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Forensic Accounting Fraud Analytics

Data Analytics, process of transforming input data into useful information through proper analytic tools, is relevant to all business professionals. This process enhances the decision makers’ ability to use data effectively, in order to better understand the cases that they are dealing with, and to provide better, consistent, and to the point decision models to solve a wide range of business problems. This course is designed to introduce necessary tools and techniques to improve students’ applied data analytics skills in the area of forensic accounting so that they will have the required knowledge and expertise to put an auditing mechanism in place to detect fraud, problems, or anomalies in accounting data. Students will learn both theoretical and practical sides of analyzing large data sets.

Find full course description in the course catalogue.    


The grade for the course consists of two parts:

  • Coursework counting app. 40 %
  • 3-hour written exam counting app. 60 %


The written exam is online and presence in Aarhus is not nescessary.

Admission Requirements

Course specific:

A Bachelor's degree in Economics and Business Administration or a related degree.  


Exchange Students: nomination from your home university

Freemovers: documentation for English Language proficiency

You can read more about the admission here.


Mustafa Canbolat


Academic profile


Mustafa Canbolat is an Associate Professor at the School of Business and Management, State University of New York at Brockport, USA. His main academic interests are Business Data Analytics, Production and Operations Management, Supply Chain Management, Project Management, and Data Analytics and Outlier Detection Models.