Course 2023-2024 a.y.

• Session 1 - Introduction to the course and to some definitions
• Sessions 2-7 - Focus on Prevention - risk management, risk assessment and internal controls: principles and  methodologies for both qualitative and quantitative risk analysis (examples of quantitative techniques: sampling for internal controls and Monte Carlo simulation for risk assessment);
• Sessions 8-14 - Focus on Detection -  a framework for fraud risk management and detection (the fraudster’s Fraud Triangle, the  detection process: from a suspected fraud to the proof of intentionally): principles and methodologies for both qualitative and quantitative investigations (examples of quantitative techniques: computer forensic, data mining, big data, network analysis);
• Sessions 15-21 - Focus on some Fraud Schemes (lessons learned from famous scandals): analysis of some fraud schemes in order to understand the failure of governance, risk management and internal controls; examples: internal transactions frauds, Ponzi’s scheme, Accounting Scandals, Concealment of financial distress, Money Laundering and more…)
• Sessions 22-24 - Presentation of Group Assignment and conclusions

• Understand the main methodological steps of risk assessment and risk management
• Understand what are the most common corporate frauds.
• Understand the difference between fraud prevention and fraud detection (and what are the relevant methodologies and techniques).
• Understand the difference between earnings management and fraudulent financial reporting.

• Make an overall assessment of business risks and fraud risks (fraudsters, opportunities, fraud schemes and red flags).
• Apply some fraud detection techniques based on financial analysis and data analytics.

• Online lectures
• Exercises (exercises, database, software etc.)
• Case studies /Incidents (traditional, online)
• Group assignments

Students are required to understand how to use some easy tools of Data Analytics.

An online forum will stimulate students to questions and discussione about concepts, problems and possibile solutions.

In order to promote active participation to classes and to improve the quality of learning, students are asked to accompany their class participation with 1 group assignment. This assignment is estimated to require on average 10-days working time and is evaluated by instructors, thus becoming an integral part of the final individual evaluation. The assignment will be supported by written guidelines and formats prepared by instructors and uploaded on the course website. Each group delivers the written output of the assignment to the instructor according to the guidelines received. Each group must be ready to make a brief presentation to the classroom according to a schedule that will be defined and communicated by the instructors. Groups may choose one of following assignments:

1.Detection of a financial fraud (with a quantitative Network Analysis);

2.Detection of an accounting fraud (with a qualitative Network Analysis)

3.Risk analysis for a business process (with Monte Carlo Simulation);

4.Data mining for fraud detection in a specific business process.

Attending Students are those students with a grade from the group assignment.

The faculty team determines student grades by using a combination of assignments and final exam. 
Students' evaluation is based on
1. Individual written exam (3 essay questions; it lasts 45 minutes): 50%.
2. Overall group assignment evaluation:  50%.

Group Assignment aims at verifying the ability to apply the methodologies and techniques  presented during the course and to critically analyze and evaluate  a specific case study.
The final  exam is based on essay questions to verify the general understanding of the topics and related professional case studies illustrate during the course. 

Individual written exam (essay questions; it lasts approximately 1 hour and 15 minutes): 100%.
This exam will include 2 additional questions based on a list of 4 papers (provided by the teachers).
The final  exam is based on essay questions to verify the general understanding of the topics and related professional case studies illustrate during the course where the topics are practically discussed.
Questions about the additional papers are foscued on some critical issued in the fields of risk assessment and fraud detection.

• Slides, readings, case studies and other materials are provided during the course. Students need to refer to each specific session in the elearning Blackboard platform.

• Slides, readings, case studies and other materials are provided during the course. Students need to refer to each specific session in the elearning Blackboard platform.
• 4 additional papers provided by the teachers on the Blackboard platform.