Course Overview

This course offers an overview of the Guide - "Managing the Business Risk of Fraud" which was jointly developed by the AICPA, IIA and ACFE. The key techniques for the prevention and detection of fraud are discussed:

1. Statistical Sampling
2. Linear Regression
3. Data Mining

Three software packages are used in the course to provide hands-on application of the concepts taught. These packages are:

1. Excel
2. RAT-STATS (HHS)
3. Audit Commander (EZ-R Stats)

Although some of the theoretical concepts and bases of random sampling are reviewed, the focus of the course is on how to use and apply each software package to arrive at statistically valid conclusions based upon a sample. The course covers all the basics, including attribute sampling, variable sampling, stratified sampling as well as the selection of sample sizes and the generation of random numbers.

The essentials of linear regression, including "best fit" curve fitting, confidence and prediction intervals, as well as charting are presented.

An overview of data mining concepts as they relate to audits is presented in order to enable the auditor to perform more efficiently undertake audit tasks previously reserved for specialists only.

Case studies will be provided to ensure the auditor will be able to apply all the concepts learned on actual audits.

Prerequisite	Employee of State of North Carolina or agency.
Advanced Preparation	None
Course Level	Intermediate
Teaching Methods	Lecture, discussion, case studies with hands-on computer use
Field	Auditing
Hours	16.0 or 8.0