Evolution of Auditing in Industry 4.0

 
 
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 Imagineering Audit 4.0
 
Jun Dai and Miklos A Vasarhelyi
 
 
Agenda
 
Background
 
Definition of Audit 4.0
 
Key Elements
 
Imagneering of Audit 4.0
 
Challenges
 
Conclusion and Future Research Questions
 
 
6
 
Background
 
Advances in Cyber-Physical Systems (CPS), Internet of Things (IoT), Internet
of Service (IoS), and Smart factory promote a new industry revolution
 
Industry 4.0 (Industrie 4.0) became publicly known at Hannover Fair in 2011
The German federal government announced Industry 4.0 as one of the key
initiatives to implement the German high-tech strategy 2020
 
“Industry 4.0 is a collective term for technologies and concepts of value chain
organization. Within the modular structured Smart Factories of Industry 4.0,
CPS monitor physical processes, create a virtual copy of the physical world and
make decentralized decisions. Over IoT, CPS communicate and cooperate with
each other and humans in real time. Via the IoS, both internal and cross-
organizational services are offered and utilized by participants of the value
chain.” (Hermann et al. 2015)
 
 
 
7
 
 
Audit 4.0 Definition
 
Audit 4.0 will piggyback on technology promoted by Industry 4.0,
especially the IoT, IoS, CPS, and smart factories, to collect financial
and operational information, as well as other audit-related data from
an organization and its associated parties
 
It analyzes, models, and visualizes data in order to discover patterns,
identify anomalies, and extract other useful information for the
purpose of providing effective, efficient, and real-time assurance
 
It is typically an overlay of Industry 4.0 business management
processes and uses a similar infrastructure, but for assurance
purposes
 
8
 
 
Evolution of Auditing: From 1.0 to 4.0
 
9
 
Four Elements
 
Standards
Principles
Technology
Auditors
10
 
 
Standards
 
Assurance, in the world of Industry 4.0, will be largely dominated
by formal inter-object protocols, the technical capabilities of
“things”, and the objective functions of the interlinked objects.
 
Examples:
Inventory measurement would be automated by obtaining and tracking the
current values of purchases
Products will autonomously issue alerts if they are obsolete, slow-moving, or
damaged, to prevent including or overstating the value of obsolete inventory
Manufactured inventory can be constantly measured by collecting real-time
data regarding energy consumptions of production lines and labor costs. Many
items that were overhead allocation will be measured directly
 
11
 
 
Principles
 
Interoperability: Traffic lights and cars, automatic confirmation between
two related parties
 
Virtualization: a virtual copy of the physical world – the Mirror World
 
Decentralization: each machine or device can individual decisions and
adjustments
 
Real-time capability: continuous auditing and control monitoring
 
Service orientation: any resource could be served as a service via networks
 
Modularity: using apps for analytics
 
12
 
 
Technology
 
Sensors: collect real-time accounting information, such as quantity and
quality of inventory, working hours of employees, energy consumption...
 
Cyber-physical systems: embedded computers and networks monitor and
control the physical processes, usually with feedback loops where physical
processes affect computations and vice versa
 
Internet of things: objects linked through a network
 
Internet of service: service vendors can offer their services via the internet
 
Smart factories : use CPS, and IoT/S to assist people and machines in the
execution of their tasks
 
Others: RFID, GPS, and data analytics
 
13
 
 
Auditors
 
In a world of intense automation and process scrutiny, the skillset of
auditors is to change dramatically.
 
The auditor must be much more technically trained, but processes must also be
built with untrained users in mind.
 
Auditors will have specialized dashboards that will include close to real time
alerts
 
Byrnes (2015) developed a “super-app” to supplement auditor usage of
clustering. This tool not only performs clusterization but also applies statistical
knowledge to complement auditor knowledge.
 
14
 
 
Imagineering Audit 4.0 - Overall
 
15
 
 
 
Imagineering Audit 4.0 – Inter-businesses
 
 
16
 
 
Imagineering Audit 4.0 – Intra-business
 
 
17
 
 
Imagineering Audit 4.0 –Audit Service
 
 
18
 
Challenges
 
Digital crime: technique given, technique taken
Security and privacy issues of companies’ data
Standardization of information and data
19
 
 
Conclusion
 
This paper foresees the impacts of the fourth industrial revolution
 
on
the auditing profession, imagineers the use of new schemata
promoted by Industry 4.0 for audit purposes, and identifies
challenges in the transformation towards the new generation of
auditing.
 
 
 
20
 
 
Future Research Questions
 
What new types of audit evidence can be generated and collected in the
context of Audit 4.0?
As more data will be collected in Audit 4.0, how can auditors avoid
information overload to find relevant auditing information?
How should the auditing standards be changed to adapt to the next auditing
environment?
What are the new audit procedures to be developed/ created in Audit 4.0?
What new knowledge should auditors obtain to perform audits in Audit
4.0?
What should be done to protect the security and privacy of companies’
sensitive information in Audit 4.0?
 
 
21
 
 
How should external and internal auditors cooperate to enable Audit 4.0?
Will the current audit model be changed in Audit 4.0?
What are the new roles of the different lines of defense?
How can predictive and prescriptive audits be used in Audit 4.0?
Audit 4.0 will considerably lower the cost of auditing procedures. These
are typically the result of tradeoffs of the cost of a particular procedure
versus the benefits of such examination. How will this change the depth of
examination, the procedures used, and their frequency of usage?
As many emerging technologies/systems are used in Audit 4.0, what are
new controls that should take place to examine whether the
technologies/systems operate as they are supposed to do?
 
22
 
Future Research Questions (cont.)
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Rutgers, the State University of New Jersey
 
 
Qiao Li
Miklos A
. Vasarhelyi
 
 
Introduction
 
Purpose:
Identify 
risks and discuss how a material misstatement, whether fraudulent or erroneous,
could occur
 (AICPA, 2016, 
Landis 2008, Hammersley et al. 2010, Beasley and Jenkins 2003)
 
Common
 
procedure:
Checklist
Open-ended form 
(Bellovary and Johnstone 2007)
 
What is Audit Plan Brainstorming
 
Session:
 
1/13
 
 
Limitations with Checklist:
Structurally-restrictive tool
limits 
new ideas generation
 &
 
induces biases
Uncollected experience
 
and
 
expertise
No information retrieval or recommendation support
 
Current computer assisted audit tools and techniques (CAATTs)
 
cannot
provide
 
 effective decision support for audit planning
 
risk
 
assessment
 
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: financial
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Major phases of an audit
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Client acceptance, preliminary engagement activities, audit plan, internal
control audit, business processes and accounts audit, audit completion
(
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Application to other audit phases
 
10/13
 
 
Application to other audit phases
Application of the proposed tool to: Client Acceptance
 
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29
 
POTENTIAL
DISRUPTIVE
MAINSTREAM
AUDITING
PRACTICE
REGULATI
ON
 
SUSTAINING
 
 
 
CONTINUOUS
DISCONTINU
OUS
 
AUDIT VALUE NETWORK
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Thank you!
 
31
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The evolution of auditing from manual tools to semi-automated processes in Industry 4.0 is explored in this content. Audit 4.0 utilizes technologies like IoT, CPS, and smart factories to collect data for real-time assurance, marking a significant shift in audit methodologies towards efficiency and effectiveness.

  • Auditing
  • Industry 4.0
  • IoT
  • CPS
  • Evolution

Uploaded on May 16, 2024 | 1 Views


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  1. 1

  2. 2

  3. 3

  4. 4

  5. Imagineering Audit 4.0 Jun Dai and Miklos A Vasarhelyi

  6. Agenda Background Definition of Audit 4.0 Key Elements Imagneering of Audit 4.0 Challenges Conclusion and Future Research Questions 6

  7. Background Advances in Cyber-Physical Systems (CPS), Internet of Things (IoT), Internet of Service (IoS), and Smart factory promote a new industry revolution Industry 4.0 (Industrie 4.0) became publicly known at Hannover Fair in 2011 The German federal government announced Industry 4.0 as one of the key initiatives to implement the German high-tech strategy 2020 Industry 4.0 is a collective term for technologies and concepts of value chain organization. Within the modular structured Smart Factories of Industry 4.0, CPS monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over IoT, CPS communicate and cooperate with each other and humans in real time. Via the IoS, both internal and cross- organizational services are offered and utilized by participants of the value chain. (Hermann et al. 2015) 7

  8. Audit 4.0 Definition Audit 4.0 will piggyback on technology promoted by Industry 4.0, especially the IoT, IoS, CPS, and smart factories, to collect financial and operational information, as well as other audit-related data from an organization and its associated parties It analyzes, models, and visualizes data in order to discover patterns, identify anomalies, and extract other useful information for the purpose of providing effective, efficient, and real-time assurance It is typically an overlay of Industry 4.0 business management processes and uses a similar infrastructure, but for assurance purposes 8

  9. Evolution of Auditing: From 1.0 to 4.0 Audit 1.0 Manual audit Tools: pencils, calculators Audit 2.0 IT audit Tools: Excel, CAAT software Audit 3.0 Inclusion of non- financial data in audit analytics Tools: analytical software Audit 4.0 Semi- and progressive automation of audit Tools: sensors, CPS, IoT/S, RFID, GPS ? 9

  10. Four Elements Standards Principles Technology Auditors 10

  11. Standards Assurance, in the world of Industry 4.0, will be largely dominated by formal inter-object protocols, the technical capabilities of things , and the objective functions of the interlinked objects. Examples: Inventory measurement would be automated by obtaining and tracking the current values of purchases Products will autonomously issue alerts if they are obsolete, slow-moving, or damaged, to prevent including or overstating the value of obsolete inventory Manufactured inventory can be constantly measured by collecting real-time data regarding energy consumptions of production lines and labor costs. Many items that were overhead allocation will be measured directly 11

  12. Principles Interoperability: Traffic lights and cars, automatic confirmation between two related parties Virtualization: a virtual copy of the physical world the Mirror World Decentralization: each machine or device can individual decisions and adjustments Real-time capability: continuous auditing and control monitoring Service orientation: any resource could be served as a service via networks Modularity: using apps for analytics 12

  13. Technology Sensors: collect real-time accounting information, such as quantity and quality of inventory, working hours of employees, energy consumption... Cyber-physical systems: embedded computers and networks monitor and control the physical processes, usually with feedback loops where physical processes affect computations and vice versa Internet of things: objects linked through a network Internet of service: service vendors can offer their services via the internet Smart factories : use CPS, and IoT/S to assist people and machines in the execution of their tasks Others: RFID, GPS, and data analytics 13

  14. Auditors In a world of intense automation and process scrutiny, the skillset of auditors is to change dramatically. The auditor must be much more technically trained, but processes must also be built with untrained users in mind. Auditors will have specialized dashboards that will include close to real time alerts Byrnes (2015) developed a super-app to supplement auditor usage of clustering. This tool not only performs clusterization but also applies statistical knowledge to complement auditor knowledge. 14

  15. Imagineering Audit 4.0 - Overall 15

  16. Imagineering Audit 4.0 Inter-businesses 16

  17. Imagineering Audit 4.0 Intra-business 17

  18. Imagineering Audit 4.0 Audit Service 18

  19. Challenges Digital crime: technique given, technique taken Security and privacy issues of companies data Standardization of information and data 19

  20. Conclusion This paper foresees the impacts of the fourth industrial revolution on the auditing profession, imagineers the use of new schemata promoted by Industry 4.0 for audit purposes, and identifies challenges in the transformation towards the new generation of auditing. 20

  21. Future Research Questions What new types of audit evidence can be generated and collected in the context of Audit 4.0? As more data will be collected in Audit 4.0, how can auditors avoid information overload to find relevant auditing information? How should the auditing standards be changed to adapt to the next auditing environment? What are the new audit procedures to be developed/ created in Audit 4.0? What new knowledge should auditors obtain to perform audits in Audit 4.0? What should be done to protect the security and privacy of companies sensitive information in Audit 4.0? 21

  22. Future Research Questions (cont.) How should external and internal auditors cooperate to enable Audit 4.0? Will the current audit model be changed in Audit 4.0? What are the new roles of the different lines of defense? How can predictive and prescriptive audits be used in Audit 4.0? Audit 4.0 will considerably lower the cost of auditing procedures. These are typically the result of tradeoffs of the cost of a particular procedure versus the benefits of such examination. How will this change the depth of examination, the procedures used, and their frequency of usage? As many emerging technologies/systems are used in Audit 4.0, what are new controls that should take place to examine whether the technologies/systems operate as they are supposed to do? 22

  23. A conceptual framework of an audit plan cognitive assistant Qiao Li Miklos A. Vasarhelyi Rutgers, the State University of New Jersey

  24. Introduction What is Audit Plan Brainstorming Session: Purpose: Identify risks and discuss how a material misstatement, whether fraudulent or erroneous, could occur (AICPA, 2016, Landis 2008, Hammersley et al. 2010, Beasley and Jenkins 2003) Common procedure: Checklist Open-ended form (Bellovary and Johnstone 2007) Limitations with Checklist: Structurally-restrictive tool limits new ideas generation & induces biases Uncollected experience and expertise No information retrieval or recommendation support Current computer assisted audit tools and techniques (CAATTs) cannot provide effective decision support for audit planning risk assessment 1/13

  25. Proposed Audit Cognitive Assistant Luca Open an application Luca Luca industry Luca Interface Luca Query Client Processing Recommended Topics: General understanding, new events, business risks Position You may also interested in: Domain: judgement or experience Unstructured: financial statements, accounting policies, Show Answer Answer Modules: Capability Search engine such as google ACL, IDEA Ratios; others like Benford s law Regulations related to the audit area or account Required procedures, guidance or programs Open prior audit Audit plan schedule Ap p 1 2 3 Automatic Speech Query Classifier analytical procedures, litigation, claims, recent news information, audits workpapers, prior year audit deficiencies and adjustments User interaction: queries and search Architecture Automatic Speech Recognition QA Recognition (ASR) Language Understanding Knowle dge Base Question or Action 4 Dialogue Management DBMS Natural Language 5 text Generation Action 6 7 Text-to-Speech synthesis Execute Action Audit Related ApplicationsIt Can Access Knowledge Database Open (ACL, IDEA ) Web Search Calculato r backstage s Domain Knowledge Knowledge about users Unstructu red data upporter Open standards Open templates Audit work paper 4/13 Calendar .

  26. Luca Q-A Module Answer Answer Selection Question Question Analysis Knowledge base Machine Learning Models Answer with highest score Normalized Question Doc. With Candidates Generated Query Keyword extraction; Punctuations, abbreviations, nouns and verbs Query Generation Answer Matching Answer Extraction + IR-based (Domain) QA + Knowledge-based (Cognitive) QA DBMS Paired QA Answer NL Answer Generating 5/13

  27. Application to other audit phases Major phases of an audit: Client acceptance, preliminary engagement activities, audit plan, internal control audit, business processes and accounts audit, audit completion (Messier et al. 2016). Client acceptan ce Preliminary engagement activities Audit plan Internal control audit Business processes and accounts audit Audit completion Decision support in the cognitive assistant -Information Retrieval -Recommendations -App connections Collected Knowledge -NLP conversation 10/13 analysis framework

  28. Application to other audit phases Application of the proposed tool to: Client Acceptance Decision Support Information Retrieval Detailed design Technical support and knowledge sources Question Sub-question categories categories Management Management integrity, Management tone toward financial reporting, management competence, turnover of key personnel; Available files: entity documents and reports Financial health Financial distress, financial leverage, profitability of company, company cash flow, stock volatility Complexity of company, business changes, Accounting & Finance Dept personnel competence, internal controls, litigation risk/ prior restatements, significant related party transactions, strain the client puts on the audit firm s staff, reasons for change of auditors Audit committee competence, Audit committee financial expertise Availability of appropriate personnel, sufficient expertise of personnel, profitability of engagement Client Continuance Significant event; conflicts over accounting and auditing issues; disputes over fees files financial statements, income tax returns, etc. - Regulations, audit standards - Received inquiry from third parties - Notes from meetings discussion - Memo or completed entity acceptance questionnaire or checklist - Documented inquiries from predecessor auditor - Copies of working papers from predecessor auditor - Risk rating from audit programs Collected knowledge teleconference, meetings, inquiries Collected knowledge: Documented observations and inquires; converted inquires and meeting discussions Company characteristics Knowledge type Details Format to save in the QA system Governance Auditor characteristics Sub question categories; Updated related topics discovered from adaptive learning module Recomme ndation Pre-defined recommendation table; Adaptive learning module Service Delegation module - Financial information: annual reports, interim Available IR-based QA system and knowledge QA system Applicatio ns Audit programs/tools 11/13 - Converted knowledge from conversational Knowledge QA system

  29. Contract Analytics and Technological Process Retrofitting ZHAOKAI YAN 29

  30. AUDIT VALUE NETWORK SUSTAINING CONTINUOUS DISCONTINU OUS AUDITOR TECHNOLOGY ACCEPTANCE (MODIFIED UTAUT) PERFORMA NCE EXPECTANC Y SOCIAL INFLUENCE EFFORT EXPECTANC Y FACILITATIN G CONDITION S INDIVIDUAL DIFFERENC E MAINSTREAM AUDITING PRACTICE REGULATI ON PRICE VALUE INDEPENDENT PROCESS POTENTIAL DISRUPTIVE CLIENT FIRM USAGE ADVISORY AUDIT MARKET

  31. Thank you! 31

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