and Second-Review Process
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 where the use of credit scores may create disparities
in the home mortgage process. The first four installments in this series
addressed 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 topic of the fifth and final installment addresses
the use of counteroffers, overrides, and second reviews of credit-scored
decisions. We have solicited feedback from industry, consumer, and regulatory
representatives to ensure a variety of perspectives on these topics.
Contributors to this 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 that has been raised is that the objectivity of the credit
score is 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 lenders' 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, consistently applied 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:
- 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?
- What actions could lenders take to ensure counteroffers
are extended fairly?
- What measures and systems should be instituted
to ensure that the second review process is operating in a manner that
is consistent and fair?
- Describe steps the lenders could take to ascertain
the level of staff's compliance with its policies and procedures.
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 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.
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.
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 MBA 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,
co-authoring 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
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.
Kevin Stein is the associate director of the
California Reinvestment Committee, 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 for the Community
Economic Development Attorney at the East Palo Alto Community Law Project
and for HomeBase, a law and social policy center on homelessness. He is
a graduate of the Georgetown University Law Center and Stanford University.
Statement of Dan Immergluck
Grand Valley State University
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 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 remain more complex and mystifying
than pervious 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 been matched
by an equivalent investment in home buyer and home owner counseling resources.
Another larger issue posed by credit scoring is often
referred to as the problem of "paradigm shift" and has been
brought up more often in the context of safety and soundness concerns.
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
would diminish, thus becoming a less important determinant of repayment.
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
Turning now to the more specific problems of overrides
and counteroffers, there are a number of issues that lenders, regulators,
and advocates should be particularly concerned about. 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 risk-based 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 nonblank) that
engage in mortgage lending. If, for example, the bank affiliate tends
to make retail loans to white borrowers, and the non-bank 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.
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
Fifth Third Bank
Within predominately minority neighborhoods, subprime
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 near-prime-rate products. Thus, the proper
use of credit scoring should increase properly priced credit in all market
This series of articles on the use and monitoring of credit-scoring-based
origination programs 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.
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 illustration below provides a framework for discussing how strategic
orientation and fair lending compliance combine to generate more equitable
The most important phase of the origination process
is the establishment of a 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 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
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 line
employees who are responsible for lending and assistance programs. SDSI
establishes benchmarks and business objectives, creating top-down 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.
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 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.
An executive management 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 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
The combination of strategic focus through our BLITZ program, an aggressive
training program, and compliance audits have 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 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.
Statement of Kevin Stein
California Reinvestment Committee
The use of credit-scoring models to evaluate creditworthiness has become
widespread, even finding its way into the insurance arena, despite 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 various
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 creditworthy borrowers.
All of this leads us to wonder if the credit denials of any low-income,
immigrant, of color, or elderly 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 subprime 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 none other than 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, 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.
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 subprime and payday lenders. These borrowers
are in the subprime market because they and their neighborhoods have been
abandoned by mainstream banks and thrifts. A recent CRC study of subprime
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
subprime market could have qualified for prime loans. Using the subprime
market may lower one's credit score, essentially punishing those with
few real or perceived mainstream credit alternatives, many of whom have
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 middle-class 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 the mortgage. Instead, lenders should accept
alternate forms of credit, such as utility and rent payments, as evidence
of a borrower's creditworthiness.
The Need for Secondary
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 low-income 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, are 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.
Focus on compensating factors for low-side overrides. 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 subprime, 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 more
opportunity for applications to be treated differently, the more risk
of fair lending violations. Override authority should rest with a small
number of key staff.
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
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
low-income, elderly, and immigrant borrowers and borrowers of color. The
fact that half of all subprime 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 subprime 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. The Federal Reserve Board must help root out discrimination
in home lending more aggressively by enhancing Home Mortgage Disclosure
Act (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 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.
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.
Response of Michael LaCour-Little
Wells Fargo Home Mortgage
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 to make mortgage credit
more widely available to all households, including traditionally underserved
market segments, and it has helped to 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.
- 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
procedures to monitor the incidence of overrides to ensure they do not
favor or disfavor any class of loan applicant disproportionately.
- What actions could lenders take to ensure that
counteroffers are extended fairly?
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.
- 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 that are 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 outcomes of the second reviews 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.
- What steps lenders can take to ascertain the
level of staff's 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
Response of Stanley D. Longhofer
Wichita State University
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 bigotry 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
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
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 credit-access 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
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 characterizes 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 trade-offs 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 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 is 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 lower-income
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
manual underwriting. Thus, the techniques that 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 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
This installment concludes the five-part series of
articles on credit scoring and fair mortgage lending. Many thanks go to
the respondents that contributed to the articles-they brought a diversity
of perspectives on this complex and often controversial subject that was
enlightening and challenging.
The Mortgage Credit Partnership Credit Scoring Committee's
goal has been to raise awareness about the fair lending implications of
credit scoring. We hope the dialogue we have started will keep these issues
at the forefront 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 Berry, Federal Reserve Bank of Chicago.