Detecting Fraud Using IDEA                          16 CPE
Instructor:  Scott Langlinais 

In this two-day hands-on seminar, attendees will apply data analysis techniques to real-life fraud scenarios using data files and case studies to identify and solve problems.  Our goal is to teach audit and accounting professionals to detect fraud, waste and abuse early and address them professionally.  

Who should attend:  Auditors, Investigators, Accounting Professionals.  
Whether you are a seasoned investigator or someone seeking a better understanding of what can go wrong in your organization, you will benefit from this program.  Novice auditors or those new to data analysis will learn and employ fundamental detection techniques to real cases, while advanced users and investigators will apply their knowledge in new and challenging ways to detect buried symptoms within complex schemes.

Attendees should bring a laptop computer with IDEA software installed and updated.  The Instructor will provide downloadable data for use in class.  Don't use IDEA?  A free demo version of IDEA software will be provided to you.

From the opening exercise, we will employ a team approach to solving cases, as in the field.  Within IDEA, you will apply to actual case data: Creative Extractions; Statistical Analyses; Join-matches & mismatches; Trend Analysis; Pivot Tables; Embedded Functions; Field Manipulation; Numeric & Date Stratification; Benford's Law; Data Duplications & Exclusions; and more!

Register Now!  Register online using the link above.  Register over the phone by calling 214-361-8346.

Program Fee = $895             Register by September 12 = $845

Team Discount: 2 or more from the same organization = $745 ea.

Program fee is payable with registration to Courtenay Thompson & Associates, P. O. Box 822343, Dallas, TX 75382 by check or pay by credit card online.  Contact our office if an invoice is required.  Fee includes instruction, all program materials, lunch and refreshment breaks.

Cancellation and Refund: Substitutes will be accepted until the program starts.  Cancellations will be accepted up to 7 calendar days prior to program start without incurring a $50 late cancellation fee.  Full fee is charged for failure to attend when enrollment has not been cancelled as specified.

Learning Objectives

Attendees will understand how to...

• Apply a five-step approach to fraud detection, and avoid the dangers of mishandling cases.
• Blend traditional detection methods with data analysis techniques.
• Correct problems with the data import, identifying missing and hidden data.
• Keep data organized and use editable fields to isolate problems.
• Employ more creative extractions to increase the chance of detecting wrongdoing.
• Use effective techniques for detecting circumvention of system controls.
• Extract symptoms embedded within blocks of data.
• Identify symptoms of theft and fraudulent reporting within common processes.
• Use principles of effective thinking and presentation to compile strong evidence.

Course Contents

Preparing to Detect Fraud

• Factors that discourage us from detecting fraud.
• Building discipline to handle wrongdoing and avoid the dangers of mishandling cases.
• Applying a five-step approach to fraud detection.
• Understanding what can go wrong and recognizing symptoms of wrongdoing.
• Correcting problems with the data import, identifying missing and hidden data.
• Keeping your data organized.

Detecting Fraud with IDEA

• Identifying patterns through statistical review, data sorting, and field summarizations.
• Effective and creative extractions for disbursements, employee reimbursements, liquid assets,
  revenues, and general ledger transactions.
• Employing editable fields to flag anomalies.
• Applying duplicate key detection/exclusion, and combining with field manipulation to detect
  circumvention of system controls. 
• Avoiding six common errors in data analysis.
• Stratifying data to detect approval circumvention, earnings management, and money laundering.
• Using special functions to carve out symptoms embedded within blocks of data.
• Employing join-matches and mismatches to detect fictitious vendors, revenue leaks, and false shipments.
• Extracting key-word symptoms of corruption and fraudulent financial reporting.
• Application of pivot tables, Benford's law, and trend analysis.

Putting It All Together

• Developing programs to detect theft and fraudulent reporting.
• Applying techniques to solve cases from allegation to presentation of evidence.
• Weaving techniques into a continuous monitoring program.
• Using principles of effective thinking and presentation to compile effective evidence.