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Fraud and Business Process Analytics

  • Teacher(s):   M.Baumgartner  
  • Course given in: English
  • ECTS Credits: 3 credits
  • Schedule: Autumn Semester 2019-2020, 2.0h. course (weekly average)
  •  sessions
  • Related programmes:
    Master of Science (MSc) in Management, Orientation Marketing

    Maîtrise universitaire ès Sciences en management, Orientation Behaviour, Economics and Evolution

    Master of Science (MSc) in Management, Orientation Business Analytics

    Master of Science (MSc) in Management, Orientation Strategy, Organization and Leadership

 

Objectives

  • Introduce the students to the world of fraud detection and prevention in companies.
  • Provide an overview of data analytics methods used to detect fraud.
  • Present in detail several anomaly detection techniques.
  • Illustrate the potential of using Process Mining in companies.

Contents

Titles per day:

  1. Fraud: Introduction, Definition, Prevalence
  2. Outliers: Definition, Examples, Simple Algorithms
  3. Clustering: Introduction, Examples
  4. Association Rules: Introduction
  5. Network Graphs: Definitions, Tools and Techniques, Applications
  6. Process Mining: Introduction, Definitions, Tools
  7. Written Exam

References

Fraud Analytics (Using Descriptive, Predictive and Social Network Techniques): A Guide to Data Science for Fraud Detection
Bart Baesens, Véronique van Vlasselaer, Wouter Verbeke
Wiley, 2015

Process Mining: Data Science in Action
Wil van der Aalst
Wiley, 2016 (2nd edition)

Pre-requisites

none.

Regarding programming language:
I will illustrate the large majority of methods and tools using R. An introductory level of knowledge of R is helpful, but it is not a prerequisite. The course is also about creating interest to learn R at a later stage of your career.

Evaluation

First attempt

Exam:
Without exam (cf. terms)  
Evaluation:

Continuous control during the semester, and written interrogation on the last day of the course (18.12.2019). Presence on this day is mandatory. If a student cannot be present, we will require a medical certificate.

Continuous control:
During the first 6 days of the course, I will switch from lecture to exercises regularly. The exercises form essentially the basic training for the final exam. I will ask you to read a document, to carry out a simple programming task in R, or simply to reproduce a short analysis that I showed during the lecture.

Format of final exam:
I will ask you questions, and you will need to provide written answers. The questions will cover the main aspects of the lectures, and they will be rather general. The objective is to check whether you have managed to understand the overall view. No programming is involved. The exam is closed book.

Retake

Exam:
Written 2h00 hours
Documentation:
Not allowed
Calculator:
Not allowed
Evaluation:

For students who missed or failed the written interrogation on 18.12.2019, a written exam will be organized during the retake session of 2020 (end of August-beginning of September).



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