Auditing and data analytics

2021/2022

Content, progress and pedagogy of the module

Growing trends towards more integrated use of data from multiple sources allow informing business decisions and draw conclusions and are increasingly also affecting the audit profession. Data analytics techniques have the potential to enhance audit quality and create a more robust understanding of an organisation, its environment, and financial performance.

The module provides the students with knowledge of information technologies and techniques used in data analytics, and the ways the available technologies can be applied in the audit process. It gives an overview of how information technologies are used in digitalising business transactions and the creation of accounting data, and how various technologies can be used to assist the auditor. It involves an outline of current developments in emerging technologies, such as big data, artificial intelligence, machine learning etc., and the potential impact of these technologies on the conduct of audit and audit quality.

The module provides knowledge on the basics of data analytics in general and the computer-assisted audit techniques (CAATs) in particular, covering the theoretical concepts and methods, and the practical application and challenges of data analytics.The discussions of the topics in this module also involve considerations of ethics and GDPR (The General Data Protection Regulation). 

Learning objectives

Knowledge

The objective is that the student after the module possesses the necessary knowledge on:

  • the contemporary technologies of digitalisation in auditing.
  • the basics of data analytics and the ways data analytics can support the audit process.
  • the computer-assisted audit techniques (i.e. audit analytics).

Skills

The objective is that the student after the module possesses the necessary skills in:

  • assessing the relevance and usability of different data sets.
  • assessing the relevance of different data analytics techniques.
  • applying audit analytics techniques in practice.

Competences

The objective is that the student after the module possesses the necessary competences in:

  • choosing between tools and methods available in data analytics and applying them.
  • identifying and troubleshooting the common problems in implementing data analytics in auditing.
  • examining different data sets and drawing conclusions.

Type of instruction

For information see § 17.

Exam

Prerequisite for enrollment for the exam

  • Prerequisite for the exam is a submission of a series of assignments during the semester. This set of assignments (portfolio) is then the basis for the oral examination.

Exams

Name of examAuditing and data analytics
Type of exam
Oral exam based on a project
Group examination with max. 4 students. The student may also choose to write the project alone.
ECTS10
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleRevision og dataanalyse
Module codeKAREV202112
Module typeCourse
Duration1 semester
SemesterAutumn and Spring
2-årig: Modulet udbydes om efteråret.
4-årig: Modulet udbydes om efteråret og foråret.
ECTS10
Language of instructionDanish and English
Location of the lectureCampus Aalborg
Responsible for the module

Organisation

Study BoardStudy Board of Auditing
DepartmentAAU Business School
FacultyThe Faculty of Social Sciences