Concentration Course Descriptions
Fraud and Forensic Accounting (MAcc 663): This course provides a background in all areas of forensic accounting including: fraudulent financial reporting, prevention and detection of fraud, courtroom procedures, interviewing skills, and cyber-crime. A wide variety of teaching tools are employed including extensive use of the professional literature, case analysis, videos, role-playing, and text materials.
Fraud Detection and Deterrence (MAcc 665): This course provides a background in all areas of fraud deterrence with a strong emphasis on internal control. Additional topics include deterrence through analysis of fraudulent financial reporting, prevention and detection of fraud, expert testimony, and intellectual property. A wide variety of teaching tools are employed including extensive use of the professional literature, case analysis, videos, role-playing, and text materials.
Business Valuation: Fundamentals, Techniques & Theory (MAcc 667): This course provides an in depth study of the fundamentals of business valuations including basic, intermediate, and some advanced concepts and methodologies required by accounting and financial professionals in valuing a closely held (privately owned) business where there is no market price.
Business Intelligence Technology and Data Mining (MBAD 610): This course provides an introduction to data mining methods and demonstrates how data mining can be employed in various accounting, business and forensics projects. A subset of the following issues, based upon student interest, will be discussed:
• Introduction to data mining methods for data cleaning, finding reliable indicators and key factors, feature selection, pattern and outlier detection, anomaly detection, automated classification, segmentation, clustering, regression, forecasting, predictive analytics
• Basics of cost-sensitive machine learning and data mining
• Identifying profitable business units, and what characteristics make them so
• Identifying behavioral changes – detecting opportunities and risks
• Detecting patterns, irregularities, and indicators for identifying and preventing improper accounting practices, dubious transactions, potential fraud, money laundering, or other undesired activities
• Credit scoring, credit default prediction, and risk factors for risk assessment, mitigation, and minimization
• Predicting future demand, prices, and sales
• Optimizing controlling actions by cost-sensitive data mining
• Mining structured and unstructured data, i.e. database tables as well as e.g. textual information using statistical analysis, data and text mining
Evidence Management and Presentation: This course examines legal issues and practical considerations involved in the collection, acquisition, analysis and storage of digital evidence. Presentation of digital and technical evidence to judges, juries and other decision makers. The law of evidence and its implications for the manner and method technical evidence is acquired and presented for consideration in court or in other proceedings (i.e. criminal, civil, or administrative). Requirements and preparation for the presentation of technical evidence as an expert or fact witness.
