Aantekeningen / Notes
-
Data-Driven Control
(EBM154A05)
Lecturers: Semester 1B year 2022/2023
- F.H. Zandhuis MSc RE
Index
Lecture 1 – Introduction .......................................................................................................................... 3
The world is changing .......................................................................................................................... 4
Technological developments............................................................................................................... 4
Increased value of Data ....................................................................................................................... 5
Changing Role of Assurance (Control/audit) ....................................................................................... 7
Lecture 2 – Vision of the future............................................................................................................... 8
Control ................................................................................................................................................. 8
Data, strategy and Governance ........................................................................................................... 8
Data Governance ................................................................................................................................. 9
COBIT (Control Objectives for Information and Related Technology ............................................... 10
Key Performance Indicators (KPI) ...................................................................................................... 12
Key Risk Indicators (KRI) .................................................................................................................... 12
Romney & Steinbart -Chapter 5, 6 & 7 .............................................................................................. 13
Lecture 3 – Technical aspects of data ................................................................................................... 14
Technical Aspects of Data ................................................................................................................. 14
Business process & SQL ..................................................................................................................... 18
Giving Advice ..................................................................................................................................... 19
Lecture 4 – Data as instrument of assurance + case discussion ........................................................... 20
Instrument of Assurance ................................................................................................................... 20
Error and Fraud Detection................................................................................................................. 22
S&S Integrative Case ......................................................................................................................... 24
Continuous Auditing / Monitoring .................................................................................................... 25
Data Mining / Machine Learning ....................................................................................................... 25
Process Mining .................................................................................................................................. 26
Lecture 5 – Data as object of assurance ................................................................................................ 27
Object of Assurance .......................................................................................................................... 27
IAASB – International Auditing And Assurance Board ...................................................................... 27
Data risks ........................................................................................................................................... 28
1
, Romney & Steinbart .......................................................................................................................... 30
Lecture 6 – Standardization of data ...................................................................................................... 33
XML, HRML & XBRL ........................................................................................................................... 33
General Ledger .................................................................................................................................. 35
Lecture 7 – Standardization of data processing .................................................................................... 37
Robotic Process Automation ............................................................................................................. 37
2
,Lecture 1 – Introduction
Today’s agenda
- Data-analytics is not new
- But changes in recent years
1. The world is changing
2. Technological developments
3. Increased value of data
4. Changing role and expectations of a controller/auditor
- Course logistics
Formal Course objectives
- Explain the impact of data driven technological innovation on internal control, and more
specifically on the way assurance professionals achieve assurance about (non) financial
information.
- Identify opportunities and threats for organizations related to the application of data driven
assurance solutions, based on the specific organizational purpose, strategy and
contingencies.
- Understand and apply modern data analysis techniques for assurance purposes.
- Identify and discuss the influence of characteristics of the internal environment of
organizations, such as culture, ethics, relevant laws and regulation, strategy and governance
structure, on the application of data drive assurance in these organizations.
Learning objectives
- The controller/auditor relies on work of experts (tax, legal, valuation, IT)
- However, you must combine inputs from different domains to come to a consistent,
coherent result.
- Essential to have a high-level understanding of the essential elements of IT and data
throughout organizaitons, processes and risks
- In practice: employers and clients highly value skills and understanding in this area.
Why Both ITIC and DDC?
- Even though they overlap, they are not the same thing (IT and data)
- Both fields of knowledge are continuously growing
- Importance for (internal) control, assurance and audit have been increasing for many years,
and will likely continue to do so
- Overlap in topics have been eliminated/minimized through alignment between the two
courses.
3
, NBA data science
Only 3.2% of job openings requires knowledge of new technology.
- Data-analytics
- Robotic Process Automation (RPA)
- Data mining (trying to find patterns)
- Process mining (visualize data of a process)
- Data visualization
- Machine learning
The world is changing
Increased complexity
- People have become more demanding
- Organizations respond and react
- Growth, globalisation, interdependency
Example: VOC
Management procedures of Heren XVII, management of Dutch East India Company (1602 – 1799)
Example: Samsung Group
- Samsung founded in 1938 now Samsung Group.
- Make everything from chips to ships
- Technology and patents are part of your daily life.
- Hotels, hospital, life insurance
What does data mean for the organizations mentioned before?
Technological developments
Moore’s law, the capacity in your laptop doubles every 18 months. When you buy a laptop for 1000
dollar. You can buy next year a laptop for 1000 dollar with more calucation capacity
4
-
Data-Driven Control
(EBM154A05)
Lecturers: Semester 1B year 2022/2023
- F.H. Zandhuis MSc RE
Index
Lecture 1 – Introduction .......................................................................................................................... 3
The world is changing .......................................................................................................................... 4
Technological developments............................................................................................................... 4
Increased value of Data ....................................................................................................................... 5
Changing Role of Assurance (Control/audit) ....................................................................................... 7
Lecture 2 – Vision of the future............................................................................................................... 8
Control ................................................................................................................................................. 8
Data, strategy and Governance ........................................................................................................... 8
Data Governance ................................................................................................................................. 9
COBIT (Control Objectives for Information and Related Technology ............................................... 10
Key Performance Indicators (KPI) ...................................................................................................... 12
Key Risk Indicators (KRI) .................................................................................................................... 12
Romney & Steinbart -Chapter 5, 6 & 7 .............................................................................................. 13
Lecture 3 – Technical aspects of data ................................................................................................... 14
Technical Aspects of Data ................................................................................................................. 14
Business process & SQL ..................................................................................................................... 18
Giving Advice ..................................................................................................................................... 19
Lecture 4 – Data as instrument of assurance + case discussion ........................................................... 20
Instrument of Assurance ................................................................................................................... 20
Error and Fraud Detection................................................................................................................. 22
S&S Integrative Case ......................................................................................................................... 24
Continuous Auditing / Monitoring .................................................................................................... 25
Data Mining / Machine Learning ....................................................................................................... 25
Process Mining .................................................................................................................................. 26
Lecture 5 – Data as object of assurance ................................................................................................ 27
Object of Assurance .......................................................................................................................... 27
IAASB – International Auditing And Assurance Board ...................................................................... 27
Data risks ........................................................................................................................................... 28
1
, Romney & Steinbart .......................................................................................................................... 30
Lecture 6 – Standardization of data ...................................................................................................... 33
XML, HRML & XBRL ........................................................................................................................... 33
General Ledger .................................................................................................................................. 35
Lecture 7 – Standardization of data processing .................................................................................... 37
Robotic Process Automation ............................................................................................................. 37
2
,Lecture 1 – Introduction
Today’s agenda
- Data-analytics is not new
- But changes in recent years
1. The world is changing
2. Technological developments
3. Increased value of data
4. Changing role and expectations of a controller/auditor
- Course logistics
Formal Course objectives
- Explain the impact of data driven technological innovation on internal control, and more
specifically on the way assurance professionals achieve assurance about (non) financial
information.
- Identify opportunities and threats for organizations related to the application of data driven
assurance solutions, based on the specific organizational purpose, strategy and
contingencies.
- Understand and apply modern data analysis techniques for assurance purposes.
- Identify and discuss the influence of characteristics of the internal environment of
organizations, such as culture, ethics, relevant laws and regulation, strategy and governance
structure, on the application of data drive assurance in these organizations.
Learning objectives
- The controller/auditor relies on work of experts (tax, legal, valuation, IT)
- However, you must combine inputs from different domains to come to a consistent,
coherent result.
- Essential to have a high-level understanding of the essential elements of IT and data
throughout organizaitons, processes and risks
- In practice: employers and clients highly value skills and understanding in this area.
Why Both ITIC and DDC?
- Even though they overlap, they are not the same thing (IT and data)
- Both fields of knowledge are continuously growing
- Importance for (internal) control, assurance and audit have been increasing for many years,
and will likely continue to do so
- Overlap in topics have been eliminated/minimized through alignment between the two
courses.
3
, NBA data science
Only 3.2% of job openings requires knowledge of new technology.
- Data-analytics
- Robotic Process Automation (RPA)
- Data mining (trying to find patterns)
- Process mining (visualize data of a process)
- Data visualization
- Machine learning
The world is changing
Increased complexity
- People have become more demanding
- Organizations respond and react
- Growth, globalisation, interdependency
Example: VOC
Management procedures of Heren XVII, management of Dutch East India Company (1602 – 1799)
Example: Samsung Group
- Samsung founded in 1938 now Samsung Group.
- Make everything from chips to ships
- Technology and patents are part of your daily life.
- Hotels, hospital, life insurance
What does data mean for the organizations mentioned before?
Technological developments
Moore’s law, the capacity in your laptop doubles every 18 months. When you buy a laptop for 1000
dollar. You can buy next year a laptop for 1000 dollar with more calucation capacity
4
