Overrides 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:

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 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 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.

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 lending markets.

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 segments.

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 results.

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 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 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.

Summary
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 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

Introduction
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 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 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 Review

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 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 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.

Conclusion
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.

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 procedures to monitor the incidence of overrides to ensure they do not favor or disfavor any class of loan applicant disproportionately.
2. 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.
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 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.
4. 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 repeated violations.

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 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 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 access.

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.

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