principles of fraud examination - acfe
TRANSCRIPT
© 2018 Association of Certified Fraud Examiners, Inc.
Principles of Fraud
Examination
Analyzing and Managing Financial Information
© 2018 Association of Certified Fraud Examiners, Inc. 2 of 27 CPE PIN: POFE816
Practical Problem
Questions:
1. Name one or two of the existing software
packages that you think are best for analyzing
data to detect fraud.
© 2018 Association of Certified Fraud Examiners, Inc. 3 of 27 CPE PIN: POFE816
Practical Problem
Questions:
2. What minimum analysis would you
recommend for the following fraud schemes?
a. Accounts payable; fictitious vendors
b. Journal entries
c. Fictitious revenues
© 2018 Association of Certified Fraud Examiners, Inc. 4 of 27 CPE PIN: POFE816
Analyzing and Managing Financial Data
▪ The data tells the story:
• Timelines
• Relationships
• Patterns
• Amount of losses
• Omissions and manipulations
© 2018 Association of Certified Fraud Examiners, Inc. 5 of 27 CPE PIN: POFE816
Data Analysis Applications—General
▪ Accuracy: check totals and calculations
▪ Analytical review: comparisons, profiling, etc.
▪ Validity: duplicates, exception
▪ Completeness: gaps, matches, totals
▪ Cut-off: date and number sequences analysis
▪ Statistical sampling: selection
▪ Summarization and ranking: customers, products, regions
▪ Performance measures: response times for order processing
© 2018 Association of Certified Fraud Examiners, Inc. 6 of 27 CPE PIN: POFE816
Data Analysis Applications—Fraud
▪ Questionable invoices:
• Multiple invoices with same amounts or
descriptions
• Duplicate invoices or invoices in sequence
▪ Duplicate payments
▪ Vendor schemes:
• Vendors matching employees
• Vendors with one or more address or vendor code
• New vendors with high activity
© 2018 Association of Certified Fraud Examiners, Inc. 7 of 27 CPE PIN: POFE816
Data Analysis Applications—Fraud
▪ Kickbacks and conflicts of interest:
• Vendor prices higher than standard
• Check for continued purchases despite high rates
of returns, rejects, credits, etc.
▪ Financial statement fraud:
• Ratio, vertical, and horizontal analysis
© 2018 Association of Certified Fraud Examiners, Inc. 8 of 27 CPE PIN: POFE816
Understanding Accounting Software
▪ Tables:
• Customers
• Vendors
• Employees
• Inventory
▪ Transaction files:
• Disbursements
• Sales detail
• General ledger
▪ Reports
▪ Audit trail
© 2018 Association of Certified Fraud Examiners, Inc. 9 of 27 CPE PIN: POFE816
Identifying Necessary Documents and Data
▪ Internal data:
• MS Office files (Excel, Word, etc.):
• Server
• PC
• Network or software log-in data
• Other pertinent documents:
• Contracts
• Deposit slip books
• Invoices (both A/P and A/R); shipping documents, etc.
© 2018 Association of Certified Fraud Examiners, Inc. 10 of 27 CPE PIN: POFE816
Identifying Necessary Documents and Data
▪ External data:
• Bank statements and canceled checks
• External travel and entertainment histories
• Payroll service reports
• Public document searches:
• Secretary of state
• County treasurer
• Background checks
• Social media searches
© 2018 Association of Certified Fraud Examiners, Inc. 11 of 27 CPE PIN: POFE816
Data Analytics Software
▪ Data analysis software
can take the total
population of data,
analyze it, and identify
anomalies.
▪ Fraud examiners do
not have to be
programmers to use
the software.
© 2018 Association of Certified Fraud Examiners, Inc. 12 of 27 CPE PIN: POFE816
Data Analytics Software
▪ Common applications
used to analyze data:
• ACL
• IDEA for Windows
• Spreadsheets
© 2018 Association of Certified Fraud Examiners, Inc. 13 of 27 CPE PIN: POFE816
Data Extraction Realities
▪ Time consuming
▪ Difficult to retrieve “clean” data
▪ Difficult to retrieve accurate data
▪ Cooperation of client and client’s IT
personnel
© 2018 Association of Certified Fraud Examiners, Inc. 14 of 27 CPE PIN: POFE816
Preparing Data for Analysis
▪ Preparing the data:
• Standardized
• Accurate
▪ Common errors and issues:
• Recurring headers or footers
• Text versus numbers
• Date formats
▪ Keep initial file unaltered
▪ Track changes to initial file
© 2018 Association of Certified Fraud Examiners, Inc. 15 of 27 CPE PIN: POFE816
Examples of Data Analysis
Techniques—Purchasing
Function Detection
Dates of bids• Unauthorized information release—same vendor
always bids last
Bidding patterns • Favorable treatment to select vendors
Favored-vendor
status
• Fictitious vendors, duplicate payments, or favorable
treatment
New vendor hiring
patterns• Fictitious vendors or conflicts of interest
Vendor addresses • Fictitious vendors or conflicts of interest
Override transactions • Fictitious vendors or duplicate payments
Overbilling • Unusual, or one-time extra charges
Conflict of interest
• Vendors with employees who are related to the client
• An unusually high occurrence rate of complaints
• Compliments about specific vendors
• Higher prices and/or substandard quality
© 2018 Association of Certified Fraud Examiners, Inc. 16 of 27 CPE PIN: POFE816
Examples of Data Analysis
Techniques—Accounts Receivable
Function Detection
Age and filter receivables • Identify postings to dormant accounts.
Export data• Prepare confirmation letters to
customers.
Sequence data
• Review the logical range (pre-numbered,
chronology, etc.) of credits, invoices, and
payments.
Age data• Review credits beyond discount terms
(amounts or dates).
© 2018 Association of Certified Fraud Examiners, Inc. 17 of 27 CPE PIN: POFE816
Examples of Data Analysis
Techniques—Inventory
Function Detection
Summarize and extract
data
• Compare physical count with computed
count.
Classify or subtotal • Calculate returns and shortages by vendor.
Filter, summarize, and
sample data
• Identify high-value items purchased by
internal buyers.
Extract data • Review pricing on comparable products.
Filter and classify data• Determine inventory sent to scrap by
employee.
© 2018 Association of Certified Fraud Examiners, Inc. 18 of 27 CPE PIN: POFE816
Examples of Data Analysis Techniques—
Disbursements and Accounts Payable
Function Detection
Filter• Summarize large invoices without
purchase orders by vendor.
Join• Identify vendor unit price variances by
product over time.
Extract data • Review pricing on comparable products.
Join• Reconcile check register to
disbursements by vendor invoice.
Join• Compare monthly expenses to
posted/paid expenses.
© 2018 Association of Certified Fraud Examiners, Inc. 19 of 27 CPE PIN: POFE816
Examples of Data Analysis
Techniques—Payroll
Function Detection
Sample• Review overtime, pay, bonuses,
commissions.
Duplicates
• Identify duplicate direct deposit numbers.
• Identify duplicate employee names, phone
numbers, etc.
Age• Compare employee start and termination
date with pay dates.
Filter • Identify payroll with no deductions.
© 2018 Association of Certified Fraud Examiners, Inc. 20 of 27 CPE PIN: POFE816
Benford’s Law
▪ First digits in a sequence of numbers do not
fall equally
▪ Applies to natural occurring numbers
▪ Well suited to detect anomalies
▪ Applications:
• Payments
• Authorization levels
• Excessive rounding:
• Analyze the last two digits of the numbers.
© 2018 Association of Certified Fraud Examiners, Inc. 21 of 27 CPE PIN: POFE816
Benford’s Law
© 2018 Association of Certified Fraud Examiners, Inc. 22 of 27 CPE PIN: POFE816
Using Financial Analysis to
Detect Illicit Income
▪ Two basic methods:
• Net-worth or asset
method
• Expenditures method
© 2018 Association of Certified Fraud Examiners, Inc. 23 of 27 CPE PIN: POFE816
Net Worth—Asset Method
Year 1 Year 2
Assets $234,320 $280,150
– Liabilities 132,000 115,800
= Net Worth $102,320 $164,350
– Prior Year’s Net Worth 5,905 102,320
= Increase in Net Worth $96,415 $62,030
+ Known Expenses 16,250 29,450
= Total Net-Worth Increase $112,665 $91,480
– Funds from Known Sources 39,685 41,455
= Funds from Unknown Sources $72,980 $50,025
© 2018 Association of Certified Fraud Examiners, Inc. 24 of 27 CPE PIN: POFE816
Rules of Net-Worth Analysis
▪ All assets should be valued at cost.
▪ Estimate the amount of funds available
generously.
▪ Conservatively estimate the amount of living
expenses.
© 2018 Association of Certified Fraud Examiners, Inc. 25 of 27 CPE PIN: POFE816
Expenditures Method
Year 1 Year 2
Known Expenditures $117,865 $91,480
– Known Source of Funds 44,885 41,455
= Funds from Unknown Sources $72,980 $50,025
© 2018 Association of Certified Fraud Examiners, Inc. 26 of 27 CPE PIN: POFE816
Software Used in Organizing
and Presenting Cases
▪ i2-Analyst Notebook:
• Link analysis
• Network analysis
• Timeline analysis
• Transaction pattern
• Database visualization
▪ CaseMap
▪ Spreadsheets and database software