Digitalization poses a major challenge for companies. Auditors are also affected by this, because they have to understand what changes are taking place and meet the new expectations of their clients.
What exactly is the impact of digitalization on the work of auditors? What technological changes does the industry itself need to make? How will the requirements for accountants change?
David Port proves why the digital transformation is also necessary for the auditing industry. In particular, an adjustment of the job description and the service portfolio, the competencies and the training of the examiners is necessary. Port presents a solution for practical implementation.
From the content:
- technology;
- paradigm shift;
- Accounting;
- expectations;
- competitiveness;
-Data Privacy
Table of contents
Table of contents
List of abbreviations
Abstract
1 Introduction
2 Digitalization as a paradigm shift
2.1 Definitional demarcation
2.2 Development towards Industry 4.0
2.3 Technological drivers of Industry 4.0
2.3.1 Internet of Things (IoT)
2.3.2 Big data
2.3.3 Cloud Computing
3 Digitalization-related transformation of auditing
3.1 Auditing and Industry 4.0
3.2 Necessity of the transformation of auditing
3.2.1 Technological disruption of audit services
3.2.2 Changing expectations
3.2.3 Maintaining relevance
3.2.4 Competitive factor
3.3 Digitalization - Risk and Opportunity
4 Digitalization-immanent changes in auditing
4.1 Job description
4.2 Business orientation and personnel policy
4.3 Market structure
4.4 Service portfolio
4.5 Examination design
5 Analysis of selected critical success factors
5.1 Legal competence and implementation
5.2 Degree of digitization of the client
5.3 Data acquisition and processing
5.4 IT security and data protection
5.5 Compatibility with professional principles
5.6 Overcoming classic exam limitations
5.7 Possible problems of trust and abuse
6 Development towards auditing in Industry 4.0
7 Conclusion
Bibliography
Trade journals
Internet Sources
Books
Standards
List of abbreviations
Abbildung in dieser Leseprobe nicht enthalten
Abstract
The general goal of the propounded thesis is to evaluate the impact of digitalization on the field of auditing with a particular focus on auditors and financial statement audits. The German concept of 'Industrie 4.0' is used as an exemplified tendency of digitalization in industrial production to explain technological changes occurring in the client's business accounting and how they affect auditing. These changes underline the necessity of a digital transformation of audit in order to sustain and improve audit quality and efficiency in a changing environment as a well as to stay relevant to stakeholders of this industry. Continuous audit procedures and the use of data analytics are presented as the key progress that audit needs to deliver on to undergo a successful change. From this a variety of foreseeable changes are derived that constitute what audit will look like if this transformation occurs successfully for example with respect to the auditor's future competency profile and the audit market. However, several factors are explored such as regulation or issues around data acquisition and analysis that cannot directly be impacted by single auditors or auditing firms that therefore have a tremendous amount of influence towards allowing auditing to successfully complete this transformation. By applying the concept of audit-as-a-service (Kiesow 2016) to the challenges arising from 'Industrie 4.0' some of them are taken into consideration appropriately which goes to show that, though not all problems are dealt with yet, it provides an adequate starting point to transform audit. It represents one reasonable solution to the portrayed 'Industrie 4.0' scenario and provides an idea of what auditing in this field may look like in the future.
1 Introduction
A cross-industry study published in 2015 on the influence of digitization on the German economy came to the conclusion that 55% of the companies surveyed are adapting their business model as a direct consequence and that 70% see digitization as a major challenge.1
The operational accounting of companies is not a special feature in this respect, as it is characterized by increasing networking with value-added processes, computerization and automation.2 is also faced with significant changes. Since the original task of the auditor is to audit the accounting information relevant to the annual financial statements provided, it is obvious to assume that the audit in particular but also the auditing industry as a whole is massively affected by these developments.
A much-noticed study on the US labor market by Frey/Osborne (2013), in which a large number of occupations were evaluated on the basis of the activities carried out with regard to their risk of being substituted by computers within the next 20 years in the course of digitization, calculates a probability of 94% for auditors and 98% for their assistants.3
The fact that such generalizing statements are to be viewed critically in principle is unquestionably true, yet such forecasts illustrate the potential effects of a progressive digitization of the economy on auditing.
Within the scope of this work, the example of Industry 4.0, as a new industrial production paradigm that has grown out of digitization, will therefore be used to investigate the external influence that a development of clients in this direction exerts on the audit and how this is to be assessed.
Central technological innovations used in Industry 4.0 are examined for their disruptive influence on the business model of auditing and thus inevitably resulting changes as well as the necessity of a possibly to be initiated transformation of the industry are worked out.
Based on this, the derivation and critical analysis of decisive success factors of such a transformation, as well as the reflection of resulting core challenges, which are particularly important. for audit services in such a changed business environment. Finally, with the transfer of an extended business model discussed in the literature to the requirements and circumstances of statutory audits in Industry 4.0, a possible sustainable approach for audit services and auditors in this changed environment is to be proposed.
2 Digitalization as a paradigm shift
2.1 Definitional demarcation
The fundamental process of digitization consists in the transfer of analog values into digital, for the purpose of electronic storage, transmission and processing.4 A specification approach in the context of economic value creation, carried out by Wolf/Strohschen (2018), according to which digitization refers to analog service provision, which is replaced in whole or in part in a digital and computerized model.5 Thus, in addition to a digital transformation of data and information, the term digitization also covers the computerization and automation of business processes through the networking of information, machines, people and technology.6
Based on this, the term digital transformation describes the application potentials arising in the course of digitization and the associated use of new technologies. These essentially consist of the revolutionized acquisition of data and its exchange and analysis as well as a correspondingly significantly expanded ability to extract information.7 This information, due to its detail and availability in real time8 on the one hand, a special relevance with regard to the evaluation of different options for action and the resulting improved decision-making processes, but on the other hand also for the initiation of an optimal action under the circumstances.9
In this respect, digitization can quite rightly be described as a paradigm shift.
Firstly, the potential benefits of the changed technical possibilities, e.g. with regard to efficiency gains in the provision of services, are already now available for the preservation of competitive ability of entire industries indispensable.10 Dynamism, agility and the effectiveness of companies' information architecture are crucial to the competition in relation to rapidly changing markets and the rapid emergence of new markets.11 Secondly, digitization is also irreversible.12 The targeted application of digital technologies usually improves the cost-benefit ratio in contrast to established, previously market-dominating non-digitized approaches and thus has significant potential for disruption and displacement.13 The increase in performance achieved in this way vis-à-vis customers cannot be reversed without significant losses in market share.14
Thus, in the form of digitization, a continuous and irreversible development has begun, in which the vast majority of traditional types of service provision have to be forcibly realigned.
2.2 Development towards Industry 4.0
The generic term Industry 4.0 was coined within the framework of the High-Tech Strategy of the Federal Ministry of Education and Research (BMBF), which in turn is based on implementation recommendations of a working group of Acatech (German Academy of Science and Engineering) established in this regard.15 Industry 4.0 describes building on the first three industrial revolutions,16 mechanization, mass production and automation, now the networking and integration of manufacturing processes and information technology into a self-organized industrial production made possible by the digitization process described.17
Above all, it is special that this industrial revolution – generally intended as a strategy to secure Germany as a production location and prepare it for the future18 – is predicted a priori and thus not only observed ex-post, so that companies can actively steer their development in this direction in order to siphon off the expected massive economic benefits.19
The central goal of Industry 4.0 is to improve the flexibility of existing value chains by maximizing the transparency of procurement and sales logistics, production processes and marketing, as well as all other areas of the company, including accounting.20 Outstanding relevance for this have in particular. Information; the design of collection, availability, exchange and analysis of these is thus the focus of the development initiated by Industry 4.0.21 Here are sensors/actuators,22 the e.B. generate relevant information in real time with regard to the monitoring of the condition of production machines, product quality, production costs or the verification of storage location or delivery progress, also of particular importance for accounting.
The uninterrupted object-related exchange of information between machines, plants, complete factories and other parts of the value chain (including supplier and customer side) and even the product itself through an extensive network,23 enables more controllable and influenceable processes. On the one hand, business processes are improved through automation and reduction of process steps, as delays and bottlenecks can be avoided more easily with increasing information and at the same time faster order fulfillment and increased customer-specific individualization of the products can be realized.24 On the other hand, the same processes can be controlled with foresight, e.g. Sensors provide information on the condition of production plants in order to counteract possible failures or production-related defects at an earlier stage. Furthermore, precise demand forecasts and thus optimized stock levels can be integrated into production planning.25 The use of such an integration of data into production requires the development of effective methods for continuous data analysis. The extraction of information and its proper interpretation from data that becomes available within all areas of the value chain is therefore a central challenge of Industry 4.0.26
2.3 Technological drivers of Industry 4.0
The transformation to Industry 4.0 that has emerged in the course of digitization is taking place to a significant extent as part of the utilization of new technologies and concepts in the business processes of companies. Some technological trends that significantly influence and drive this change due to their versatile application possibilities are presented in detail below.
2.3.1 Internet of Things (IoT)
The pictorial designation of the Internet of Things provides a precise description of the revolutionary core aspect of Industry 4.0, the networking of objects.27 Until the emergence of this concept, objects, whether in private or industrial use, existed predominantly isolated from each other and were often, if at all, only connected to each other by external control systems or by hand by humans.28 In the Internet of Things, objects not only collect information about themselves and their environment, but also interact and exchange data with other objects via wireless connections in a network.29 Objects are not limited to machines or production plants, but can represent all objects required in the value creation process, up to unfinished products or tools.30 For Industry 4.0, such IoT infrastructures exist in which company resources independently and continuously communicate information on status, environment, production process and maintenance,31 significant potential with regard to the provision of operational services. As such, the improvement of planning and value creation structures in and around factories, as well as the optimization and automation of production processes are to be mentioned.32
2.3.2 Big data
On the one hand resulting from the continuous and at the same time mass data exchange as well as a large number of different data sources within IoT-integrated value chains of Industry 4.0 and on the other hand due to the use of external data sources, e.g. social media, a barely manageable mass of data is brought together under the term big data.33
These can be characterized by '3 Vs': 'Volume, Variety and Velocity'.34 'Volume' describes the mass of stored data for processing and analysis,35 'Variety' the circumstance of the structural heterogeneity of the data sets, also with regard to their variable origin and format36 and 'Velocity', the speed required for generation, transmission, processing and evaluation.37
However, a collection of data that is difficult to access in this form, described by the 3 V's, does not in itself provide any added value. Their actual potential can only be tapped through active involvement in the control of decision-making processes, which in turn first requires the development of so-called data analytics.38 They can increasingly extract and process useful information from rapidly changing, highly diverse and unstructured, extensive data sets. Big data therefore refers not only to the data itself, but also to the underlying methods of data analysis.
2.3.3 Cloud Computing
The last technological trend to be explained in relation to the topic is the increasing use of cloud computing. Cloud computing is to be understood as a fundamental technology for the feasibility of the aforementioned characteristics of Industry 4.0, the high level of networking of the IoT on the one hand and the automated organization of production processes based on it on the other.39 Cloud computing services are usually IT services offered by third-party operators, which can be offered both in the form of infrastructure (the provision of computing power and storage capacities), software (access to cloud-based applications) and platform (the possibility to operate specially developed or purchased software in cloud structures).40
In the context of Industry 4.0, they are particularly suitable for central storage, administration, evaluation of data, as well as central access to IoT components.41 It should be mentioned that centrality refers only to use, while the actual infrastructure is usually decentralized and distributed. Cloud computing serves as the infrastructure for Industry 4.0 efforts42 and allows companies to keep the investments in IT infrastructure and IT solutions associated with this development at an appropriate level compared to self-provided solutions, while at the same time reducing empty costs, as capacity in cloud computing is made available on demand, and personnel and operating costs.43
3 Digitalization-related transformation of auditing
Now that the introductory presentation of the digitization-driven development towards Industry 4.0, including its properties, principles and technologies, has been made, the relationship of these profound changes to auditing will be presented.
3.1 Auditing and Industry 4.0
The development of Industry 4.0 is not to be considered in isolation with regard to the industry itself, but also exerts a considerable influence on the intermediaries to the capital markets. As such,44 the auditor must understand the disruptive nature of the changes in the corporate environment of his clients as well as the emergence of new and the change of existing business models.45 This is not least important for the i.S.d. § 38 Abs. 3 der Berufssatzung der WPK i.V.m. § 57 sec. 3 WPO is a basic prerequisite for an appropriate audit.
The aim of the annual audits carried out by the audit is acc. IDW PS 200 paragraph 8 f. the assessment and confirmation of accounting information with sufficient certainty. This fundamental task also illustrates the problems facing auditing in the context of Industry 4.0, as it requires an extensive understanding of the business model, as well as the control and accounting process.
Progressively automated accounting processes in such an environment, e.g. with regard to the recording and processing of accounting-relevant data, are increasingly upstream of the actual accounting process,46 which consequently means that these more complex and highly integrated systems become much more relevant on the auditor's side.47
The problem continues in the provisions of the IDW PS 330.48
E.g. Paragraph 8 asks how the auditor can continue to ensure that, before accepting an audit mandate, he is able to obtain an accurate picture of client-side IT systems if they are increasingly linked to each other throughout the company through cloud computing and contain a large number of new systems and IoT components.
In view of these developments, the question of how the client relationship can be continued on an equal footing is subsumed on the one hand by the threat of a massive loss of relevance of the industry as a whole,49 on the other hand, the extrinsic motivation to transform the exam and thus the relevance in increasingly complex business models50 to assert and expand, in space. To this end, however, the activities of auditing must be expanded to include the technical possibilities associated with digitization, thus creating added value within the audit and implementing new services on the market.51
This requires the auditing industry to deal with digitization on the one hand and, more importantly, its application within the audit processes in an appropriate manner.52 Otherwise, the industry will lose touch with the progressive digital innovation of its clients, which in the nature of the matter would lead to a decrease in audit quality and achievable audit security. Similarly, the additional effort required to maintain the quality of the audit within the audit would preclude the principle of profitability of IDW PS 200 paragraph 9.
With the development of his clients to the envisaged target state of Industry 4.0, the auditor now also has the opportunity to use the associated technological possibilities to gain real-time access to a large number of audit-relevant information.53 and automation54 to bundle repetitive audit steps with little discretion, in timely, efficient, accurate and high-quality auditing and in extended consulting services.55
The use of such technologies is not limited to the provision of services, as a corresponding implementation in the auditor's own company structures also promises potential for increasing efficiency.56
3.2 Necessity of the transformation of auditing
3.2.1 Technological disruption of audit services
The technological disruption in clients' business models cannot be without consequences for the WP. The integration of cloud computing, IoT and external sources of information (part of big data) into the systems and decision-making processes of the clients, on the one hand, provides a variety of possibilities for utilization in the audit through comprehensive data analytical procedures (so-called data analytics), but on the other hand also illustrates the need for auditing to develop further in this direction.57
In general, there is a risk for the WP in the case of audits of annual financial statements in the issuance of an incorrect audit report, i.e. an unqualified audit opinion despite material misstatements.58 Therefore, the risk-oriented audit approach requires an assessment – in particular. risky accounting areas – through appropriate audit procedures on the basis of which material errors can be ruled out with sufficient certainty.59
However, such tests in Industry 4.0, especially due to the amount of data resulting from IoT and Big Data, despite or as a result of the undeniable increase in information, can no longer be economically mastered with this traditional audit approach in the future.60 In this respect, for example, the determination of the current situation by means of a "functional and effectiveness check of the accounting-relevant parts of the ICS" as of the reporting date61 through preliminary checks, neither the dynamics and complexity of the digitized and automated business processes, nor the fast pace and availability of the information62 sufficient invoice.
In order to be able to continue to ensure sufficient security in the face of changed client-side circumstances without massively increased effort, the requirement of continuous audit arises, as will be shown in the further course.63 and an implementation of data analytics.64
Since Industry 4.0 or the information architecture of a corresponding client allows the use of such modern data analysis methods, the examiner has various possible applications with regard to testing. First of all, the possibility of complete analyses, i.e. of 100% of transactions, even within a large (growing) population, must be mentioned,65 which represent an enormous extension compared to the testing of random samples, while ensuring high audit quality.66 Furthermore, such mass data analyses are not only an answer option with regard to increasing data volumes, but also allow the auditory assessment of identified error risks.67 Since SMEs, in the context of Industry 4.0, are also recording rapidly growing amounts of data and process complexity, but the expansion of the ICS in this regard often does not take place at the same speed, the auditor can use these analyses, for example.B. to obtain a very precise assessment of the extent to which any control weaknesses (e.g. in the IT authorization concept) have actually influenced transaction data.68
Process mining is the name of another disruptive technology on the part of examiners, which makes certain 'analogue' audit procedures, such as the conduct of interviews and surveys, largely superfluous and thus has further efficiency potential.69 As a data analysis tool, Process Mining allows the visualization of individual work steps carried out on the client side with regard to end-to-end business processes, based on the data available in the client's ERP system and thus the identification of risky deviations from defined standard processes.70 For example, Ruhnke (2019) shows how strong these deviations from the target process can actually be in companies and how such process analyses can contribute to process understanding and control risk assessment for the auditor in view of increasing complexity.71
Software-supported data analytics also offer the advantage that they have a high automation potential, since after initial adjustment of the parameters to the circumstances of the client, analyses can be repeated as often and continuously as desired.72
In addition to the analysis of internal business factors, the analysis of the client's macroeconomic framework conditions must also be mentioned.73 Here, the fact that external data is also collected in the context of big data provides considerable advantages in terms of identifying business and fraud risks and creating expectations. (e.B. development of sales revenues) Also for the Going Concern assessment74 according to § 252 Abs. 1 Nr. 2 HGB i.V.m. IDW PS 270 para. 4., which is naturally characterized by a multitude of "different factors and their relationship to each other"75 is conditional, there is a high relevance.
Furthermore, big data combined with so-called predictive analytics, i.e. predictive data analyses, allows an improved quantification of estimates. An application example for this is the audit assessment of the future development of warranty claims against the client, for example through evaluation tools that analyze social networks,76 which are often used by end users for exchange in case of any problems, etc.
[...]
1 cf. Bitkom (2015)
2 cf. Beyhs/Poymanov (2019), p. 19 f.
3 cf. Frey/Osborne (2013), p. 1 f.
4 cf. Mertens et al. (2017), P. 35
5 Wolf/Strohschen (2018), p.58
6 cf. Hanschke (2018), p.3
7 cf. Schallmo (2016), p.5
8 cf. Beyhs/Poymanov (2019), p. 21
9 cf. Hanschke (2018), p. 48
10 cf. Hanschke (2018), p. 1
11 cf. Wolf/Strohschen (2018), p. 57
12 cf. Oswald/Krcmar (2018), p.7 f.
13 cf. Oswald/Krcmar (2018), p.7 f.
14 cf. Obermaier (2017), p. 5
15 cf. BMBF (2013), P. 81
16 cf. Pfeiffer (2015), o.S.
17 cf. Zaeh (2018), p. 449
18 cf. BMBF (2017), p. 17 f.
19 cf. Hermann et al. (2015), p. 379.
20 cf. Dai/Vasarhelyi (2016), p. 1
21 Cf. ibid.
22 cf. BMBF (2013) P. 95
23 cf. Drath/Horch (2014), p. 3
24 cf. Ematinger (2018), p. 11
25 cf. Ematinger (2018), p. 10
26 cf. Dai/Vasarhelyi (2016), p. 1
27 cf. Zaeh (2018), p. 449 f.
28 cf. Oswald/Krcmar (2017), p. 20 f.
29 cf. König/Graf-Vlachy (2017) in Obermaier (eds.), p. 53
30 cf. König/Graf-Vlachy (2017) in Obermaier (eds.), p. 54
31 cf. Dai/Vasarhelyi (2016), p. 6
32 cf. Oswald/Krcmar (2017), p. 20
33 cf. Appelbaum (2017), p. 4
34 Cf. inter alia. Gandomi/Haider (2014), p.138
35 cf. Oswald/Krcmar (2017), p. 16 f.
36 cf. Gandomi/Haider (2014), p.138
37 cf. Oswald/Krcmar (2018), p. 16 after Rossman et al.
38 cf. Gandomi/Haider (2014), p. 140
39 cf. Fallenbeck/Eckert (2017) in: Vogel-Heuser et al. (Hrsg.), S. 142 f.
40 cf. Oswald/Krcmar (2018), p. 14 f.
41 cf. Fallenbeck/Eckert (2017) in: Vogel-Heuser et al. (Ed.), p. 139
42 cf. Kollmann/Schmidt (2016), p. 43
43 cf. Oswald/Krcmar (2018), p. 15
44 cf. Leyens (2017), p. 3
45 cf. Burg et al. (1999), p. 246 f.
46 cf. Zaeh (2018), p. 451
47 See German (2019), p. 501
48 Burg et al (2017), p. 127
49 cf. Göttsche et al. (2018), p. 4.
50 cf. Alles et al. (1999), p. 246 f.
51 cf. Rega/Teipel (2016), p. 39
52 cf. Göttsche et al. (2018), p. 4.
53 cf. Working Group External and Internal Monitoring of the Company (2017), p. 326
54 cf. Kompenhans/Wermelt (2019), p. 45
55 cf. Burg et al. (2017), P. 123
56 cf. Amschler (2017), p.119
57 cf. Appelbaum et al. (2015), p. 379.
58 cf. Beck Bil-Komm/Schmidt HGB § 317, Rn. 108 f.
59 cf. IDW PS 200 para. 9
60 cf. Kempf (2017), p. 1300 f.
61 cf. Zaeh (2018), p. 451
62 cf. Dai/Vasarhelyi (2016), p. 5
63 cf. Byrnes et al. (1999), p. 246 f.
64 cf. Lieder/Goldshteyn (2013), p. 588 f.
65 cf. Lieder/Goldshteyn (2013), p.594
66 cf. Tönsgerlemann/ Reutter (2019), p.41
67 cf. Kiesow (2016), p.710
68 cf. Lieder/Goldshteyn (2013), p.594
69 cf. Adelmeyer/Teuteberg (2016), p. 701
70 cf. German (2019), p.498
71 cf. Ruhnke (2019), p. 66
72 cf. Lieder/Goldshteyn (2013), p. 594
73 cf. Lieder/Goldshteyn (2013), p. 589
74 cf. Ruhnke (2017), p. 424
75 cf. Göttsche et al. (2018), p. 4.
76 cf. German (2019), p. 499
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