effective knowledge of law, auditing, internal audit…
Abstract
Professionals who carry out the forensic accounting profession must have an extensive knowledge of accounting, as well as an effective knowledge of law, auditing, internal audit, business management, psychology, crime science, and, in particular, computer technologies. In today’s digital business environment, it has become difficult to identify fraudulent transactions with traditional methods. Developments in information (data) and information technology have helped increase anti-fraud control programs and fraud research opportunities. In particular, fraudulent financial reporting disrupts the reliability, accuracy, and efficiency of financial markets in terms of existence and continuity. The forensic accounting profession has been able to improve the effectiveness of inspections by using big data techniques, data analytics, and algorithms (Rezaee, Lo, Ha, & Suen, 2016; Seda & Kramer, 2014; Singleton & Singleton, 2010).
The aim of the author, in this chapter, is to evaluate the contribution of using big data techniques in forensic accounting applications and the skills that will be provided to students while integrating these techniques in forensic accounting trainings. For this purpose, studies on forensic accounting education and their applications were reviewed. In addition, opinions were evaluated by considering the relevant literature about the importance of big data, benefits of big data, use of big data techniques, and interest shown of them.
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Paul Fallone and Carmelo Giaccotto
The authors derive the probability distribution of the net present value of a project under the quite general assumption that the cash flows follow either an autoregressive moving…
Abstract
The authors derive the probability distribution of the net present value of a project under the quite general assumption that the cash flows follow either an autoregressive moving average process or an integrated autoregressive process. Examples are presented which serve to both illustrate the application of the results as well as to underscore how to use utility functions for decision making, how to determine a project's Internal Rate of Return, and the dynamic resolution of uncertainty.
This 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…
Abstract
Purpose
This 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/approach
This 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.
Findings
There 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/value
The 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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Russell Calk, Paul Haensly and Mary Jo Billiot
This study applies a model of systematic belief revision to examine the effect of the relation between current‐period unexpected earnings and prior‐period security returns on the…
Abstract
This study applies a model of systematic belief revision to examine the effect of the relation between current‐period unexpected earnings and prior‐period security returns on the current period relation between those unexpected earnings and returns. Cross‐sectional analysis blurs the effects of past information on current returns in a manner that makes it easy to overlook any dependence on historical patterns in this information. We show that the market responds to earnings innovations conditional on these patterns but does not respond in the manner predicted by the Hogarth and Einhorn (1992) belief adjustment model. Nonetheless, the results suggest that individual decision processes are detectable in capital markets data.