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There is an increasing recognition in the public audit profession that the emergence of big data as well as the growing use of business analytics by audit clients has brought new opportunities and challenges. That is, should more complex business analytics beyond the customary analytical procedures be used in the engagement and if so, where? Which techniques appear to be most promising? This paper starts the process of addressing these questions by examining extant external audit research. 301 papers are identified that discuss some use of analytical procedures in the public audit engagement. These papers are then categorized by technique, engagement phase, and other attributes to facilitate understanding. This analysis of the literature is categorized into an External Audit Analytics (EAA) framework, the objective of which is to identify gaps, to provide motivation for new research, and to classify and outline the main topics addressed in this literature. Specifically, this synthesis organizes audit research, thereby offering guidelines regarding possible future research about approaches for more complex and data driven analytics in the engagement.

By considering the nervous system as a type of communication system with reliable transmission of signals an attempt is made to use in neurophysiology the basic information theory theses developed by Shannon for technical communication systems. Some results of different information indices calculations (those of capacity, redundancy, degree of reliability and so on) of the pulses incorporated in their functional community (neuron ensembles) are presented. A comparison is made between peripheral and central neurons information indices. The leading role of spike trains redundancy is stressed in the mechanisms of securing a reliable signals transmission in the nervous system. The relation between redundancy and randomization process of neuron spike trains structures is shown.

The probability coding and reconstruction of information in the block‐system “Coding and Reconstruction” are examined in respect of the proposed block‐system organization and Instantaneous Human Memory. A definition is given of the capacity, the law of volume distribution and the capacity of buffer “sensual” registers.

In this paper we report on the approach we have developed and the lessons we have learned in an implementation of the monitoring and control layer for continuous monitoring of business process controls (CMBPC) in the US internal IT audit department of Siemens Corporation. The architecture developed by us implements a completely independent CMBPC system running on top of Siemens’ own enterprise information system which has read-only interaction with the application tier of the enterprise system. Among our key conclusions is that “formalizability” of audit procedures and audit judgment is grossly underestimated. Additionally, while cost savings and expedience force the implementation to closely follow the existing and approved internal audit program, a certain level of reengineering of audit processes is inevitable due to the necessity to separate formalizable and non-formalizable parts of the program. Our study identifies the management of audit alarms and the prevention of the alarm floods as critical tasks in the CMBPC implementation process. We develop an approach to solving these problems utilizing the hierarchical structure of alarms and the role-based approach to assigning alarm destinations. We also discuss the content of the audit trail of CMBPC.

This chapter traces the evolution of personality trait research in the behavioral accounting literature and offers suggestions for past and future trends. These personality traits include, among others, those measured by the Myers-Briggs Type and Five Factor models (FFMs), Type A/B, tolerance for ambiguity, locus of control, authoritarianism, and the Dark Triad components of narcissism, Machiavellianism, and psychopathy. In a broad spectrum analysis of accounting journals without regard to timing or geographics, we attempt to capture the major phases of personality trait research and provide suggestions as to the surrounding environment for such progressions in the literature. In addition to more established research streams, this chapter also discusses other personality traits that have only been marginally investigated in the accounting literature, and possible directions for future research.

Labyrinth test psychophysiological experiment is elaborated to analyze possible mechanism of the probabilistic prognosis forming and realizing in the condition of essential information uncertainty. The dynamics of the probabilistic prognosis construction and improvement during multi‐stage labyrinth test solving is established. This dynamics is characterized by considerable changes of the subjective probabilities and membership function quantitative indices apparently used in the fuzzy logic of mental activity being applied in decision‐making processes realized in the condition of uncertainty. The possible link between probabilistic prognosis efficiency and some functional peculiarities of cortical hemisphere asymmetry has also been studied.

This paper analyses the use of big data techniques in auditing, and finds that the practice is not as widespread as it is in other related fields. We first introduce contemporary big data techniques to promote understanding of their potential application. Next, we review existing research on big data in accounting and finance. In addition to auditing, our analysis shows that existing research extends across three other genealogies: financial distress modelling, financial fraud modelling, and stock market prediction and quantitative modelling. Auditing is lagging behind the other research streams in the use of valuable big data techniques. A possible explanation is that auditors are reluctant to use techniques that are far ahead of those adopted by their clients, but we refute this argument. We call for more research and a greater alignment to practice. We also outline future opportunities for auditing in the context of real-time information and in collaborative platforms and peer-to-peer marketplaces.

The purpose of this study is to identify the specific skills and abilities within the broad category of data analytics that current business professionals believe are most important for accounting graduates. Data analytics knowledge is clearly important, but this category is broad. Therefore, this study identifies the specific skills and abilities that are most important for accounting graduates so that faculty can create classroom materials most beneficial for the future accounting graduates. In 2013, the Association to Advance Collegiate Schools of Business developed new standards for accounting programs, including standard A7, related to information technology and analytics. The intent of the standard clearly focuses on increasing the level of technology and analytics studied within the accounting curriculum. However, the specific details and methods for achieving the intent of A7 remain an open question. This chapter uses prior research focused on business analytics education to identify potential analytic skills, tools, techniques, and management issues of concern within the accounting profession. A survey of 342 accounting professionals identifies suggested areas of analytic competencies for accounting graduates. Specifically, the authors find preferences for skills related to data interpretation and communication over any individual technical skills or statistical knowledge. These skills suggest a role for accountants as intermediaries who may need to translate analytic activities into business language. Post hoc, the authors examine the survey results for differences based on respondent characteristics. Interestingly, female respondents report lower beliefs about the importance of analytic skills. The authors also find some differences when examining different demographics within the respondents.