Course Description
PIA Consulting is registered with the Texas State Board of Public Accountancy as a CPE sponsor. This registration does
not constitute an endorsement by the board as to the quality of our CPE program. State boards of accountancy have final
authority on the acceptance of individual courses for CPE credit.
This course is offered as an open-enrollment class and as an on-site class.  For more information or to
register for this course, please email us at info@pia-consulting.com or phone us at (512) 343-2866.
Using ACL to Detect Fraud
Course Level:  Intermediate
CPE Credits:  8.0  (1 day)
Course Description:

Looking for a "hands-on" course that leads you through the specific commands, functions, and other features of
ACL to identify potential fraud, waste or errors in your data?  Tired of attending generic / "theory" courses that do
not provide you with actual examples of such testing using ACL?  Well look no further because this is the course
for you!

This 1-day intensive, “hands-on” training course will provide you with the know-how in using ACL to identify
potential fraud, waste, and errors in your data.  Not just theory but actual step-by-step procedures that you can
readily apply within your organization.

Course Objectives:

At the conclusion of this course, the participant will be able to:
  • Understand the role technology plays in the identification of fraud, waste, and errors.
  • Develop and execute ACL routines for testing the quality and integrity of data.
  • Understand the concept of data normalization and how to normalize data to obtain consistent data
    formatting using ACL.
  • Utilize specific ACL commands, command combinations, functions and other features to effectively analyze
    data and identify potential errors and indicators of fraud in the data.
  • Utilize ACL's new duplicates detection algorithm and perform "fuzzy logic" duplicates testing when
    necessary and appropriate.
  • Effectively utilize Benford's Law to identify abnormal occurrences of specific digits or digit combinations.

Course Balance:

  • Lecture / discussion:      50%
  • In-class applications:      20%
  • Section exercises:          30%

Course Prerequisites:

Participants should a good understanding of ACL basics, such as project creation, command use, creation of
computed fields, etc.  It is strongly recommended the participant have attended the "Introduction to ACL" training
(or similar) course.

Who Should Attend:

IS/IT Auditors, Fraud Examiners, Financial and Operational Auditors, Internal/External  Auditors, Analysts,
Accounting Professionals, Investigators, or anyone interested in learning how to use ACL to identify potential
fraud, waste, or errors in computer databases.

Other Information:

The participant will be provided with a comprehensive course manual containing presentation material and class
exercises.  The course manual also includes a listing of specific fraud detection tests that can be performed on
various business functions (i.e., accounts payable, accounts receivable, vendor management, etc.).

Course Outline:
Day 1

A.  Course Introduction and Overview
  • Definition of fraud, waste, and error.
  • Technology’s role in detecting fraud and error.

B.  General Statistics Related to Fraud, Waste and Error

C.  Verifying Data Quality and Integrity
  • Data Quality and Integrity defined.
  • Verifying data quality and integrity using ACL.

D.  Data Harmonizing / Data Normalization
  • Data normalization (DN) defined.
  • Why DN is critical to effective data analysis.
  • Why it's a bad idea to do this in Excel or Access.
  • ACL Functions & features useful for data normalization.

E.  Step-by-Step Procedures
  • Sorting on character and numeric fields to identify missing key data or unusual transactions.
  • Using ACL's Gap command to detect missing, cancelled, or suspended transactions.
  • Using ACL's improved Duplicates command algorithm to create "fuzzy logic" and other powerful duplicates testing.
  • Creating powerful ACL Search / Find routines to test for unusual descriptions and/or data.
  • Using field statistics to detect unusual account balances or transactions.
  • Using ACL functions to detect weekend and after-hours transactions.
  • Using numeric stratifications to identify possible circumvention of approval authority levels.
  • Other related tests.

F.  Other Testing Procedures
  • Purchasing
  • Accounts Payable
  • Accounts Receivable
  • General Ledger
  • Inventory
  • Payroll
  • Travel & Entertainment
  • Vendor Management
  • Procurement and Credit Card Transactions

G. Benford's Law / Digital Analysis
  • Benford’s Law defined.
  • Using the ACL Benford command.
  • Understanding the results.