Heinfeld, Meech & Co. State and Local Governmental Conference (Tempe, 1/28/2016)

1. A Look at Fraud
Presented by:
Karin M. Smith, MBA, SFO, CFE
Corey Arvizu, CPA
Heinfeld, Meech & Co., P.C.

2. The Fraud Triangle

3. How is Fraud Detected?
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
42%
16%
14%
11%
7%
3%
3% 2% 1% 1%

4. Who Commits Fraud?
19% -
Owners/
Executives
42% -
Employees
39%
Managers

5. City of Dixon
Small Midwestern city with 16,000 residents
Childhood home of Ronald Regan
General fund budget of $10 million
Audit and bookkeeping fees of $40,000
Small staff, part-time council, no City Manager

6. Rita Crundwell
Hometown resident
Began working at the city after high school in 1970
Named comptroller in 1983
Trusted employee and community member
Horse breeding employed a number of residents

7. The Fraud
• Opened a non-authorized bank account in the name
of the City in December 1990
• Prepared fictitious invoices for infrastructure
reimbursement to the State
• Wrote checks for payment on fictitious invoices
payable to “Treasurer”
• Deposited those checks into unauthorized account
• Went shopping for clothes, jewelry, cars,
motorhomes, property, horses, and unusual home
furnishings…

8. Rita Crundwell

9. The Lifestyle…

10. The Jewelry…

11. The Fraud
• Total fraud exceeded $54.0 million
• Fraud exceeded $5.6 million in 2008
• 179 fictitious invoices prepared
• Most all fictitious invoices in even amounts
• Fraud continued after initial identification
until her arrest

12. Auditor Responsibilities
The auditor obtains reasonable assurance about whether the
financial statements as a whole are free from material
misstatement, whether due to fraud or error.
To obtain reasonable assurance, which is a high but not
absolute, level of assurance, the auditor identifies and assesses
the risks of material misstatement, whether due to fraud or
error, based on an understanding of the entity and it
environment, including the entity’s internal control.
Due to the inherent limitations of an audit, an unavoidable risk
exists that some material misstatements of the financial
statements may not be detected, even though the audit is
properly planned and performed in accordance with GAAS

13. Responsibility for Prevention and
Detection of Fraud
The primary responsibility for the prevention and detection
of fraud rests with both those charged with governance of the entity
and management. It is important that management, with the oversight
of those charged with governance, places a strong emphasis
on fraud prevention, which may reduce opportunities for fraud to take
place, and fraud deterrence, which could persuade individuals not to
commit fraud because of the likelihood of detection and punishment.
This involves a commitment to creating a culture of honesty and
ethical behavior, which can be reinforced by active oversight by those
charged with governance. Oversight by those charged with governance
includes considering the potential for override of controls or other
inappropriate influence over the financial reporting process, such as
efforts by management to manage earnings in order to influence the
perceptions of financial statement users regarding the entity's
performance and profitability.

15. Types of Internal Controls
Preventative Detective

16. Terminology
Data mining
• Sorting through huge data sets using
sophisticated software to identify
undiscovered patterns and establish hidden
relationships
Data analytics
• Examining raw data with the purpose of
drawing conclusions about that information

17. Why Analyze Data?
Prevent
Fraud
Prevent
Misuse
Detect
Errors

18. Why Analyze Data?
• You go to the doctor for annual wellness exams
• You take your children to the dentist for periodic checkups
• You take your dog to the vet for preventative care shots
• You take your car to the mechanic for regular maintenance
Your financial data should receive
similar treatment…
It is the primary data for making
key management decisions!!!

19. Why Perform Data Analysis?
• Do you sign the year-end representation letter to the external
auditors?
• Key representations:
• Responsible for internal control environment
• No known significant deficiencies in the design of or
operation of internal controls
• Acknowledge responsibility for the design and
implementation of programs and controls to prevent and
detect fraud
• No known material instances of fraud
• Fiduciary responsibility as a member of the executive
management team

20. Data – The Possibilities
Data
Efficiency,
Effectiveness
&
Compliance
Fraud
Indicators
Grant
Programs
Purchasing
Cards Financial Vendors
Disbursements
Human
Resources
Payroll
Transparency
Operational
Attendance
Utility
Billings
Public
Works
Courts
Food
Service
Key
Performance
Indicators
Performance Customer
Service
Patterns &
Trends
Classroom
Spending
Time &
Effort
Revenue
Delinquent
Taxes vs.
Vendors
Utility
Billings
Property Tax
Exemptions
Sales Tax
Reports
Fund
Raising
Your
Imagination

21. Significant Assets of Organizations
People
Cash &
investments
Property,
plant &
equipment
Financial &
operational
data
Many others
Reputation
Many others
One of the most
underutilized assets

22. Traditional View of Data
Assets, Liabilities and Equity
Revenues versus Expenses
Budget versus Actual
Ratios, etc.

23. Transactional View of Data
Accounts
Payable
Accounts
Receivable
Bid Rigging
Cash
Disbursements
Conflict of
Interest
Credit Card
Management
Customer
Service
Management
Deposits
General Ledger Kickbacks Insurances Loans
Materials
Management
Inventory
Control
Policy and
Administration
Purchase Order
Management
Salaries and
Payroll
Travel Claims
Vendor
Management
Work In Process

24. Cross-Functional Views of Data
Operational
Vendors & Disbursements
Human Resources & Payroll
Vendors Compared to Human Resources
Eligibility – Federal and State programs
Delinquent Receivables / Assumed Names / Vendors
Data Analysis – Limited only to
electronic data and your imagination!

25. Surprise Audits
Effective, yet underutilized
Conducted by less than 30% of victim organizations
Lower fraud losses and detect frauds more quickly
Perception of detection
ACFE, 2012 Report to the Nation on
Occupational Fraud and Abuse

26. Accounts Payable Analysis
Duplicate payments
Rounded amounts
Just below thresholds
Abnormal volume
Cancelled checks

27. Accounts Payable Analysis
Above average payments
Payments issued to vendors without POs
Payments exceeding PO amounts
Transactions posted during off-work hours

28. ROW VND NAM INV NUM INV DATE INV AMT CHECK NUM PAY DATE PROCESS TIME APP PO AMT
1 ROBINSO 94225 12/13/2008 399.50 174709 10/25/2009 1:31 PM GH 400.00
2 SOUTHCO JT5941511 11/14/2009 4,999.99 174915 12/6/2009 2:33 PM GH 4,999.99
3 Q COAT JT6134612 12/20/2009 30.73 175144 2/13/2010 9:10 AM GH 35.00
4 ONETIME 11637 4/30/2010 5,093.38 175779 6/6/2010 1:32 AM SK 5,000.00
5 NEWMAN 4334 11/28/2009 1,086.88 175201 2/7/2010 12:32 PM GH 1,500.00
6 ONETIME 106040 6/11/2010 49.76 175957 7/11/2010 12:34 PM GH 45.00
7 ONETIME 185396 1/26/2010 1,398.25 175229 2/14/2010 4:01 PM GH 1,350.00
8 DESARIO 12126 6/8/2010 23.00 175896 7/4/2010 3:43 PM GH 25.00
9 FILTERS 69688 10/18/2009 175.00 174762 11/8/2009 1:33 PM GH 200.00
10 BOWIE 6573 10/10/2009 1,412.71 174649 10/17/2009 5:05 PM GH 1,500.00
11 ONETIME 37338 11/7/2009 296.10 174929 12/13/2009 5:45 PM GH 275.00
12 Q COAT JT61346-12 12/21/2009 30.73 175239 2/14/2010 2:35 PM GH 35.00
13 ONETIME 01104666I 4/23/2010 42.30 175680 5/16/2010 9:01 AM GH 45.00
14 HOUWATE 78763 11/20/2009 55,000.00 174950 12/25/2009 11:43 AM GH 55,000.00
15 ONETIME 0109-8635 1/10/2010 50.00 175174 1/31/2010 1:01 AM SK 45.00
16 WATKINS 8219 3/8/2010 525.81 175830 6/13/2010 7:43 AM GH 525.00
17 SOUTHCO JT5941622 11/16/2009 4,999.99 174932 12/10/2009 4:23 PM GH 4,999.99

29. Purchasing & Payables
Rounded Amounts
Use the Rounddown function to
separate the cents.
=F2 – ROUNDDOWN(F2,0)

30. Purchasing & Payables
Duplicate Payments
Use the IF function to look for
duplicates.
=IF(F2=F1,”DUP”,””)

31. Purchasing & Payables
Amounts below thresholds
Sort by the amount and look for costs
just under thresholds. ($1000, $5000,
$10000)

32. Purchasing & Payables
Abnormal volume
Use these options to roll up amounts
Look for a high volume of invoices and
dollar amounts

33. Purchasing & Payables
Employees as Vendors
Payments without a PO
Separation of Duties
User Roles

34. Payroll Analysis
Gross equal net pay
Ghost employees
Off-cycle payments
Payments to terminated employees
False or duplicate employee identification numbers
High overtime
Duplicate employee addresses

35. Payroll Analysis
New position codes added
Analysis of employees and/or total pay by position, position type,
location, funding source, number of checks issued
Anomalies in recalculation of total pay, hours, overtime, pay/hours
per funding source
Analysis of total supplemental/bonus pay
Variances compared to 941s
Compensated leave anomalies including negative balances, large positive
balances

36. ROW
EMP
NUM GROSS PAY PAY DATE NET PAY SS HIRE DATE TERM DATE
DD BANK ACCT
NUM
1 1123 2,250.00 5/15/2009 1,346.17 579627851 8/20/1973 23896
2 1156 2,060.00 11/15/2009 1,335.91 396152031 9/13/2008 12/24/2009 89000567
3 1178 1,800.01 11/30/2009 1,800.01 123456789 3/4/1980 65324
4 1198 2,370.00 11/15/2009 1,716.47 543945471 3/16/1994 7832112
5 2134 2,370.94 5/15/2009 1,592.08 417337241 11/12/2008 455599021
6 2346 288.75 8/31/2009 126.33 308801411 5/15/2008 78345
7 2389 1,725.00 8/15/2009 1,118.67 294624211 6/30/2008 12/1/2008 9998001326
8 2399 7,754.00 8/15/2009 5,251.79 256024861 6/15/2009 78231
9 1101 4,647.00 2/15/2010 2,668.53 142422251 1/19/2009 90433389
10 1109 2,657.00 11/15/2009 1,563.65 605843191 12/15/2009 51938215
11 2369 1,000.00 8/15/2009 65.01 634999999 4/5/1992 1/14/2010 89000567
12 1178 2,250.00 11/30/2009 1,459.14 341549121 3/4/2008 21903198
13 2478 2,550.00 5/15/2009 1,640.92 303764511 9/14/1991 89100026
14 1103 2,095.76 5/15/2009 1,231.26 626829921 9/8/2008 9875
15 2198 3,093.00 11/15/2009 2,291.15 243454611 8/3/1995 2999843

37. Payroll
High Overtime
Look for excessive overtime costs.

38. Payroll
Off-Cycle Payments

39. Payroll
Off-Cycle Payments

40. Payroll
Duplicate Employee Addresses

41. Payroll
Pay Date after Term Date

42. Payroll
Direct Deposits
Flag duplicates
=IF(A1=A2,”DUP”,””)

43. Vendor Payments with
Employee Addresses
Employee Name Vendor Name
CALENDAR
YTD
MAILING
ADDRESS CITY STATE
ZIP
CODE
Bouvier, Selma Bouvier, Patty $ 362.00 P.O. BOX 1295 Springfield KY 40069
Simpson, Homer Jay Simpson, Homer J. $ 59.00 PO BOX 1413 Springfield KY 40069
Simpson, Marge Simpson, Homer J. $ 59.00 PO BOX 1413 Springfield KY 40069
Flanders, Ned The Leftorium $ 2,493.13 PO BOX 1424 Springfield KY 40069
Sisters living in the
same apartment and
Patty is being
reimbursed for an
expense.
This is the same person,
but the name was just
spelled slightly different
in the vendor listing.
Data analysis can identify both legitimate situations as well as
scenarios that may require further management analysis and inquiry.
The husband and wife
are employed at the
same entity, so the
addresses match.
The vendor name is a
company. This could
indicate a ghost vendor
or a valid vendor with a
possible conflict of
interest.

44. Other Analysis
General ledger
Receivables
Capital assets
Cross module

45. QUESTIONS

46. Karin M. Smith, SFO, MBA, CFE
602-277-9449 ext. 327
karins@heinfeldmeech.com
Corey Arvizu, CPA
520-742-2611 ext. 101
carvizu@heinfeldmeech.com