Detecting Fraud Using IDEA

Massive data sets within the organization’s systems can hide symptoms of fraud and waste from auditors and control personnel.  This tactical session delves into specific methods for using IDEA data analysis software detect symptoms of problems across all company processes.  From the opening exercise, we will employ a team approach to solving cases, as in the field.  Within IDEA, attendees 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, shortcuts & organization tips, and more!

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.

You do not need an IDEA software license to attend this course; we will provide a fully functional demo copy of the software so you can work the case studies and learn the techniques.

Please scroll down to view the course outline, or click here to download the pdf outline.

Course Objectives

Upon completion of this workshop, you will understand how to:

Overcome mindsets that prevent us from properly addressing fraud;

Apply a consistent methodology for fraud detection;

Employ IDEA data analysis techniques used to successfully detect fraud;

Blend traditional methods of auditing with data analysis techniques;

Incorporate data analysis techniques into routine daily activities to improve detective controls;

Keep data organized and use editable fields to highlight 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 huge blocks of data;

Identify symptoms of theft and fraudulent reporting within common processes;

Apply lessons from case studies to your own unique environment.

16 CPE

Field of Study: Accounting, Auditing

Course Level: Intermediate


No prerequisites or advanced preparation required

Course Outline

Preparing to Detect Fraud

Overcoming beliefs that hinder our ability to achieve results;

How much fraud is out there;

Building discipline to handle wrongdoing and avoid the dangers of mishandling cases;

Applying a consistent approach to fraud detection;

Understanding what can go wrong and recognizing symptoms of wrongdoing;

Correcting problems with the data import, and 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, payroll, expense reimbursements/P-card, 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 pitfalls in data analysis;

Stratifying data to detect approval circumvention and earnings management;

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 sales;

Extracting key-word symptoms of corruption and fraudulent financial reporting;

Recognizing pay-to-play schemes and problems in the procurement bidding process;

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 strong evidence.