Internal Audit Training, IT Audit Training Courses, Information Security Training - CPE Interactive

Continuing Professional Education for Audit, Assurance, & Info Security

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Course Description

Data mining and computer assisted audit techniques (CAATS) are now considered by the audit profession as a core skill. The IIA in their Global Technology Audit Guide #13: Fraud Detection and Prevention in an Automated World, declare “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 seminar addresses these requirements.

In this seminar, we will discuss the critical issues to be considered:

  • Myths and realities about using data analytics tools and techniques to detect fraud
  • Benefits of using Computer-Assisted Audit Techniques (CAATs) to detect and investigate fraud
  • Critical ways CAATs helps 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 implement CAATs into the audit process and mistakes to avoid

Learning Objectives

  • Understand the necessity for adopting data analysis and CAATs into the fraud-detection/audit process
  • Understand the leading data analytic software applications available on the market and decide which is best for your organization
  • Determine training needs for incorporating CAATs into your fraud-audit process
  • Determine who in your organization is best qualified to spearhead CAATs implementation for fraud detection/investigation/prevention

Course Outline

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

  • IIA GTAG #13 and GTAG #16
  • ISACA “Data Analytics: A Practical Approach”
  • AuditNet Survey results on Data Analytics for Fraud Among Auditors

Getting Started with Data Analytics/CAATs

  • Step 1: Conducting the Fraud Risk Assessment
    • Identifying the fraud universe
    • Using red flags to identify fraud risk
  • Step 2: Scoping the use of data analytics based on the Fraud Risk Assessment results
    • Inventory fraud
    • Payroll fraud
    • Vendor fraud
    • Financial statement fraud
  • Step 3: Identifying the Data to be Mined
    • Identify investigation objectives
    • Feasibility assessment on how to get the data
    • Involving data custodians and/or owners Define the required data parameters
    • Identify the data fields/files needed
  • Step 4: Acquiring the data
    • Obstacles
    • Working with IT to obtain and “clean” the data
  • Step 5: Physically accessing and importing the data
    • Risks of using data originals or copies
    • Where to import the data
    • Avoid corrupting 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; when not
  • Who should investigate
  • Data analysis techniques for investigating fraud when red flags have been detected
  • Keeping the fraud trail “untainted”

Additional Information

Who Should Attend
  • Internal and external auditors
  • Internal control professionals
Learning Level

Intermediate

Delivery

Group-Live & Group Internet-Based

Field

Auditing

Advanced Preparation

None

Recommended Prerequisites

Basic accounting and audit concepts.

Session Duration

Online: 2 three hour sessions

On Site: 1 day

CPE Credits: 8