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 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 (ver 9.3) Duplicates command algorithm to create "fuzzy logic" and other powerful duplicates
- 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 Generic Testing Procedures
- Accounts Payable
- Accounts Receivable
- General Ledger
- 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.