Big data is at the forefront of importance across many business decisions to include risk management. The challenge is coming up with organized, targeted ways to get at the relevant data among the seemingly overwhelming mass of data to address selected management/business questions/problems. With technology, big data analytics provides a method/tool to address that challenge. All businesses can become victims of fraud, thereby suffering financial and non-financial (e.g. reputational) losses. Auditors/fraud examiners can integrate big data analytics technology to identify abnormalities and fraudulent transactions to mitigate/stop losses from fraud.

Fraud Data Analytics covers some of the topics covered on the CFE (Certified Fraud Examiner) Exam. Students will learn about different types of occupational (employee/internal) fraud schemes as defined by the ACFE (Association of Certified Fraud Examiners). This course will focus on big data analytics for fraud detection & investigation. Specifically, topics include fraud data analytics for cash skimming & larceny, billing schemes, payroll schemes, expense reimbursement schemes, and corruption. Students will have “hands-on experience” using fraud data analytics software (CaseWare IDEA) to learn how to identify red flags/abnormalities in selected fraud schemes. Cases will be used in the course.

12:00pm-1:50pm on Wednesday at MRSE B105 (Jan 30, 2017 to May 19, 2017)
12:00pm-1:50pm on Monday at CFNT CF442 (Jan 30, 2017 to May 19, 2017)
Morse B105