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Profit
Published by the Consumer and Community Affairs Division

The Federal Reserve
Bank of Chicago

Summer 2002

PERSPECTIVES ON
CREDIT SCORING AND FAIR
MORTGAGE LENDING

The Final Installment of a Five-Part Series

Profit

The Fed
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The Federal Reserve Bank of Chicago
Summer 2002 Edition

In this Issue

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Perspectives on Credit Scoring and
Fair Mortgage Lending: Part Five in
a Five-Part Article Series

18 lllinois Launches New Anti-

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PERSPECTIVES ON
CREDIT SCORING AND FAIR
MORTGAGE LENDING

MORTGAGE CREDIT PARTNERSHIP CREDIT SCORING COMMITTEE
The purpose of the Federal Reserve System’s Credit Scoring Committee is to
publish a variety of perspectives on the credit scoring process, and to identify
areas in which the use of credit scores may create the potential for disparities
in the home mortgage process. The first four installments in this series
addressed various aspects of the use of credit scores and fair lending concerns,
including the maintenance of scoring models, the use of third-party brokers,
and the provision of assistance in the credit application process.

The fifth and final installment in the series addresses the use of counter offers,
overrides, and second reviews of credit-scored decisions. We solicited feedback
from industry, consumer and regulatory representatives to ensure a variety of
perspectives on these topics.

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SUMMER 2002

CONTRIBUTORS
DAN IMMERGLUCK is a faculty member at the School
of Public and Nonprofit Administration at Grand
Valley State University in Grand Rapids, Michigan. He
recently joined the university after having served as
senior vice president of the Woodstock Institute for
many years. He has written extensively about access to
credit, community reinvestment, and community and
economic development, and he has worked with community organizations and government agencies on a
wide array of community reinvestment and development projects. Mr. Immergluck holds a doctorate in
urban planning and policy from the University of
Illinois–Chicago.
CHRIS ALDRIDGE is a vice president and director of
community affairs for Fifth Third Bank, where he
administers and oversees community affairs for the
bank’s Cincinnati and affiliate markets. He is also
responsible for BLITZ, a $9 billion community development initiative to fund Building, Lending, Investments, and Technology Zones over the next three
years. Mr. Aldridge is experienced in developing and
implementing alternative business strategies to help
financial institutions realize their return on investments. He has been instrumental in establishing relationships with minority brokers that generate
Community Reinvestment Act (CRA) loans, and he
has launched programs to increase product sales and
support business development. Prior to joining Fifth
Third, Mr. Aldridge was the managing principal for
NuCapital Management in Southfield, Michigan. He
holds a juris doctor degree from Wayne State
University and a bachelor’s degree in economics from
Harvard College.

KEVIN STEIN is the associate director of the California
Reinvestment Committee (CRC), a statewide CRA
coalition of more than 200 nonprofit organizations and
public agencies. CRC works with community-based
organizations to promote access to credit and economic
revitalization of California’s low-income and minority
communities. Mr. Stein works primarily on housing
issues, including efforts to fight predatory mortgage
lending. He was the primary author of CRC’s recent
report, Stolen Wealth: Inequities in California’s Subprime Mortgage Market, which investigated subprime lending practices in the state.

Before joining CRC, Mr. Stein worked as the
Community Economic Development Attorney at
the East Palo Alto Community Law Project and for
HomeBase, a law and social policy center on homelessness. Mr. Stein is a graduate of the Georgetown
University Law Center and Stanford University.

MICHAEL LACOUR-LITTLE joined Wells Fargo Home
Mortgage in 2000 as a vice president in the Risk Management Group. Previously, he was the director of
financial research at CitiMortgage. He is an adjunct
professor of real estate finance at the John M. Olin
School of Business at Washington University in St.
Louis, where he teaches graduate-level courses in real
estate finance and mortgage-backed securities. He also
has taught at the University of Wisconsin–Madison,
Southern Illinois University–Edwardsville, and the
University of Texas–Arlington. Mr. LaCour-Little holds
a doctorate from the University of Wisconsin–Madison.
His papers have appeared in Real Estate Economics,
Journal of Real Estate Finance and Economics, Journal
of Real Estate Research, Journal of Real Estate
Literature, Journal of Housing Research, Journal of
Housing Economics, Journal of Fixed Income, and
Mortgage Banking.

STANLEY D. LONGHOFER holds the Stephen L. Clark
Chair of Real Estate and Finance in the Barton School
of Business at Wichita State University, where he
founded the Center for Real Estate in 2000. He has
been actively involved in local urban redevelopment
issues, coauthoring several reports on the viability of
proposed redevelopment projects and serving as chairman of a special committee that addressed regional
land-use concerns. Prior to coming to Wichita State,
Mr. Longhofer was a financial economist at the Federal
Reserve Bank of Cleveland, where he was a founding
member of the Federal Reserve System’s Fair Lending
Advisory Group. Mr. Longhofer’s research on mortgage discrimination, financial contracting, and bankruptcy has been published in leading academic journals, including the Journal of Real Estate Finance and
Economics, the Journal of Money, Credit, and Banking,
the Journal of Financial Intermediation, and the
European Economic Review. In addition, he has written several popular articles on the mortgage market
and other topics. He holds a doctoral degree in economics from the University of Illinois.

PERSPECTIVES ON CREDIT SCORING AND FAIR MORTGAGE LENDING

STATEMENT OF DAN IMMERGLUCK
The contributors to this article collection were asked
to respond to the following statement:
The emergence of credit scoring in the home-buying
process has been a significant contributor to the
increase in mortgage lending activity around the
country. Proponents of scoring systems argue that
their purely objective nature constitutes a significant fair lending benefit by virtually assuring
against disparate treatment on a prohibited basis.
Others point out that when inaccurate information
is contained in the credit report, the consumer may
not have the opportunity to rectify the report, and
the lending decision will be made with inaccurate
data. Another concern is that the objectivity of the
credit score may be lost when a lender supplements
the scoring process with overrides, counteroffers, or
second review programs that are subjective in
nature or in use.
Credit scoring overrides and counteroffers can serve
important functions in maximizing access to credit.
However, their nature and usage could result in
unlawful discrimination. A frequent use of overrides
would suggest a mismatch between the scoring system and the lender’s credit policies or objectives.
In addition, inconsistency in the use of either
“high-side” or “low-side” overrides to reach a
credit decision, or inconsistent counteroffers made
to similarly situated applicants, may result in
disparate treatment on a prohibited basis.
Furthermore, if a lender engages in a subjective second review process, unlawful disparities may result
from the absence of well-established, consistentlyapplied second review guidelines that include clear
explanations of judgmental factors and cut-off scores.
Considering the credit scoring issues outlined above,
please comment on the following questions:
1. What methods should lenders adopt to optimize
the usefulness of overrides, minimize their frequency,
and ensure their use is in compliance with the fair
lending laws?
2. What actions could lenders take to ensure counteroffers are extended fairly?
3. What measures and systems should be instituted to
ensure that the second review process is operating in
a manner that is consistent and fair?
4. Describe steps lenders could take to ascertain
the level of staff ’s compliance with established
policies and procedures.

As a researcher and an advocate for fair lending and
community reinvestment, I have shared the concerns
of many over the now ubiquitous use of credit scoring in the mortgage lending process. Many of my
concerns have been articulated by others in earlier
articles in this series. For example, in Part I, Cal
Bradford points to the disparate impact of credit
scoring systems and questions where the threshold
[should] be set in determining whether a scoring
system meets the “business necessity” test under the
Equal Credit Opportunity Act and Regulation B. If
lowering the threshold for approving loans reduces
disparate impact but increases loan losses, what
standard is to be used to determine whether such
losses have increased too much? Lenders may argue
that pressures for ever-increasing earnings force
them to push loan losses lower and lower, therefore
raising approval thresholds. Who determines how
low losses need to be—the market’s invisible hand?
Even conceding such a market-based approach, who
determines where the invisible hand has set that
threshold—the lender or the regulator?
Previous commenters have pointed to other important issues, such as the lack of transparency in scoring
models and the focus on correlation over causation.
Before exploring particular issues with overrides and
counteroffers, however, I feel obliged to spend a little
time on a couple of issues that I feel did not receive
enough attention in earlier parts of this series. First,
alluded to in other essays but perhaps not addressed
directly, are the problems that increasingly sophisticated lending tools pose for less-sophisticated
loan applicants. As lending processes become more
difficult to understand (even if there is greater disclosure, credit scoring systems often are more complex
and mystifying than previous systems), those who
have less understanding of how credit works or
less-developed mathematical skills will be more
confused about why they are denied credit or
charged higher rates. Without such an understanding, it is unlikely that people will be able to improve
their credit prospects very much. While some counseling programs do a good job of dealing with this
problem, the proliferation of credit scoring has not

PROFITWISE

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SUMMER 2002

been matched by an equivalent investment in
home buyer and home owner counseling resources.
Another larger issue posed by credit scoring that
has been brought up more often in the context of
safety and soundness concerns is often referred to
as “paradigm shift.” Credit scoring systems are relatively new, only having grown into common use in
the mortgage market since the mid-1990s. Most
have not been tested extensively during a substantial change in the business cycle (although that is
likely occurring now to some degree). When a major
business cycle or technological change occurs, scoring models may not do a good job at predicting
behavior. While these concerns typically have
focused on the possibility of scoring systems yielding approval rates that are too high (thus causing
safety and soundness problems), it is also possible
that paradigm shifts cause changes in the importance
of different variables in predicting loan performance
—which, if not corrected, could unfairly disadvantage minority applicants. For example, some systems
disproportionately penalize some minority applicants
for having more credit activity with finance companies. If the regulation of finance companies were to
improve significantly, we might expect the negative
effect of such interactions to diminish, thus becoming
a less important determinant of risk.
An often-overlooked issue with credit scoring is its
use in data-mining and marketing efforts by lenders
and mortgage brokers. It is now possible to obtain
data on the credit scores of residents of specific neighborhoods, enabling lenders to target specific areas
with different types of products—which, in turn, can
lead to increasingly segregated lending markets.
Turning now to the more specific problems of overrides and counteroffers, there are a number of issues
about which lenders, regulators, and advocates
should be particularly concerned. First, to be clear,
overrides and counteroffers are not problems in and
of themselves, and they can be an important part of
mortgage lending operations. The growth in credit
scoring means that such practices have become
more prevalent, however, and so can create greater
fair lending risks.

As shown in the Deposit Guaranty case, where the
lender was found to favor non-minority applicants
in the override process, lenders must monitor such
practices closely. They should look especially at
aspects of the scoring system where minority borrowers may be disadvantaged (for instance, failure
to consider a history of rental payments in the
evaluation of credit history).
In terms of counteroffers, if above-standard pricing
is used, lenders should be careful to use real, riskbased pricing and should be required to document
and justify this to regulators. Arbitrary risk premiums should not be tolerated. Regulators should
compare the pricing and approval systems to
those of other lenders.
Clearly, retail lenders must be concerned with both
the fairness of overrides and the fairness of pricing
in overrides. However, regulators need to clarify
and enforce the fact that wholesale lenders—or
lenders with correspondent relationships—are liable
for any discriminatory behavior on the part of their
brokers or correspondents. Because brokers are
disproportionately active in minority communities,
this is an important point. Effectively, lenders may
attempt to “outsource” discriminatory overrides by
having brokers perform the override function so
that the lender itself ends up with few overrides,
if any at all.
Related to this problem is the common scenario of
one holding company owning several affiliates
(bank and non-bank) that engage in mortgage lending. If, for example, the bank affiliate tends to
make retail loans to white borrowers, and the nonbank affiliate tends to make wholesale loans
through brokers to nonwhite borrowers, then an
override system that applies only to the bank may
disproportionately benefit white applicants when
considering all applications to the holding company
and its brokers. This problem, in turn, is related to
the larger need for fair lending examinations to be
conducted on a holding company basis, not just on
a bank basis.

PERSPECTIVES ON CREDIT SCORING AND FAIR MORTGAGE LENDING

Second reviews, overrides, and counteroffers can be
an important part of a lender’s program to adequately
serve all segments of a market. Guarding against
fair lending problems requires a comprehensive
system of oversight and controls, and a regulatory
framework that includes close and comprehensive
scrutiny of the override process.

STATEMENT OF CHRIS ALDRIDGE
Within predominately minority neighborhoods,
sub-prime financing accounts for over 50 percent of
the mortgage lending activity. Separate HUD and
Fannie Mae studies have found that many of these
borrowers (up to 50 percent) would have qualified
for prime or near-prime financing. This situation
has generated a flurry of local lending regulations,
and it has refocused attention on the impact of credit scoring on the availability of prime-rate products
in certain markets.
The perceived negative impact of credit scoring is
counterintuitive if the tool is used properly. The
reduction in time and resources spent underwriting
high-score applicants should expand resources to
manually underwrite cases in which the borrower
is a good risk but has no credit history or inaccurate
information in the mortgage application. More
important, it could also free resources to offer more
labor-intensive, complementary products that use a
combination of credit training, rehabilitation, and
recent payment history to offer prime- or nearprime-rate products. Thus, the proper use of credit
scoring should increase properly priced credit in
all market segments.

Specifically, an organization’s overall strategy
establishes the vigor with which each market
segment is pursued. A business strategy that requires
“fair-share” penetration across all segments within
the company’s footprint aligns business line and compliance objectives, and provides top-down pressure to
ensure adherence to credit policy and aggressive outreach efforts. It also signals an institutional intolerance
for fair lending and credit policy violations.
The most important phase of the origination process
is the establishment of market focus and business
goals. Business goals that include penetration targets
and objectives for all market segments drive the
marketing, advertising and outreach programs that
bring prospects into the system. In the absence of
such a program, a perfect fair lending and credit

A business strategy that requires “fairshare” penetration across all segments
within the company’s footprint aligns
business line and compliance objectives,
and provides top-down pressure to
ensure adherence to credit policy…

This series of articles on the use and monitoring
of mortgage origination programs based on credit
scoring, reflects concern over the proper use of
credit scores, and of policies and processes to ensure this increasingly prevalent tool is used fairly.
However, this focus on tactical compliance ignores
the more important, proactive impact that a bank’s
strategic focus can have on fair lending and credit
policy adherence.

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SUMMER 2002

policy still would generate an inequitable result. In
addition, inclusive business goals authored by senior
management signal to originators and underwriters
that failure to observe policy equitably has consequences for performance reviews. This business line
pressure to perform reinforces the compliance
program and ultimately produces more equitable
lending results and a stronger compliance program.
Fifth Third Bank’s senior executives sponsor an
aggressive Senior Diversity Strategy Initiative (SDSI),
which seeks to identify opportunities to increase
share in each market segment within our footprint.
In the context of fair lending and credit access,
its most important function is to signal executive
management’s interest in serving every segment of
our markets to the line employees responsible for

lending and assistance programs. SDSI establishes
benchmarks and business objectives, creating topdown pressure to aggressively capture all “good
credit risks”and prospects requiring additional help.
The SDSI complements our ongoing business process,
which establishes aggressive business goals for each
tract within our market area and holds management
accountable for meeting these objectives. These
goals include both volume and loan-default
performance targets. As a result, our marketing
program and outreach efforts are structured to reach
areas of underperformance. This effort results in
more than fair-share allocation of underwriting
resources to underserved markets. The goals must
be aggressive enough to make inequitable behavior
expensive at the personal level.

The secondary review process allows the bank
to compare performance to policy, to spot patterns
that may indicate a breakdown in the training
regime, or to identify opportunities to assist
prospects in obtaining credit.

PERSPECTIVES ON CREDIT SCORING AND FAIR MORTGAGE LENDING

Banks should invest in strong training and education
programs to ensure that each individual involved in
the lending process is proficient in their understanding of lending policy and the critical importance of
equitable treatment. Each person should be aware
of the tools available to our customers to improve
credit scores. The program should include classroom
instruction as well as follow-up training programs
that include some self-study component. Participation
in such training regimens should be mandatory,
with a tracking mechanism to verify progress.
A secondary review process that compares similarly
situated applicants provides the most effective and
timely method to ensure that policy is followed and
assistance is offered on a consistent basis. The secondary review process allows the bank to compare
performance to policy, to spot patterns that may indicate
a breakdown in the training regime, or to identify
opportunities to assist prospects in obtaining credit.
Banks should offer portfolio products that do not
rely completely on the automated underwriting
process. These products have proven profitable
for bank and non-bank lenders. The more flexible
process generally leads to a more complete discussion
of credit factors. It often allows banks to capture
business from individuals who are good risks but,
for one reason or another, are not identified in a
purely automated process. A flexible product with
stretch goals creates an environment in which all
credit issues are thoroughly discussed.
Banks should, through their training programs,
make certain that originators are well trained in
credit scoring and its impact on the approval and
pricing process, as well as the applicability of
alternative products in the case of credit problems.
The availability of products with different credit
score thresholds, in combination with strong training
and aggressive goals, will invariably lead to a full
discussion of credit issues.
Executive management’s commitment to each market segment and stretch goals for production and
credit performance create an environment in which

disparate treatment becomes personally expensive.
The resulting performance pressures ensure that all
applicants become critical to business line success
and, thus, the recipient of all reasonable efforts.
Good intentions mean nothing without the right
tools. An aggressive internal training program that
includes diversity as well as credit and product
components is critical to ensuring that our staffs
have the requisite knowledge to deliver consistent
service to all of our loan applicants. We track training participation and send reminders to personnel
who fall behind in their training.
To police actual performance, we conduct a second
review of all denied mortgages for minority mortgage applicants. These second reviews are conducted
weekly, and committee members include the mortgage business line manager and staff members from
compliance and community affairs.
In addition, a formal fair lending audit is conducted
1
at least twice each year. Fair Lending Wiz includes a
number of tools that allow us to spot patterns for
further review.
A combination of senior management involvement,
strategic focus, and a sound compliance program
are critical to generating equitable fair lending
results on a consistent basis. Unless business goals
include volume from underserved markets, the
most perfect compliance system will generate
meaningless results.
The combination of strategic focus through our
BLITZ program, an aggressive training program,
and compliance audits has allowed Fifth Third
Bank to produce a number of impressive results.
First, we boast a denial rate for African American
applicants in our home market that is 25 percent
lower than the Home Mortgage Disclosure Act
(HMDA) aggregate. Second, we have continued to
meet our aggressive business growth targets in each
of the past two years. Finally, we continue to boast
superior credit performance within our peer group.

A commercially available software package.

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•

SUMMER 2002

STATEMENT OF KEVIN STEIN
The use of credit scoring models to evaluate creditworthiness has become widespread, even finding its
way into the insurance arena, despite serious concerns about the fairness and utility of these models.
Credit scoring models were developed and adopted
primarily as a means of helping financial institutions
manage credit risk. The California Reinvestment
Committee (CRC) believes financial institutions
should be working instead to develop and adopt
innovative methods of safely extending low-cost
credit to underserved borrowers and communities.
Most observers accept that the use of credit scoring
models has had a disparate impact on people of
color. Below are reasons to question whether heavy
reliance on credit scores furthers the nation’s interest in fair lending and equal access to credit, as well
as the safety and soundness of financial institutions.
The Larry Rule
In early 1996, an unlikely report came out that then–
Federal Reserve Board Governor Larry Lindsey, now
President Bush’s chief domestic economic adviser,
was denied a Toys “R” Us credit card because he did
not have an adequate credit score. This incident
raised questions about which and whose values
underlie credit scoring models and how financial
institutions react to these models. American Banker
reported that “the result of all this flap will be what
we call the Larry Rule,” whereby financial institutions
look harder at credit scores to ensure the factor that
apparently tripped up Mr. Lindsey—too many credit
inquiries—didn’t result in denials to [other] creditworthy borrowers. All of this leads us to wonder if
the credit denials of any low-income, immigrant,
elderly or of color credit applicants resulted in
similar introspective industry discussions.
The underlying data may be inaccurate
Credit scores are based on reports from the main
credit bureaus, even though these reports often
contain errors. The Home Buyer Assistance and
Information Center, located in Oakland and serving

consumers in the San Francisco Bay area, estimates
that at least half of all credit reports reviewed by
trained counselors contain errors. What may be an
inconvenience for many becomes a significant
barrier to credit for people who lack the resources
to discover the mistake, appreciate its significance,
and correct the error. Further, we now know that
unscrupulous creditors, such as predatory mortgage
lenders, often do not report their borrowers’ good
payment history to credit-reporting agencies in
order to keep them in the sub-prime market.
People who understand the game can improve
their score
With some knowledge about how credit scores are
derived, credit applicants can improve their credit
scores. Prospective borrowers can even pay a fee to
find out how to improve their score. Apparently,
such programs are being offered by the companies
that devise the credit scoring model themselves. But
which consumers will find out about these services,
and who will pay for them? Is the person who
opened a new account or closed an old one in order
to manipulate her score really a better credit risk
than she was before she was advised to make these
changes? Is she really more likely to pay off her
mortgage than the applicant who did not know
how to manipulate her score?
Disparate levels of assistance
Much can happen in the handling of a home loan
application. Often, a lender or broker wants to see
additional documentation to support the application
of a nontraditional borrower. Problems can arise
when applicants are not given equal assistance in
securing the necessary documentation. Testing conducted by fair housing councils in California
revealed that customers of color are treated differently than white customers upon entering a bank
or thrift. They are less often given a home loan
application, less often encouraged to speak to bank
staff, and less often given key information that
could strengthen their application.

PERSPECTIVES ON CREDIT SCORING AND FAIR MORTGAGE LENDING

The two-tiered banking system is perpetuated and
punishes the victim
Disturbingly, credit scoring models may downgrade
borrowers who have accounts with finance companies or sub-prime and payday lenders. These borrowers are in the sub-prime market because they
and their neighborhoods have been abandoned by
mainstream banks and thrifts. A recent CRC study
of sub-prime borrowers in California revealed that
a shocking 72 percent of respondents did not even
approach a bank or thrift for their mortgage loan,
even though most reported they had seen their
credit score or credit report and that it was “good”
or “excellent.” These figures are consistent with
estimates by Fannie Mae that up to 50 percent of
borrowers in the sub-prime market could have
qualified for prime loans. Using the sub-prime
market may lower one’s credit score, essentially
punishing those with few real or perceived mainstream credit alternatives, many of whom have
good credit.
Not all borrower behavior is based on the values
that likely underlie credit scoring models
Credit scoring models are based, by and large, on
how the majority of “mainstream” consumers use
credit. Such models are designed to match credit
applicants with the manifest behavior of middleclass consumers. It is unclear how such models
account for our legacy of discrimination in access to
credit. Credit scoring models that penalize people
with no established credit are not a good indicator
of whether a borrower will repay a mortgage.
Lenders should accept alternate forms of credit,
such as utility and rent payments, as evidence of
a borrower’s creditworthiness.

Is the person who opened a new
account or closed an old one in
order to manipulate her score,
really a better credit risk than she
was before she was advised to
make these changes?

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SUMMER 2002

The need for secondary review

The more people at an institution
who may override a credit decision,
the greater the chance for [similarly
situated] applicants to be treated
differently… Override authority

Given the disparities that may result from credit
decisions based solely on credit scores, there is a
role for secondary review of loan applications.
Unfortunately, existing secondary-review programs can
appear more theoretical than real, merely affirming
the initial decision to deny low-cost credit to lowincome borrowers and borrowers of color. In designing
and implementing a process for secondary review, the
following principles should be observed.
Clear guidelines must be established
The danger of disparate treatment of applications
based on impermissible considerations, such as
race, gender, and age, is heightened when
underwriters are allowed to override credit-score
determinations. Thus, clear rules regarding overrides must be developed and applied consistently.
When exceptions or overrides are made, the file
should clearly reflect the reasons for doing so.

should rest with a small number

Focus on compensating factors for
low-side overrides

of key staff.

Override guidelines should be geared toward ensuring that applicants whose credit scores fall below a
given cut-off will be evaluated in a comprehensive
fashion. Underwriters should review the whole file,
considering character issues. For applicants with little or no credit history or those with spotty credit,
underwriters should consider the existence of alternate credit, such as utility payments and history of
making housing payments in a timely fashion. This
is especially important for applications for prime
credit, because denial could mean the unnecessary
and costly relegation of a creditworthy borrower to
the sub-prime, higher-cost loan market.
High-level review
Secondary reviewers who consider overriding a decision based on credit score should be senior-level staff.
The more people at an institution who may override
a credit decision, the greater the chance for [similarly
situated] applicants to be treated differently, resulting
in risk of fair lending violations. Override authority
should rest with a small number of key staff.

PERSPECTIVES ON CREDIT SCORING AND FAIR MORTGAGE LENDING

Fair lending training at all levels
Staff at all levels of the institution should be trained
in fair lending and its implications for the institution’s use of credit scoring models. The same should
hold true for mortgage brokers, who account for the
majority of home loans today. Institutions should
have clear nondiscrimination policies that are
adhered to at all stages of the loan process.
Periodic loan file review
Implementation of a company’s credit scoring policies
must be monitored periodically for consistency in
acceptance and denials of home loan applications,
as well as the terms of loans originated. All loans
that have gone through secondary review must be
examined and analyzed to determine whether the
secondary review and override process is having
a disparate impact on any group. Similarly, lenders
should review whether the company’s general use
of credit scoring models is having a disparate
impact on protected classes and should revise
the model or its usage appropriately.
Equal assistance to loan applicants
Lenders and brokers should always and consistently
explain to credit applicants the meaning and significance of their credit scores, and they should assist all
borrowers equally in improving their credit scores to
qualify for a loan. Lenders should develop a policy
on how to assist applicants who disagree with an
initial determination of the lender.

HEAVY RELIANCE ON CREDIT SCORING MEANS
MORE MUST BE DONE TO ENSURE EQUAL ACCESS
TO CREDIT
Prime lenders must develop better marketing,
outreach, and products for underserved communities
Prime lenders need to better serve qualified lowincome, elderly, or immigrant borrowers and borrowers of color. The fact that half of all sub-prime
borrowers might qualify for prime loans means
that thousands of borrowers are losing thousands of
dollars in home equity and wealth because they are

not being well served by the prime lending banks,
thrifts, and mortgage companies. The other side
of this equation is that these borrowers also represent lost business opportunities for financial institutions. Los Angeles Neighborhood Housing
Services recently reported having difficulty finding
prime lenders to originate home loans to hundreds
of high credit score borrowers who presented linguistic and other underwriting challenges.
Refer qualified borrowers up for prime products
Several banks and thrifts own sub-prime lending
subsidiaries and affiliates that do not refer qualified
loan applicants with appropriately high credit scores
to the prime lending bank or thrift. Given that subprime applicants are more likely to be people of color
and the elderly, failure to have an effective referral
up program raises serious fair lending questions.
Improve HMDA (Home Mortgage Disclosure Act)
The Federal Reserve Board must help root out
discrimination in home lending more aggressively
by enhancing HMDA data to include credit scores
and the annual percentage rate on all HMDA
reportable loans. Without such price and credit
data, HMDA is very limited. Each year, community
groups analyzing HMDA data note disparities in
lending. Each year, industry groups respond by
pointing out the limitations of HMDA. At the same
time, industry groups continue to oppose efforts to
include credit score data in HMDA, and they have
successfully lobbied the bank regulators to postpone
implementation of changes to HMDA that will
include the reporting of APR data on home loans
for the first time.
Investigate these issues further
The Federal Reserve should conduct a study that
includes a review of existing loan files to examine
the impact of credit scoring on borrowers, especially
protected classes. As with credit scoring models, the
public is in the dark when it comes to the validity of
credit decisions. The Fed, which has access to bank
loan files, can illuminate these issues for the public,
thereby enhancing the public’s faith in the lending

PROFITWISE

•

SUMMER 2002

industry. The Boston Fed went a long way in this
direction when it developed its study on mortgage
lending and race in the early 1990s.

procedures to monitor the incidence of overrides to
ensure they do not favor or disfavor any class of
loan applicant disproportionately.

CONCLUSION

2. What actions could lenders take to ensure that
counteroffers are extended fairly?

Credit is not available to all consumers equally,
and the public knows it. The National Community
Reinvestment Coalition commissioned a national
poll, which found that three-quarters of Americans
believe steering minorities and women to more
costly loan products than they actually qualify for
is a serious problem. Eighty-six percent feel that
laws are needed to ensure banks do not deny loans
to creditworthy borrowers based on race, religion,
ethnicity, or marital status. Prime lenders are missing out on significant business opportunities, and
the public continues to view banks, thrifts, and
mortgage and finance companies with distrust.

STATEMENT OF MICHAEL LACOUR-LITTLE
Wells Fargo Home Mortgage strongly believes that
credit scoring has provided significant net benefits
to both the mortgage industry and the public.
Credit scoring has helped make mortgage credit
more widely available to all households, including
traditionally underserved market segments, and it
has helped fuel the growth in homeownership that
has occurred over the past decade. We welcome
open public dialogue about credit scoring and second reviews and, thus, we are pleased to address
the following questions.
1. What methods should lenders adopt to optimize
the usefulness of overrides, minimize their frequency,
and ensure their use is in compliance with fair
lending laws?
Credit scores can incorporate only a limited set of
factors. Overrides tend to occur most frequently
when certain important risk factors are omitted
from the credit score. Consequently, a high rate of
overrides may indicate that it is time to redevelop
the credit score. In addition, lenders should, as part
of a comprehensive fair lending program, institute

Monitoring counteroffers is just as important as
monitoring the incidence of overrides. Lenders may
wish to establish a centralized monitoring function
within a staff department, such as the compliance
function, to ensure adherence to corporate policies
and procedures regarding credit scoring, overrides,
and second reviews.
3. What measures and systems should be instituted
to ensure that the second review process is operating
in a consistent and fair manner?
In connection with credit scoring, a second review
process typically reviews loan applications that do
not meet credit-score guidelines—that is, those that
are turned down under strict reliance on the score.
Second reviews seek to determine whether compensating factors not captured in the score are present
and whether, on balance, those factors outweigh
the negative outcome of the scoring process.
Monitoring the use and outcome of the second
review is key.
Understanding the decisions made as a result of
second reviews can provide important information,
ensure adherence to corporate policies and procedures,
and help to ensure there is no disproportionate
effect on any class of loan applicant.
4. What steps can lenders take to ascertain the level
of staff compliance with its policies and procedures?
Often, effective monitoring processes are based on
the principles of quality assurance, testing samples
of actual transactions to determine defect rates,
reporting results to management, and then initiating corrective action as required. Corrective action
might include broad training, individualized coaching, and a range of more punitive sanctions for
repeated violations.

PERSPECTIVES ON CREDIT SCORING AND FAIR MORTGAGE LENDING

STATEMENT OF STANLEY D. LONGHOFER
MORTGAGE SCORING MODELS AND THE MYTH
OF OVERRIDES
One of the most significant developments in the
mortgage market over the last decade has been the
formation and growing acceptance of computerized
credit scoring models as a supplement to—or a
replacement for—traditional manual underwriting
techniques. Programs such as Fannie Mae’s Desktop
Underwriter and Freddie Mac’s Loan Prospector
incorporate performance information from literally
hundreds of thousands of mortgage loans to provide a fast, objective, and statistically reliable
method for comparing the complex trade-offs
inherent in mortgage underwriting.
In addition to assisting lenders in risk assessment,
these objective scoring models can be a powerful
tool for increasing consumers’ access to mortgage
credit. Not only does their increased efficiency
translate into reduced closing costs for consumers—
in and of themselves, a significant barrier for many
lower-income households—if used exclusively,
these models could effectively eliminate overt big2
otry and disparate treatment from the underwriting
process, as protected class status is explicitly
excluded from these models. Thus, scoring models
hold out great promise to make the mortgage market more fair and accessible.
Ultimately, however, mortgage underwriting can
never be fully relegated to a scoring model, nor
indeed should it be; subjective human evaluation
will always be essential for some portion of all
mortgage applications. Why? Despite the power of
scoring models, there are often factors an underwriter would like to consider for which there is
insufficient historical data for computers to analyze,
or for which a subjective interpretation is required.
For example, a lender may wish to discount a period
of past delinquencies that can be traced to a documented medical problem from which the applicant has recovered. Such “idiosyncratic” factors

Disparate treatment is defined as a situation in which a lender treats a credit
applicant differently on the basis of race or any other prohibited factor. It is
considered by courts to be intentional because no credible, nondiscriminatory
reason explains the difference in treatment.

cannot be incorporated into an objective scoring model, even though they may provide information that is vital to underwriting credit risk.
This subjective analysis may, in fact, have further
benefits in improving access to mortgage credit,
particularly for lower-income and minority households. Research over the last two decades—
including the notorious Boston Fed study—has
provided evidence that these households are more
prone to the very “application idiosyncrasies” that
scoring models may be unable to process. Thus,
subjective analysis is a crucial step in ensuring that
creditworthy minority and lower-income households receive the credit for which they are qualified.
At the same time, however, many perceive a dark
side to the use of “overrides” in the underwriting
process. In particular, this subjective analysis may
allow lenders to inject (intentional or inadvertent)
prejudicial bias back into the underwriting process.
On the flip side, lenders may be too unwilling to
reverse the conclusions of the scoring model, either
because the subjective analysis itself is too much
effort or because secondary market purchasers may
be unwilling to purchase loans that were originally
“rejected” by the scoring model. As a result, many
consumer advocates are skeptical that the benefits
promised by mortgage scoring programs will actually be realized.
Thus, we are faced with the question of how to
extract the benefits inherent in scoring models while
ensuring that any follow-up subjective analysis is
applied fairly and consistently. In other words, the
challenge is to make sure that any overrides to the
objective analysis promote rather than hinder creditaccess objectives.
The main point we wish to make in this essay is
that this problem is fundamentally no different
from what must already be done in the context of a
manual mortgage underwriting process. In fact, we
argue that the term “override” is a misnomer in the
context of mortgage underwriting, as the scoring

PROFITWISE

•

SUMMER 2002

model is not designed to provide a definitive underwriting decision. To understand how subjectivity
and “overrides” fit into the mortgage scoring
process, it is important to understand how scoring
models are used, and how they are not used.
The process of mortgage underwriting is essentially
the same, whether it is done manually or with
scoring models. An applicant’s characteristics are
compared to an explicit set of “ideal” standards
(for instance, maximum expense and loan-to-value
ratios, maximum number of delinquencies, sufficient verified liquid assets). Although these standards are stated as the lender’s “requirements,”
as a matter of practice all applicants who exceed
this ideal are approved, as well as many who fall
short. This implies that the lender’s true minimum
underwriting standard is lower than that required
by the objective guidelines.
Instead, these objective standards are used to sort
the applications into three groups that we characterize
as Yes, No, and Maybe. Applications that possess
all of the ideal characteristics (the Yes group) are
almost universally approved. When they are rejected,
it is usually because of a material change in the
information that put them into the Yes group to
begin with (for example, the applicant suffered a
sudden layoff). Similarly, the No group consists of
applications for which no further analysis is necessary because they clearly represent too great a credit
risk. Applicants in this group may have severe
blemishes on their credit reports, very unstable
income, or high proposed loan-to-value ratios.
As a practical matter, the No group is generally
quite small, as such individuals will rarely even
complete the application process.
The remaining applications represent the vast group
of Maybes, which must be reevaluated using more
subjective analysis. At this stage, the underwriter
attempts to ascertain whether the applicant’s favorable characteristics are sufficient to outweigh any
factors that fail to meet the ideal standard, or if there
are mitigating circumstances that offset the fact that
the application does not meet the ideal standards.

Whether a scoring model or a manual underwriting
model is employed, the purpose of the objective
analysis is not to determine which applications
should be approved and which should be denied,
but rather to isolate those applications that require
further subjective evaluation. There are several
ways in which scoring models can improve the
integrity and efficiency of the subjective process.
First, automated systems can process many more
applications much more quickly than a manual
analysis. This not only shortens the time lapse between application and loan closing, it also reduces
the cost of processing relatively standard applications,
freeing up an underwriter’s time to focus on the
Maybe group.
Second, scoring models are developed using
objectively verified performance information,
and therefore they can do a more effective job of
assessing risk layering or considering the tradeoffs among different factors. For example, is a
20 percent front-end ratio enough to offset a 45
percent back-end ratio? Is a spotless credit record
over the last year enough to offset three 60-day
mortgage delinquencies that occurred two years
ago? While underwriters can make subjective
assessments of such trade-offs, scoring models can
do this quickly, objectively and consistently across
applications. The upshot is that scoring models
effectively reduce the number of Maybes (generally moving many into the Yes group), once
again allowing underwriters to focus their efforts
on applications that really require human judgment.
Third, the purpose of the subjective analysis itself is
different when used in conjunction with a scoring
model. Subjective analysis is used only if the application contains factors that occur too infrequently
in the general population for the scoring model to
accurately assess, or if the application is missing
some crucial information required by the scoring
model. These same judgments must be made with
a manual underwriting process as well. However,
manual underwriting must also evaluate subjectively
the impact of risk layering. In other words, manual
underwriting involves the subjective consideration

PERSPECTIVES ON CREDIT SCORING AND FAIR MORTGAGE LENDING

of both “irregular” applications and “marginal”
applications, the latter of which can be sorted
objectively by a scoring model. Thus, using a scoring model actually reduces a lender’s reliance on
subjectivity in making underwriting decisions.
As described above, the intent of a subjective
review is to collect and weigh all of the relevant
information in order to come to a Yes or No
decision for each application that a scoring model
identifies as a Maybe. Clearly, a subjective review
does not “override” an underwriting decision made
by the scoring model, as no such decision is actually
made. Instead, the subjective review comes to a Yes
or No underwriting decision that the scoring model
explicitly recognized it could not make.
This is in contrast to what typically occurs with the
use of credit scores in making consumer credit decisions. With credit cards and other personal loans, an
applicant’s score, as reported by a credit bureau, is
often the only factor a lender considers, and deviations from a predetermined cut-off are relatively
infrequent. In this context, the term “override” is
perfectly appropriate to describe, for example, a
decision to lend to an applicant whose score does
not meet the cut-off.
Mortgage lending decisions involve much more
complex trade-offs than consumer credit, however, so lenders never rely solely on a credit
bureau score the way they may for unsecured
consumer credit. In addition, the opportunity to
subjectively review the Maybe group is essential
if lenders are to use scoring models to create
greater access to credit. If the subjective process
were eliminated or curtailed in a meaningful way
out of concerns about fairness or bias, the efficiency
of a scoring model would be compromised.
For example, if subjectivity were eliminated,
lenders would be forced to either deny loans sorted into the Maybe group or lower the bar defining what constitutes a Yes. If the first path were
taken, minority and lower-income applicants
would bear the brunt of this policy, because of

their greater likelihood of falling into this group.
On the other hand, if the Yes bar is lowered, then
the cost of mortgage credit would have to increase to offset the poor underwriting decisions
the scoring model would be forced to make. Once
again, this would disproportionately affect lowerincome applicants because their ability to afford
home ownership is affected more directly by
mortgage pricing.
The real question, therefore, is how to make sure
that any subjective analysis is conducted both
fairly and accurately. Consistency across applications is the key. Yet this is inherently difficult,
given that these applications require subjective
analysis precisely because they are unique and not
completely comparable with others. As a result,
a subjective process can mask illegal discrimination, both intentional and inadvertent. It is
important to acknowledge, however, that this
problem is fundamentally no different from a fair
lending perspective than it always has been with

…the challenge is to make sure that
any overrides to the objective analysis promote rather than hinder credit
access… this problem is fundamentally no different that what must
already be done in the manual
mortgage underwriting process.

PROFITWISE

•

SUMMER 2002

manual underwriting. Thus, the techniques
lenders should apply to monitor subjective
analysis for compliance with fair lending laws
are the same with scoring models as they are
with manual underwriting.
While there are differences in the supporting role
played by subjectivity with scoring models versus
manual underwriting, we believe these differences
give scoring models a unique and important role in
expanding access to mortgage credit. Their superior
ability to assess the layering of risks (especially in
the case of marginal applications) significantly

CREDIT SCORING ARTICLE SERIES CONCLUSION
This installment concludes the five-part series
of articles on credit scoring and fair mortgage
lending.
In the course of the series, we endeavored to
keep the discussion in plain terms, highlighting the fair lending aspects of the topic. Even
when the topic of credit scoring is narrowed to
fair lending considerations, the dialogue
inevitably moves to related issues such as
training of bank staff, third-party relationships
and credit report accuracy. Accordingly, we
asked our respondents to comment on these
and other aspects as well. Notably, the controversial aspects of credit scoring fell into just a
few main areas. Though not an exhaustive list,
virtually every respondent mentioned at least
one of the following areas.
Credit scores of minorities are disproportionately
lower than scores of white applicants.
Exactly why that is the case, and the ramifications for minority mortgage applicants, are of

reduces the number of applications to which subjectivity is applied. Scoring models also greatly
improve underwriting efficiency, in part by allowing lenders to focus their underwriting efforts on
applications that are too unique for computers to
analyze. Furthermore, these models provide a
benchmark for lenders in conducting their subjective assessments, giving them better information
with which to make their evaluations. In the end,
lenders’ ability to combine scoring models and
subjective analysis will bring the full power of
scoring models to promote fair lending and
broader credit-market access.

concern to consumer advocates. That there is
racial disparity is not generally refuted, and in
part reflects the uneven distribution of wealth,
education and opportunity in our nation. The
controversy arises from other potential reasons
for disparity. Do certain factors considered in
scoring models, or their weight in determining
the score, effectively serve as proxies for race?
Past use of certain types of lenders, such as
finance companies, is often cited.
There is much misinformation about the key factors
that impact a credit score; even steps that are otherwise in the consumer’s best interest can lower the
score in the short term.
People not in the financial mainstream have
less access to important, basic information
about optimizing their credit score. For example, closing little-used or unused accounts
might be a good idea from the standpoint of
managing credit responsibly. However closing
accounts in anticipation of applying for a
mortgage might produce a lower credit score
by increasing the ratio of debt to available

PERSPECTIVES ON CREDIT SCORING AND FAIR MORTGAGE LENDING

credit above the optimal range. This ratio
should be below 50 percent and ideally below
25 percent. Shopping for the best mortgage
rate, often recommended by housing counselors, may have the unintended consequence
of generating too many credit history inquiries
and lowering the credit score.
Credit scoring frees up more time for underwriters to
deal with applicants that have credit issues, but policies regarding marginal credit risk applicants may be
inadequate or not observed uniformly.
It is difficult to dispute the position that credit
scoring has made the mortgage underwriting
process more efficient. The key question is: Do
similarly situated majority and minority (marginal)
applicants receive the same levels of assistance,
have similar accept/decline rates, and are their
loans priced similarly? A fair response might be
that the policy for dealing with marginal applicants is not really a credit scoring issue, but strictly
a compliance and/or policy issue. However, the
score reflects both accurate and inaccurate information contained in the credit report. To the
extent some applicants receive assistance and
others do not, and if there is a high degree of
reliance on the credit score in the credit and/or
pricing decision, it may not be appropriate to
separate the discussions completely.
Despite claims to the contrary, many lenders rely
heavily, if not entirely, on the credit score in making
the credit decision.
Consumer advocates argue that an applicant may
have a marginal credit score for reasons other
than those the credit score accurately reflects, or
that would not logically have a casual relationship with default. As an example, households
lacking established credit with at least one mainstream credit product, such as a bank credit card,
would tend to score poorly even if rent and any
(non-traditional) credit accounts are current.

Even the most ardent proponents of credit scoring
concede that it is not a perfect tool, but maintain
that it is a fast, generally accurate tool for assessing credit risk. Credit scoring models offered by
responsible model developers are continually
refined using increasingly large populations of
borrowers, both good and bad credit risks, to
ensure and improve the predictive ability of
scores and fairness of models generally. Some
examples noted by our respondents of factors
that might give rise to disparities cited during
the series, such as past use of a finance company,
medical collections, or frequent/multiple credit
inquiries, among others, have been eliminated
as factors from many scoring models. Further,
the industry has shown a clear intent to ensure
that models are consistent with provisions of
the Equal Credit Opportunity Act.

Many thanks go to the respondents that contributed
to the articles—they brought a diversity of perspectives on this complex and controversial subject.
The Mortgage Credit Partnership Credit Scoring
Committee’s goal is to raise awareness about the fair
lending implications of credit scoring. We hope the
dialogue we have started will endure as the use of
credit scoring increases.
Mortgage Credit Partnership
Credit Scoring Committee
The Committee comprised Community Affairs
representatives from the Federal Reserve Banks of
Boston, Chicago, Cleveland, San Francisco, and
St. Louis and the Board of Governors of the Federal
Reserve System. The Committee was chaired by
Michael V. Berry, Federal Reserve Bank of Chicago.
We hope you have found the series to be informative and enlightening. We invite your comments
to our e-mail box at CCA-PUBS@chi.frb.org.

ILLINOIS LAUNCHES NEW
ANTI-PREDATORY LOAN PROGRAM
By Harry Pestine, Illinois Community Affairs Program Director, Federal Reserve Bank of Chicago

In an effort to help Illinois families avoid falling
victim to predatory lenders, Illinois State Treasurer
Judy Baar Topinka announced on June 18, 2002, a
new statewide program to help people buy a home
or keep their home from being foreclosed.

but this new program provides financial institutions
with an incentive to consider offering conventional
loans to less conventional borrowers without putting
themselves at unnecessary risk.”

In addition to helping families purchase a home,
the program also helps those individuals who have
“Our new program titled, Our Own Home,
missed a couple of mortgage payments but
will help many middle- to lower-income
n
w
H
O
o
families achieve the American
me have resumed making their payments.
r
Ou
dream of home ownership without
“Too many people have found themthe nightmares caused by predatory
selves in a situation where they
lenders,” Topinka said. “Through
become easy targets for lenders who
Our Own Home, we’re working
loan
money under unfair loan terms
with financial institutions across
A
and at outrageous interest rates and
the state to help people overcome
Pa
th
r
r
o
then
when payments are missed, the
t
f
A m n ership
their credit problems, get the finanm
a
e
original loan is refinanced at even higher
r i c a n D re
cial help they need and settle into
interest
rates,” Topinka explained. “This
their own homes. These institutions are
vicious cycle can often end up leaving you with a
helping families overcome credit problems
shattered credit history and losing your home.”
by offering conventional loans to less than conventional borrowers.”
Participating banks would work with the borrower
to refinance their loan or extend an additional loan
“The program acts like a buying partner,” Topinka
for the amount of the arrearage.
explained. “We tell lenders that we’ll back up your
investment with funds from our program. Our
goal is to give lenders the reassurance they need to
make the loan.”
Our Own Home will pledge up to 10 percent of the
value of the loan to the bank as security for the borrower’s loan. The money is never actually given to
the bank; rather it stays in the Our Own Home Fund.
The bank would only receive the amount pledged if
the borrower defaults on the loan.
“We know there will always be individuals with less
than perfect credit who need access to capital for
things like home mortgages,” Topinka said. “Banks
take a greater risk in loaning money in these situations,

To qualify for the Our Own Home program, you
must be a homebuyer who does not qualify for a
conventional mortgage loan and your annual household income cannot exceed $75,000. Our Own Home
may only be used toward loans for single family homes
with an appraised value that does not exceed the
county’s median home value where the home is
located or $125,000, whichever is less.
For further information about how to sign up for the
program, call Jim Soreng, Manager Our Own Home
program, 312/814-1819, or 888/803-HOME, or check
the Illinois State Treasurer’s Web site at
www.ourownhome.net.

The Community Affairs Office of the
Federal Reserve Bank of St. Louis invites
you to SAVE THE DATE to attend its fall
conference on community development:

Jackie Joyner-Kersee Center
East St. Louis, Illinois
Registration materials will be sent this
summer. For more information, call Matt
Ashby at (314) 444-8891.

OCTOBER 22 AND 23, 2002

Cosponsored by the University of Illinois at Urbana-Champaign’s
East St. Louis Action Research Project

Livable Communities: Linking Community Development and Smart Growth

Save the Date for
Livable Communities:
Linking Community Development and Smart Growth
Location

Hyatt Regency, Cincinnati, Ohio
Reception

Wednesday, November 6 6 –7:30 p.m.
Conference

Thursday, November 7

8 a.m.– 5 p.m.

Full text of Profitwise News and Views (Federal Reserve Bank of Chicago) : Summer 2002

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