Fair Lending laws have been around for decades, but more robust Fair Lending analysis has recently become a hot-button issue and point of emphasis with regulators. Financial institutions must now be able mathematically prove no discrimination or "disparate impact/treatment" is occurring in marketing activities, during the loan application process, with pricing and add-on products, and with charge-off and collection practices.

1. Fair Lending Analysis Made Easy
Presented by: Ian Dunn
CEO,

2. Agenda
The Basics
Assessing Your Potential Fair Lending Risk Exposure
1
2
3 Key Fair Lending Analysis & Reporting

3. The Basics- Fair Lending Laws and Prohibited Basis Groups
Fair Housing Act (FH Act)
Prohibits discrimination in residential real estate transactions:
-making loans to buy, build, repair, improve a dwelling
-purchasing real estate loans
-selling, brokering, or appraising residential real estate
-selling or renting a dwelling
Equal Credit Opportunity Act (ECOA)
Prohibits discrimination in any aspect of a credit
transaction
Reg B, HMDA, and CRA

4. Then Basics-Fair Lending Laws and Prohibited Basis Groups
Race/Color
Religion
Gender
Age
Marital Status
Source of Income
National Origin
Handicap
Familial Status
 FH Act  ECOA  Both

5. The Basics- Types of Discrimination
Disparate Treatment
>Overt-Lender openly discriminates on a prohibited basis (can be written or verbal)
>Comparative Evidence-Differences in treatment not fully explained by legitimate non-discriminatory factors
*A disparate treatment claim does not require evidence the lender intended to discriminate or was motivated by prejudice.
Disparate Impact (“Effects Test”)
>When an otherwise neutral policy or practice has a disproportionately negative impact on persons from a
prohibited basis group.
*A disparate impact claim must show the challenged policy or practice is either:
1) not justified by a valid business propose or
2) that the business justification could be accomplished using a less discriminatory alternative.

6. The Basics- Prohibited Practices
Fail to provide or provide different information or services regarding any aspect of the lending process
Discourage or selectively encourage individuals who inquire or apply for credit
Refuse to extend credit or use different standards in determining whether to extend credit
Vary the terms of credit offered
Use different standards to evaluate collateral
Treat a borrower differently in servicing a loan or making invoking default remedies
Use different standards for pooling or packaging loans in the secondary market
1
2
3
4
5
6
7
Applies to: Applicants Associations Occupants Neighborhood

7. The Basics- Fair Lending touches every part of Lending Process
Pre-Application Activities
-Advertising & Market Selection
-Channels
-Responding to Inquiries
Application Activities
-Level of Assistance
-Use of 3rd Parties
-Initial Terms & Conditions
Underwriting/Closing
-Approval Criteria
-Final Terms & Conditions
-Appraisal Practices
Servicing/Post-Closing
-Modifications
-Default Remedies
-REO

8. The Basics-Example 1
-For joint applicants, combine the debts and income of married joint applicants to calculate debt-to-
income ratio and for unmarried joint applicants calculate an individual debt-to-income ratio for
each applicant.
Discrimination?
-Yes!
Prohibited Basis:
-Marital Status
Discrimination Type:
-Disparate Treatment: Overt
Prohibited Practice:
-Refuse to extend credit or use different standards (married vs. unmarried) in determining
whether to extend credit

9. The Basics-Example 2
Borrower National Origin Number of Home Purchase Loans Average Interest Rate
Non Hispanic White 150 8.5%
Discrimination?
-Potentially
Prohibited Basis:
-National Origin
Hispanic 125 12.5%
Discrimination Type:
-Disparate Treatment: Comparative Evidence
Prohibited Practice:
-Vary the terms of credit offered

10. The Basics-Example 3
The financial institution has a policy not to make home loans less than $100,000.
Discrimination?
-Potentially
Prohibited Basis:
-Race, Familial or Marital Status
Discrimination Type:
-Disparate Impact
Prohibited Practice:
-Fail to provide services, discourage applications
Notes:
-Does this policy effectively exclude certain low income and/or
minority majority areas?
-Does the $100k min. policy have a legitimate business need?
Can that need be satisfied in a less discriminatory manner?

11. The Basics-Example 4
Discrimination?
-Potentially
Prohibited Basis:
-Race, Familial or Marital Status
Discrimination Type:
-Disparate Impact
Prohibited Practice:
-Fail to provide services, discourage applications
Notes:
-With few exceptions, there are no compliance
requirements to advertise in a foreign language
-Are all triggers/key terms/disclosures also in the
foreign language?

12. Agenda
The Basics
Assessing Your Potential Fair Lending Risk Exposure
1
2
3 Key Fair Lending Analysis & Reporting

13. Assessing Your Potential Fair Lending Risk Exposure
Marketing
Activities
Discretion
Permitted
Exception
Handling
Use of
Third Parties
How and where you offer
credit products are not
just fundamental
business decisions, they
have fair lending
implications as well.
The level of individual
discretion permitted in
certain activities such
as approvals or pricing
increases an
institution’s fair lending
risk.
Exceptions should be
made consistently for
similar reasons for
similarly situated
applicants or borrowers.
From a fair lending
perspective TPOs are the
financial institution and if
any TPO does not comply
with fair lending regulations
the financial institution may
be as culpable as if you
were the initial creditor.
Incentives &
Compensation
Compensation tied to
loan production can be
a great motivator for a
tough job, but it can
also lead to significant
fair lending issues.

14. Marketing Activities
Redlining
The illegal practice of refusing to make loans or
imposing more onerous terms on borrowers
because of the racial, national origin, or other
prohibited basis characteristics of the residents
of a subject neighborhood.
Reverse Redlining
Reverse redlining is the deliberate targeting of
residents of such neighborhoods with less
advantageous or potentially predatory products.
Figure 1. Home Owner’s Loan Corporation, Philadelphia, PA., 1936
Evans Bank (NY): https://www.youtube.com/watch?v=nZix2Joay-0
The Department of Justice (DOJ) recently settled two redlining cases: one against Citizens Bank of
Flint, Michigan and one against Midwest BankCentre of St. Louis County, Missouri.

15. Marketing Activities
Steering
The guiding of an applicant or a borrower to a
less advantageous product on a prohibited basis
rather than on the legitimate needs.
(Steering in Real Estate refers to guiding a
prospective purchaser towards or away from
certain neighborhoods based on race.)

16. Marketing Activities
Advertising/Pre-screening
Advertising methods that could discourage
individuals from applying for loans or in media
that exclude specific regions are sources of fair
lending risk.

17. 1 (Low) 2 3 4 5 (High)
Market Demographics:
Stable, Low Competition, Low Diversity Evolving, High Competition, High Diversity
Delivery Channels:
Limited, Processes don’t vary, No Subprime Subsidiaries/Affiliates
Multiple, Processes vary, Subprime
Subsidiaries/Affiliates
Product Complexity:
Traditional Mix
New Products Reviewed for Fair Lending Compliance
Complex and Non-traditional Mix
New Products Not Reviewed
Advertising:
Limited, No Recent Changes, Broad Based Extensive, Constantly Changing, Targeted
Score:
Marketing Activities (Score 1 to 5)

18. Discretion Permitted
SunTrust Mortgage Inc. has agreed
to pay $21 million Settlement
The lawsuit alleges that SunTrust's policies promoted racial discrimination by giving
loan officers and mortgage brokers significant discretion to vary a loan's interest rate
and other fees from the prices the company set based on a borrower's
creditworthiness.
In 2009, new SunTrust Mortgage policies reduced the discretion of loan officers and
mortgage brokers to alter prices. The company also now requires variations in prices
to be documented and reviewed by a supervisor.

19. Discretion Permitted (Score from 1 to 5)
How much discretion is permitted? Does the degree of permitted discretion vary by geography,
channel, or activity? Can the exercise of discretion impact compensation?
1 (Low) 2 3 4 5 (High)
Limited and Consistent Discretion Broad and Variable Discretion
Discretion Criteria is Clear Discretion Criteria is Broad or Non-existent
Discretion Does Not Impact Compensation Discretion Does Impact Compensation
Score:

20. Exception Handling

21. Is file documentation accurate and descriptive? Is rationale objective? Are exceptions low in
number? Do certain loan officers, branches, etc. have a higher level of granting exceptions?
1 (Low) 2 3 4 5 (High)
Exceptions are Objective and Well Documented Exceptions are Subjective and Not Well Documented
Exceptions are Few in Number Exceptions are Many
Score:
Exception Handling (Score from 1 to 5)

22. Consumer
Dealer
Lender(s)
Lender
Consumer Dealer
Dealer
1. Consumer submits application to Dealer
2. Dealer submits application
to Lender(s)
3. Lender(s) submit “buy rate”
and dealer compensation to
dealer
4. Dealer sets actual rate to consumer
Use of
Third
Parties
5. Consumer and Dealer
close the sale
Lender(s) Lender(s)
6. Dealer sales the contract
to the chosen Lender
Q: Where is a major source of
Fair Lending Risk in this process?

23. Do you use Third Party Operators (TPOs)? Is due diligence performed? Do you have written
agreements addressing fair lending obligations? Do agreements define who is responsible and
accountable? Do you receive regular reporting? Does the TPO have frequent complaints? Does the
TPO conduct fair lending training?
1 (Low) 2 3 4 5 (High)
Little or No Use of Third Parties Extensive Use of Third Parties
Due Diligence Performed No Due Diligence Performed
Written Agreements/Accountability Defined No Written Agreements/Accountability Not Defined
Receive Regular Reporting Receive No Reporting
Regular Fair Lending Training No Fair Lending Training
Score:
Use of Third Parties (Score from 1 to 5)

24. Incentives & Compensation
https://www.youtube.com/watch?v=t-W_ilJqt4A
Bank of America $335 Million
Settlement
“Compensation structure was such
that a (loan officer) would make more
money if they put people into a poor
quality, higher priced loans.”
Lisa Madigan, Attorney General,
Illinois

25. Incentives & Compensation (Score from 1 to 5)
Are your loan officer and other decision makers compensated on loan production? Is compensation
tied to higher pricing or higher fees?
1 (Low) 2 3 4 5 (High)
Incentives & Compensation Not Tied to Loan
Production
Incentives & Compensation Tied to Loan Production
Score:
Incentives & Compensation Not Tied to Loan Pricing
and/or Fees
Incentives & Compensation Tied to Loan Pricing and/or
Fees

26. Assessing Your Potential Fair Lending Risk Exposure
Source Score
-Marketing Activities (1-5)
Discretion Permitted (1-5)
Exception Handling (1-5)
Use of Third Parties (1-5)
Incentives & Compensation (1-5)
TOTAL SCORE (5-25)
RISK LEVEL (Low to High)
Low Medium-Low Medium Medium-High High
<=7 8-12 13-16 17-21 >=22
What is your total score and risk level?
Risk Level (Based on Total Score):

27. Discretion Permitted
Incentives & Compensation
Discrepancies by Prohibited Basis Groups
=
HIGH RISK!!!
Does statistical analysis show
higher rates/fees being charged to
minorities or other prohibited
basis groups?
Is compensation tied to
higher priced loans?
Can loan officers or
other decision makers
set rates and fees?

28. Agenda
The Basics
Assessing Your Potential Fair Lending Risk Exposure
Key Fair Lending Analysis & Reporting
1
2
3

29. Self Evaluation vs. Self Test
A self evaluation or a self test may provide for a streamlined exam.
Self Evaluation Self Test
Essentially any fair lending
analysis of loan and
application data that is
not a “self test”.
Examples:
-Comparative File Reviews
-Statistical Audit/Reports
Any voluntary program,
practice, or study that is
designed and specifically
used to assess an
institution’s compliance with
fair lending laws and creates
data not available or
derived from loan,
application, or other records
related to a credit
transaction.
Examples
-Paired Testing
-Surveys
“Likely” violations require “Appropriate
Corrective Action”
Appropriate Self-Testing can create legal
privilege.
Consult your legal counsel!

30. Fair Lending Basic Building Blocks
2
1
3
4
Applicant/Borrower data such credit score, DTI, PTI, length of employment, length at
residence, etc. Also, race, gender, and age of borrower as appropriate.
Application/Loan data such as channel used, decision makers involved , status, rate, term,
amounts, etc.
Collateral information such as type and original value.
Demographics of the Census Tract where each applicant/borrower resides.
Demographics of your Institution’s “Lending Area”.
5

31. Fair Lending Advanced Building Blocks
1 Expected Race
Estimating Expected Race (Bayesian Improved Surname Geocoding-BISG):
Step 1. Match Borrower Address to Census Tract
Step 2. Calculate Baseline Expected Race/Ethnicity Using Census Data
Step 3. Match Borrower Surname to Name/Race Database
Step 4. Apply Bayesian Statistics to Update Baseline Expected Race
P(Ethnicity|Given Surname) = P(Given Surname|Ethnicity)*P(Ethnicity)
P(Given Surname|Ethnicity)*P(Ethnicity) + P(Given Surname|Not Ethnicity)*P(Not Ethnicity)

32. Fair Lending Advanced Building Blocks
Expected Interest Rate
2
Estimating Expected Interest Rate (Multiple Regression Analysis):
1. Sample Construction
Similar loan types, similar origination periods, large sample size
2. Regression Estimation
Independent Variables: Credit Score, Reference Rate, Loan-to-Value, Etc.
Estimate Variable Coefficients
3. Apply Resulting Coefficients to each loan to estimate Expected Interest Rate

33. An Example

34. The 4 Key Fair Lending Ratios & Reports
2.14
(Hispanic)
% of PBG in Lending Area /
% of PBG in Portfolio
1.93
(HELOC-Subprime)
% of PBG in Product /
% of Portfolio
% of PBG Denied /
Expected % of Denied
Avg. Rate of PBG /
Expected Rate of PBG
Redlining Ratio Steering Ratio
Expected Denial
Ratio
Expected
Pricing Ratio
2.78
(Female)
*PBG is a Prohibited Basis Group such as Race, Gender, Age, Etc.
1.22
(Black)

35. Redlining Ratio
2.14
(Hispanic)
% of PBG in Lending Area /
% of PBG in Portfolio
Percent of
Applications
(or Loans)
*PBG is a Prohibited Basis Group such as Race, Gender, Age, Etc.
Percent of Lending
Area Redlining Ratio
Asian/Pacific
Islander
3.0% 2.5% 0.83
Black 7.0% 7.5% 1.07
Hispanic 14.0% 30.0% 2.14
Native American 1.0% 1.0% 1.00
White 70.0% 55.0% 0.79
Other/Not
Reported
5.0% 4.0% 0.80

36. Steering Ratio
1.93
(HELOC-Subprime)
% of PBG in Product /
% of PBG in Portfolio
Asian/Pacific
Islander Black Hispanic
*PBG is a Prohibited Basis Group such as Race, Gender, Age, Etc.
Native
American White Other
First Mortgage 2.0% 7.5% 8.0% N/A 80.5% 2.0%
Second Mortgage 1.2% 3.4% 12.2% N/A 82.2% 1.0%
HELOC (Prime) 1.4% 4.5% 5.5% N/A 87.1% 1.5%
HELOC (Sub Prime) 1.6% 14.2% 10.6% N/A 72.4% 1.3%
Other 1.7% 0.5% 2.5% N/A 93.6% 1.7%
Total 2.0% 7.4% 7.9% N/A 81.3% 1.8%
Asian/Pacific
Islander Black Hispanic
Native
American White Other
First Mortgage 1.00 1.02 1.01 N/A 0.99 1.10
Second Mortgage 0.59 0.46 1.54 N/A 1.01 0.55
HELOC (Prime) 0.69 0.61 0.69 N/A 1.07 0.83
HELOC (Sub Prime) 0.78 1.93 1.34 N/A 0.89 0.69
Other 0.83 0.07 0.32 N/A 1.15 0.94

37. Expected
Denial Ratio Gender
% of PBG Denied /
Expected % PBG Denied
All
Application
Count
*PBG is a Prohibited Basis Group such as Race, Gender, Age, Etc.
Denied
Application
Count
% Denied
Expected
% Denied
Expected
Denial Ratio
Male 400 10 2.5% 2.7% 0.93
Female 200 50 25.0% 9.0% 2.78
Joint 300 30 10.0% 9.0% 1.1
Unknown 50 0 0% 0% N/A
Not Reported 50 0 0% 0% N/A
TOTAL/OVERALL 1000 90 9.0% 9.0% 1.0
2.78
(Female)

38. Race/Ethnicity Average Rate
Average
Expected Rate
Difference
Expected Pricing
Ratio
Asian/Pacific
6.8% 7% 0.2%
0.97
Islander 10.5% 2.3%
Black 12.8% 1.22
Hispanic 11.5% 1.02
11.3% 0.2%
6.1% 0.1%
7.0% 0.0%
0% 0%
White 6.0% 1.00
Other 7.0% 1.00
Expected
Pricing Ratio
1.22
(Black)
Avg. Rate of PBG / Not Reported 0% 1.00
Expected Rate of PBG
*PBG is a Prohibited Basis Group such as Race, Gender, Age, Etc.
-Show by: Race, Gender, and Age
-Significant differences between average rates and expected rates are an indication of potential disparate treatment
-You can also compare “Buy Rates” to “Contract Rates” to see dealer markups

39. Additional Fair Lending Reports
Description Applications Loans
Volumes/Concentrations
Approval/Denial Rates
Disposition (of Applications)
Exception Tracking
Decisionmaker Analysis
Mod/Default Tracking

40. Volumes/Concentrations
Race
All Application
Count
% of All
Applications
Asian/Pacific Islander 50 5%
Black 200 20%
Hispanic 10 0%
White 500 50%
Not Reported 50 5%
-Show by: Race, Gender, and Age
-A low volume of applicants/loans may be an indicator of Pre-screening, Redlining, and/or
Policies with Disparate Impact

41. Approval/Denial Rates & Denial Disparity Ratio
Gender
All Application
Count
Denied Application
Count
Denial Ratio
Denial Disparity Ratio
(by Total*)
Male 400 10 2.5% 0.28
Female 200 50 25% 2.78
Joint 300 30 10% 1.1
Unknown 50 0 0% N/A
Not Reported 50 0 0% N/A
TOTAL/OVERALL 1000 90 9.0% 1.0
-Show by: Race, Gender, and Age
-Significant variations in acceptance/denial ratios may be an indicator of disparate treatment
*The Denial Disparity Ratio can also be calculated by comparing to a control group (i.e. Male) instead of the total.

42. Disposition (of Applications)
Age
All
Application
Count
Approved-
Funded
Application
Count
Approved-Not
Funded
Application
Count
Denial
Application
Count
Withdrawn
Application
Count
Other
<=20 50 20 0 30 0 0
21-30 100 55 5 40 0 0
31-40 300 290 5 5 0 0
41-50 300 200 20 70 10 0
51-60 125 100 5 12 3 5
>60 100 50 25 0 25 0
-Show by: Race, Gender, and Age
-high levels of withdrawn and/or approved-not funded applications may be an indicator of
disparate treatment

43. Exception Tracking
Description
% of
Asian/Pacific
Islander
% of Black % of Hispanic % of White % of Other
% of Not
Reported
Exception Code A 2% 3% 1% 92% 0% 2%
Exception Code B 1% 4% 3% 90% 0% 2%
Exception Code C 2% 6% 3% 87% 0% 2%
Exception Code D 2% 3% 2% 91% 0% 2%
Exception Code E 2% 3% 5% 90% 0% 0%
Etc. 2% 3% 5% 88% 0% 2%
-Show by: Exception Codes, Descriptions, or Yes/No
-Comparatively high concentrations in control groups in certain exception categories are an
indication of potential disparate treatment

44. Decisonmaker Analysis
Description
% of
Asian/Pacific
Islander
% of Black % of Hispanic % of White % of Other
% of Not
Reported
Loan Officer A 2% 13% 15% 68% 0% 2%
Loan Officer B 2.5% 12.5% 14% 70% 0% 1%
Loan Officer C 1% 13% 16% 69% 0% 1%
Loan Officer D 1% 1% 1% 95% 0% 2%
Loan Officer E 3% 12% 17% 65% 0% 3%
Etc. 2% 13% 11% 70% 0% 4%
-Show by: Loan Officer, Underwriter, Branch, Etc.
-Basically any of the above reports (volumes, denial rates, steering, pricing, exception
tracking, etc.) stratified by a decision maker (loan officer, underwriter, etc.)

45. Modifications Tracking
Description
% of
Asian/Pacific
Islander
% of Black % of Hispanic % of White % of Other
-Modification Rates by Race, Gender, Age, Marital Status, Etc.
-High % of Modification’s Denied are an indication of potential disparate treatment
% of Not
Reported
Modification
Granted 2% 1.3% 1.5% 93.2% 0% 2%
Modification
Denied 2.5% 94.3% 2.2% 2.5% 0% 1%

46. Tone at The
Top
Policies &
Procedures
Assessing
Fair Lending
Risk
Training
Bringing it all together…
Any weaknesses or violations are
promptly corrected , including
appropriate restitution.
Correction
Performance
Monitoring
Fair Lending is cultural and
reinforced at the highest levels
and throughout the organization
in both written and verbal forms.
Policies and Procedures provide
clear guidance and are free of
overt discrimination.
Assess and mitigate, as
appropriate, heighted fair lending
risk areas.
Fair lending compliance and
performance is regularly
reported and monitored.
Training occurs regularly and
is well documented. Trainees include top
management, board members, and new
employees.

47. Phone:
888-409-1560
Email:
info@visibleequity.com
https://www.linkedin.com/company/visible-equity
facebook.com/visibleequity
twitter.com/visibleequity
THANK YOU!