Presentation Date: Sunday August 2, 2009
  Presentation Time: 8:00 am-4:00 pm

CPE Session 16

Computer-Aided Fraud Examination & Detection

Presented By:

Conan Albrecht, Brigham Young University

Conan C Albrecht, Brigham Young University

Uday Murthy, University of South Florida

Description: SESSION CANCELLED This session will introduce methods of fraud detection using the open source Picalo toolkit. Participants will learn how to use the Picalo application, including techniques like importing of data, connecting to databases via ODBC, and working with tables and table lists. The instructors will introduce the following analysis routines

* Selection of records via direct key match, fuzzy matching, wildcards, and expressions. nked and a comprehensive list of IFRS resources is provided.

The session is sponsored by the IASC Foundation, the International Section of the American Accounting Association and the International Association for Accounting Education and Research.

nked and a comprehensive list of IFRS resources is provided.

The session is spoe use of the z-score calculation to find outliers. * Trending analysis.

Uday Murthy ran a computer-aided fraud detection course and developed many assignments. He will go through these assignments with the participants during the second half of the day.

Participants will be expected to bring laptops as the course will be hands-on.

Field of Study: Accounting
Program Level: Intermediate

Intended Audience:

Format/Structure: Conan Albrecht will train on Python and Picalo fraud routines in the morning. Uday Murthy, who taught a fraud detection course in Picalo, will go through his class assignments in the afternoon. Participants will do all the assignments on their laptops, and help will be provided.

Learning Objective: * Understand computer techniques and analysis methods that can be used for fraud detection. * Import and work with data from various sources. * Complete fraud detection routines in the Picalo platform, and program basic fraud detection scripts in Python. * Know how to run a computer-aided fraud detection course.

Prerequisites: Participants must have a laptop and have an intermediate degree of computer prowess. For example, intermediate users of Excel, ACL, or IDEA are perfect for this course. Database experience is also helpful.

Advanced Preparation Required: None

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