The following presentation highlights a white-collar crime activity that has flourished within American neighborhoods since the late 1990s and early 2000s. The slide show not only provides a description of mortgage fraud, but also highlights some of the academic research findings by the author over the past five years.

1. MORTGAGE FRAUD: ITS LEGAL, POLITICAL,
COMMUNITY, AND CONSUMER IMPLICATIONS
Presented by: Andy Carswell, Ph.D.
University of Georgia HACE Department
JURIS 5540
September 12, 2013

2. QUESTIONS TO BE ADDRESSED
DURING TODAY’S PRESENTATION
 What exactly is (isn’t)
mortgage fraud?
 How pervasive is it?
 What are the consequences of
mortgage fraud?
 What are some of the warning
signs for mortgage fraud within
communities?
 Why has it taken so long for
mortgage fraud to become
newsworthy?
 How does mortgage fraud
change over time?
 What can be done about
mortgage fraud for the long-
term?

3. What exactly is mortgage fraud?

4. Mortgage Fraud Is…
1. A crime whereby property values are artificially
inflated in order to take significant funds out of the
property’s equity
2. A crime in which a party knowingly makes any
deliberate misstatement, misrepresentation, or
omission during the mortgage lending process.
3. A scheme to defraud banks and usually requires
collusion by:
 Buyer / Seller
 Real Estate Agent
 Real Estate Appraiser
 Mortgage Broker
 Real Estate Attorney
Source: Scott Smith

5. Mortgage Fraud Is NOT…
 “Flipping” properties for the sake of turning a profit after
improvements have been made
 A reference to non owner-occupied property used for
speculative purposes over time
 Predatory lending

6. Illustration of a Common Fraud Scheme
 Property flipper purchases house for $100,000.
 Obtains fraudulent appraisal for $400,000.
 Sells house for $400,000 and walks away with $300,000 profit.
 Home usually results in foreclosure.
 Bank takes a $300,000 loss. If FHA insured, government absorbs
loss.
Source: Sgt. Terry Joyner, ATL Police

7. Source: FBI

9. OK, so how bad is this
mortgage fraud problem?

10. SUSPICIOUS ACTIVITY REPORTS
Mortgage loan fraud reported on SARs:
 Falsification of loan application
 Identity theft
 Misrepresentation of Loan Purpose
 Misuse of Loan Proceeds
 Appraisal fraud
 Fraudulent flipping

11. Source: Lexis-Nexis

12. Source: Lexis-Nexis

14. Source: Lexis-Nexis

15. Mortgage Fraud in Georgia Declines in
2005
“The dramatic reduction in mortgage fraud in Georgia…is due to very
aggressive efforts by many parties, including this department, local,
state and federal law enforcement and prosecutors, lenders and
GREFPAC. It has been a coordinated effort, which is what it takes to
adequately address such a widespread problem.”
Department of Banking of Finance
Commissioner Rob Braswell
May 26, 2006

16. What are some of the consequences of
mortgage fraud?

17. Some Common Misperceptions
About Mortgage Fraud
 Banks are the only victims
 Surrounding communities should not be concerned
 This is a white-collar crime only
 This only happens in a few neighborhoods
Source: Scott Smith

18. Economic Consequences of
Mortgage Fraud
• Falsely escalated property
values
• Increases in property taxes
and home owner’s insurance
• Increases in foreclosures
• Neighborhood decline
Source: Sarah Gillespie

19. Falsely Escalated Property Values
• Comparative analysis
becomes difficult to
determine
• Buyers and sellers
assume market value
based on fraudulent sales
• Buyers purchase homes
overpriced for the current
sustainable market
• Sellers expect to sell
their homes at escalated
prices.
• Create affordability
issues within your
communities.
Source: Sarah Gillespie

20. Increases in Property Taxes,
Insurance and Bank Fees
• Tax assessors increase property
taxes based on artificial property
value increases
• Homeowner’s Insurance policies
increase due to artificial values and
fraudulent activity
•The cost of doing business at your
bank just increased considerably
Source: Sarah Gillespie

21. Increases in Foreclosure
• Criminals pull value out without
improving property
• Abandoned properties
• Properties foreclose and fall
below actual market values
(banks sell at a loss)
• Artificial values increase
property taxes forcing some
legitimate low-income owners
to foreclose
Source: Sarah Gillespie

22. Neighborhood Decline
• Instability, caused by high foreclosures, fractures community social fabric
• Ultimately lowers actual values, not just prices, for properties in community
• Legitimate homeowners risk getting no return for real improvements
• Homes are abandoned, vacant and boarded up attracting bad elements
• Crime increases and inevitably the value of property goes down
• Appeal of neighborhood decreases, and neighborhood could become
blighted
Source: Sarah Gillespie

23. MORTGAGE FRAUD AND ITS
RELATIONSHIP WITH HOUSE VALUES

24. Mortgage
Fraud
House
Neighborhood
Property Value
Surrounding City
Property Value
FRAUD
DETECTED!
True Market Value?
Fraud

25. Source: Carswell, A., Wade, M., Smith, S., & Huet, B. (2010). Techniques to enhance
the recognition of mortgage fraud in college classrooms and affected communities.
Journal of Forensic Studies in Accounting and Business, 2(1), 73-91.

26. Source: Carswell, A.T. (2009). Effects of mortgage fraud on property tax assessments.
Journal of Property Tax Assessment and Administration, 6(2), 5-17.
Mortgage Fraud Helps Push
Assessment Values Upward

27. Source: Carswell, A.T. (2009). Effects of mortgage fraud on property tax assessments.
Journal of Property Tax Assessment and Administration, 6(2), 5-17.
Mortgage Fraud Helps Push
Assessment Values Upward

28. WHAT ARE SOME OF THE WARNING
SIGNS OF MORTGAGE FRAUD?

29. Table 1: Concentration of Mortgage Fraud
Area
# of Census Tracts Analyzed
Total No Fraud Single Fraud Multiple Frauds
Ohio 1587 1508 24 55
Georgia (Atlanta
metro) 186 129 21 36
Missouri 573 504 7 62
CONCENTRATION OF MORTGAGE FRAUD
Source: Carswell, A., & Bachtel, D. (2009). Mortgage fraud: A risk factor analysis of affected communities.
Crime, Law, & Social Change, 52(4), 347-364.

30. MORTGAGE FRAUD INDICATORS – BY STATE
Unemployment
Rate
Poverty
Rate
Vacancy
Rate
Median
House
Price
Underserved
Status
Ohio
Fraud Census Tracts 8.35% 20.42% 10.89% $108,851 N/A
Non-Fraud Census
Tracts 6.59% 14.32% 7.69% $192,496 N/A
Georgia (Atlanta
metro)
Fraud Census Tracts 9.27% 16.31% 7.13% $189,349 25.64%
Non-Fraud Census
Tracts 11.74% 22.68% 8.89% $157,263 39.13%
Missouri
Fraud Census Tracts 9.49% 20.80% 53.46% $ 67,701 21.27%
Non-Fraud Census
Tracts 7.37% 12.82% 24.51% $105,249 4.03%
Source: Carswell, A., & Bachtel, D. (2009). Mortgage fraud: A risk factor analysis of affected communities.
Crime, Law, & Social Change, 52(4), 347-364.

31. INDICATORS BY SEVERITY OF MORTGAGE FRAUD
Census Tract
Underserved
Areas
Unemployment
Rate
Poverty
Rate
Vacancy
Rate
Median House
Price
No Fraud 49.63% 7.08% 14.47% 11.73% $115,920
Moderate Fraud
(1-8 occurrences) 70.21% 8.61% 19.18% 20.69% $112,618
Heavy Fraud
(over 8
occurrences) 65.63% 11.47% 20.85% 47.16% $100,944
Source: Carswell, A., & Bachtel, D. (2009). Mortgage fraud: A risk factor analysis of affected communities.
Crime, Law, & Social Change, 52(4), 347-364.

32. Source: Carswell, A., & Bachtel, D. (2009). Mortgage fraud: A risk factor analysis of affected communities.
Crime, Law, & Social Change, 52(4), 347-364.

33. Why am I just now learning
about mortgage fraud?

34. MEDIA COVERAGE OF MORTGAGE FRAUD
2000 2001 2002 2003 2004 2005 2006
Major Papers 25 33 25 29 42 66 100
Magazines and Journals 1 1 1 1 4 14 51
Policy Papers 0 0 0 0 0 0 0
Midwest Regional Sources 16 10 27 12 17 46 50
Northeast Regional Sources 9 18 15 15 12 24 35
Southeast Regional Sources 12 17 22 36 67 53 99
Western Regional Sources 7 14 22 21 48 29 48
North/South America News
Sources
6 17 17 19 32 75 93
Foreign News Sources 20 13 14 47 20 37 69
Business & Finance 33 29 38 41 96 181 242
Industry News 27 24 32 27 72 116 138
Totals 156 176 213 248 410 641 925
Source: Lexis-Nexis

35. Why am I just now learning
about mortgage fraud?
 Mortgage fraud has actually existed for a long
time.
 State of the housing economy
 Rise of Internet banking
 Increased use of 3rd
party brokers/lack of
regulation
 Popularity of real estate investor groups
 Concurrent with rise in identity theft
 Decline of neighborhood cohesiveness

36. How does mortgage fraud
change over time?

38. DIFFERENCES BETWEEN FORECLOSURE
RESCUE AND OTHER TYPES OF MORTGAGE
FRAUD
 Instead of occurring at the beginning of the loan transaction, this
occurs sometime within the duration of the mortgage period.
 Bank not really the victim here, it is the homeowner!
 There are varying punishments and legal remedies for this type of
fraud.

39. Source: Freddie Mac

40. REVERSE MORTGAGES AS AN
ATTRACTIVE TARGET FOR FRAUD

41. HOW DO REVERSE MORTGAGES
WORK EXACTLY?
 Traditional Refi
 Must be 62 or older
 Must claim the home as primary residence
 A portion of the home owner’s equity is made available to
homeowner based on:
- home’s value
- owner’s age
- prevailing interest rates
 Proceeds are available through either:
- lump sum payment
- annuity stream
- line of credit

42. POTENTIAL MARKET FOR
REVERSE MORTGAGES
 Nearly 7 million elderly households fit the profile of “house-rich,
cash-poor”  Rasmussen, Megbolugbe, & Morgan (1995)
 Just under 1 million low- to moderate-income would see a
significant increase to their financial well-being  Merrill, Finkel,
& Kutty (1994)
 Kutty (1998) estimated that RMs could effectively lower the
poverty rate by 2.4%

43. Source: Carswell, A., Seay, M.C., & Polanowski, M. (2013). Reverse mortgage fraud against seniors:
Recognition and education of a burgeoning problem. Journal of Housing for the Elderly, 27(1/2), 146-160.

44. MORE REASONS FOR GROWTH
IN REVERSE MORTGAGES
 Lack of retirement preparedness, as stated by EBRI’s
Retirement Confidence Survey
 Recent economic downturn exacerbated the problem
(VanDerhei, 2011)
 An increasing desire for older households to “age in place”
(Bayer & Harper, 2000)
 Astonishing rise in medical expenses (Skinner, 2007)

45. Source: Carswell, A., Seay, M.C., & Polanowski, M. (2013). Reverse mortgage fraud against seniors:
Recognition and education of a burgeoning problem. Journal of Housing for the Elderly, 27(1/2), 146-160.

46. ROLE OF HOUSING COUNSELORS IN
ADDRESSING FRAUD

47. TRADITIONALLY HECM HOUSING
COUNSELORS ARE EXPECTED TO:
 Serve as a “trusted gatekeeper” by closing the information
asymmetry gap between buyer and seller
 Be higher trained than other types of housing counselors
 Provide some follow-up with clients even after the HECM has
been transacted

48. OK, so what can be done
about mortgage fraud?

49. Warning Signs of Fraud
Unkempt lawn/yard
No sign of person
living there
People arriving at
location only at night
Houses selling
unusually quickly
Source: Derrick Duckworth, Jeannie Mills

50. Problem Resolution Requires
Communication and Action on a
Variety of Fronts
 Community/HOA’s
 Mayor/City Council
 Local Police Force
 Real Estate Industry Professionals
Source: Scott Smith

51. Some Inconsistencies with
Technological Tools
 Inconsistencies in ownership between title
commitment, appraisal and sales contract
 More than 5 mortgage inquiries reflected
on credit report within last 90 days
 Bank statement deposits do not coincide
with income/payroll deposits
 Seller is corporation
 Cross-outs on title commitments, sales
contracts, or other loan documents
 A small % of fraud transactions are
automatically flagged by technological
tools
 A large majority of some banks’ claims
include loans that “passed” technological
tool screening
 Over-reliance on technological tools costs
the industry billions of dollars in losses on
an annual basis

52. Know Some of the Targets for
Mortgage Fraud
 Out-of-Town Investors
 Young Women
 Military
 Older, More Mature Neighborhood
 Elderly Residents
 Elderly Investors
 Appraisers…yes, Appraisers!
 No HOA/Weak HOA
Source: Scott Smith

53. Places To Turn For Help In Mortgage
Fraud Situations
 GREFPAC
 Local law enforcement
 Housing/building code
inspectors
 Community Association
Institute
 Legitimate appraisers
 DO NOT hostilely confront
fraudsters!
Source: Scott Smith