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Data Analysis and Data Mining as a Fraud Investigation Tool

Course Description

Print-friendly Course Description and Outline

The ability to use data mining and computer assisted audit techniques (CAATs) is now considered by the audit profession as a core skill. The IIA’s Global Technology Audit Guide (GTAG) 13: Fraud Prevention and Detection in an Automated World declares, “Internal auditors require appropriate skills and should use available technological skills to help them maintain a successful fraud management program … all audit professionals — not just IT audit specialists — are expected to be increasingly proficient.” This course addresses these requirements.

In this course, we will discuss:
  • Myths and realities about using data analytics tools and techniques to detect fraud.
  • Benefits of using CAATs to detect and investigate fraud.
  • Critical ways CAATs can help to prevent fraud.
  • Key fraud detection capabilities of CAATs.
  • How to obtain management buy-in to implement CAATs for fraud detection, investigation, and prevention.
  • How to incorporate CAATs into the audit process and mistakes to avoid.​
Course Duration: 1 day(s)
CPE Hours Available: 8
Knowledge Level: Intermediate
Field of Study: Auditing

Participants should have knowledge or experience with basic accounting and audit concepts.​

Advance Preparation: 
Delivery Format: On-site Training (Group-Live)

​Audit Evidence​​

  • Why evidence is important
  • Different types of evidence
  • Methods to gather evidence
  • Best types of evidence
  • Determine and review audit evidence that is appropriate, sufficient, and persuasive to support audit conclusions — examples provided

The Fraud Problem

  • Defining the fraud problem
  • A statistical overview of the fraud problem
  • Who commits fraud
  • The Fraud Triangle (why employees commit fraud)
  • Lessons from “successful” fraudsters

New IIA and ISACA Fraud-detection Standards

  • The IIA’s GTAG 13: Fraud Prevention and Detection in an Automated World and GTAG 16: Data Analysis Technologies
  • ISACA’s whitepaper Data Analytics—A Practical Approach
  • AuditNet’s Data Analytics for Fraud Among Auditors survey results

Getting Started With Data Analytics/CAATs

  • Step 1: Conducting the fraud risk assessment
  • Step 2: Scoping the use of data analytics based on the fraud risk assessment results
  • Step 3: Identifying the data to be mined
  • Step 4: Acquiring the data
  • Step 5: Physically accessing and importing the data

Planning the Approach

  • Ad hoc testing
  • Repetitive testing
  • Continuous auditing
  • Continuous monitoring

“How-to” Demos

  • Detect duplicate payment fraud
  • Detect payroll (“ghost” employee) fraud
  • Detect P-card fraud

Other Data Analysis Tests that Can Be Performed to Discover Red Flags of Fraud

  • Using data analysis to investigate fraud
  • When to investigate and when not to investigate
  • Who should investigate
  • Data analysis techniques for investigating fraud when red flags have been detected
  • Keeping the fraud trail “untainted”

​Most courses can be delivered through on-site training. You might be surprised that the organization leading the profession is just as committed to the delivery of affordable training.​​

Contact us by calling +1-407-937-1388 or send an e-mail to​