The primary mortgage market features a variety of loan products and relies, in part, on the process of securitization to provide funds for mortgage lending. Over the years, a number of federal and state laws and regulations were implemented to protect mortgage borrowers. In 2007, the bill was introduced to strengthen consumer protections and included provisions that would have created a safe harbor for loans that met certain requirements. The primary mortgage market has several segments and offers a range of loan products: The prime market serves borrowers with strong credit histories and provides the most attractive interest rates and mortgage terms. The Alt-A market generally serves borrowers whose credit histories are close to prime, but the loans often have one or more higher-risk features, such as limited documentation of income or assets. The subprime market generally serves borrowers with blemished credit and features higher interest rates and fees than the prime market. Finally, the government-insured or -guaranteed market primarily serves borrowers who may have difficulty qualifying for prime mortgages but features interest rates competitive with prime loans in return for payment of insurance premiums or guarantee fees. HUD’s Federal Housing Administration (FHA) and the Department of Veterans Affairs (VA) operate the two main federal programs that insure or guarantee mortgages. Across all of these market segments, two types of loans are common: fixed-rate mortgages, which have interest rates that do not change over the life of the loans and adjustable-rate mortgages (ARM), which have interest rates that change periodically based on changes in a specified index. Other more unique loan products, referred to as nontraditional mortgage products, grew in popularity over the last decade (see table 1). Hybrid ARMs—which are fixed for a given period and then reset to an adjustable rate—also became popular in recent years, especially in the subprime market. In particular, a significant portion of subprime loans originated from 2003 through 2006 were 2/28 or 3/27 hybrid ARMs—that is, they were fixed for the first 2 or 3 years before resetting to often much higher interest rates and correspondingly higher mortgage payments. Other nontraditional mortgage products included interest-only or payment- option loans, which allowed borrowers to defer repayment of principal and possibly part of the interest for the first few years of the loan. A number of loan features also became more common over the past decade. While these features potentially expanded access to mortgage credit, they are often associated with higher default rates. These features included the following: Low and no-documentation loans. Originally intended for borrowers who had difficulty documenting income, such as the self-employed, these loans were made with little or no verification of a borrower’s income or assets. High loan-to-value (LTV) ratios. As homebuyers made smaller down payments, the ratio of loan amount to home value increased. Prepayment penalties. Some loans contained built-in penalties for repaying part or all of a loan in advance of the regular schedule. Many loans were originated with a number of these features, a practice known as risk layering. The secondary mortgage market and the process of securitization play important roles in providing liquidity for mortgage lending. Mortgage lenders originate and then sell their loans to third parties, freeing up funds to originate more loans. Securitization, in this context, is the bundling of mortgage loans into investment products called residential MBS that are bought and sold by investors. The secondary market consists of (1) Ginnie Mae-guaranteed MBS, which are backed by cash flows from federally- insured or -guaranteed mortgages; (2) government-sponsored enterprise (GSE) MBS, which are backed by mortgages that meet the criteria for purchase by Fannie Mae and Freddie Mac; and (3) private label MBS, which are backed by mortgages that do not conform to GSE purchase requirements because they are too large or do not meet GSE underwriting criteria. Investment banks have traditionally bundled most subprime and Alt-A loans into private label MBS, although since 2007, the market has slowed dramatically. The Truth in Lending Act (TILA), which was enacted in 1968, and the Home Ownership and Equity Protection Act of 1994 (HOEPA), which amended TILA in 1994, are among the primary federal laws governing mortgage lending. TILA was designed to provide consumers with accurate information about the cost of credit. Among other things, TILA requires lenders to disclose information about the terms of loans— including the amount financed, the finance charge, and the annual percentage rate (APR)—that can help borrowers understand the overall costs of their loans. Congress enacted HOEPA to amend TILA, in response to concerns about predatory lending. HOEPA regulates and restricts the terms and characteristics of certain kinds of high-cost mortgage loans that exceed certain thresholds in their APRs or fees (often referred to as “rate and fee triggers”). The Board of Governors of the Federal Reserve System (Federal Reserve) implements TILA and HOEPA through Regulation Z, which was amended in 2001 and 2008 with respect to high-cost lending. As a result of the most recent rulemaking in 2008, Regulation Z will restrict mortgage lending in the following ways, as of October 1, 2009: Higher-priced loans: First-lien loans with APRs that equal or exceed an index of average prime offer rates by 1.5 percentage points above an index of average prime offer rates—a category meant to include virtually all loans in the subprime market, but generally exclude loans in the prime market—are called “higher-priced mortgage loans.” Creditors are prohibited from making these loans without regard to the borrower’s ability to repay from income and assets other than the home’s value, and creditors must verify the income and assets they rely upon to determine a borrower’s repayment ability. Also, prepayment penalties are prohibited for these loans if the payment can change in the first 4 years of the loan; for loans where the payment is fixed for at least the first 4 years, prepayment penalties are limited to 2 years. In addition, creditors must establish escrow accounts for this category of loans for property taxes and homeowners’ insurance. High-cost HOEPA loans: First-lien loans with APRs that exceed the yield on Treasury securities of comparable maturity by more than 8 percentage points or with total points and fees that exceed the greater of 8 percent of the loan amount or $583, are called “high-cost HOEPA loans.” For these loans, the law restricts prepayment penalties, prohibits balloon payments (i.e., a large balance due at maturity of the loan term) for loans with terms of less than 5 years, prohibits negative amortization, and contains certain other restrictions on loan terms or payments. General provisions: For all loans, regardless of whether they fall into one of the above categories, Regulation Z includes a number of basic disclosure requirements and prohibits certain activities considered to be unfair, deceptive, misleading, abusive, or otherwise problematic, such as coercing a real estate appraiser to misstate a home’s value, and abusive collection practices by loan servicers. Each federal banking regulator is charged with enforcing TILA and HOEPA with respect to the depository institutions it regulates, and the FTC has responsibility for enforcing the statutes for mortgage brokers and most financial entities other than banks, thrifts, and federal credit unions. The Federal Reserve has concurrent authority to enforce T and HOEPA for non-bank subsidiaries of bank holding companie s. In addition to TILA and HOEPA, some other federal laws govern aspects of mortgage lending. For example, the Real Estate Settlement Procedures Act (RESPA), passed in 1974, seeks to protect consumers from unnecessarily high charges in the settlement of residential mortgages by requiring lenders to disclose details of the costs of settling a loan and by prohibiting kickbacks (payments made in exchange for referring a settlement service) and other costs. HUD has primary rule-writing authority and is responsible for enforcing RESPA. HUD coordinates on RESPA issues, as it deems appropriate, with federal banking regulators and other federal agencies, such as the FTC and the Department of Justice. In addition, the federal banking agencies, under section 8 of the Federal Deposit Insurance Act, examine for and enforce compliance with RESPA’s requirements with respect to the institutions they supervise. Finally, the Federal Deposit Insurance Act and Federal Credit Union Act allow federal banking regulators to use their supervisory and enforcement authorities to ensure that an institution’s conduct with respect to consumer protection laws does not affect its safety and soundness or that of an affiliated institution. In conjunction with enforcing federal statutes, federal banking regulators have issued guidance to their institutions—including federally-regulated banks, thrifts, credit unions, holding companies and their subsidiaries— about nontraditional and subprime lending. In September 2006, banking regulators issued final guidance clarifying how institutions can offer nontraditional mortgage products in a safe and sound manner, and in a way that clearly discloses the risks that borrowers may assume. The guidance provides specific steps institutions should take to help ensure that loan terms and underwriting standards are consistent with prudent lending practices, including considering a borrower’s repayment capacity; ensuring strong risk management standards, including capital levels; and ensuring that consumers have sufficient information to clearly understand loan terms and associated risks. In June 2007, banking regulators issued a final statement on subprime lending, in response to concerns about certain types of loans that could result in payment shock to borrowers. The statement warned institutions about risks associated with subprime loans with adjustable rates with low initial payments, based on fixed introductory rates that expire after a short period, limited or no documentation of income, prepayment penalties that were very high or that extended beyond the initial fixed rate period, and other product features likely to result in frequent refinancing to maintain an affordable monthly payment. In response to concerns about the growth of predatory lending over the past decade, many states have enacted laws to restrict the terms or provisions of certain types of mortgage loans. According to the Congressional Research Service, at least 30 states and the District of Columbia had enacted a wide array of such laws, as of November 2008. Many of these state laws are similar to HOEPA in that they regulate and restrict the terms and characteristics of certain kinds of high-cost mortgages exceeding certain interest rate or fee thresholds that require enhanced protections. Like HOEPA, these laws often restrict certain loan features that can, in certain cases, be abusive—such as prepayment penalties, balloon payments, negative amortization, and loan flipping—and many laws also require enhanced disclosures and credit counseling. While some laws are only minimally different than HOEPA, others are more comprehensive. Significant debate has taken place as to the advantages and disadvantages of state predatory lending laws. In several cases, regulators of federally supervised financial institutions have determined that federal laws preempt state predatory lending laws for the institutions they regulate. In making these determinations, two regulators—the Office of the Comptroller of the Currency (OCC) and Office of Thrift Supervision (OTS)—have cited federal law that provides for uniform regulation of federally chartered institutions and have noted the potential harm that state predatory lending laws can do to legitimate lending. Many state officials and consumer advocates are opposed to federal preemption of state predatory lending laws. They maintain that federal laws related to predatory lending are insufficient, and that preemption, therefore, interferes with their ability to protect consumers in their states. The first state predatory lending law, the North Carolina Anti-Predatory Lending Law of 1999, has been the subject of particular attention by researchers and policymakers. The law was more restrictive than HOEPA was at the time. Among other things, it banned prepayment penalties on all home loans with a principal amount of $150,000 or less, and prohibited loan flipping (refinancings of consumer home loans that do not provide a reasonable, net tangible benefit to the borrower). It included more restrictions for a category of high-cost loans, which were defined to include lower points and fee triggers than HOEPA, as well as a third trigger that included any loan with a prepayment penalty that could be collected more than 30 months after closing or that was greater than 2 percent of the amount paid. The U.S. House of Representatives passed H.R. 3915—the Mortgage Reform and Anti-Predatory Lending Act of 2007—on November 15, 2007, in response to significant increases in mortgage defaults and foreclosures, especially among subprime borrowers. Although the bill was passed by the U.S. House of Representatives, it was not enacted into law before the end of the 110th Congress. The bill would have reformed mortgage lending by, among other things, setting minimum standards for residential mortgage loans (see fig. 1). The two standards included: Reasonable ability to repay. The bill would have created a “reasonable ability to repay” standard by prohibiting a creditor from making a residential mortgage loan without making a determination based on verified and documented information that a consumer was likely to be able to repay the loan, including all applicable taxes, insurance, and assessments. Such a determination was to be based on the consumer’s credit history, current and expected income, obligations, debt-service-to- income (DTI) ratio, employment status, and financial resources other than any equity in the real property securing the loan. Additionally, the bill would have required lenders making ARMs to qualify borrowers at the fully indexed rate. However, the actual standard was to be prescribed in regulation by the federal banking agencies, in consultation with the FTC. Net tangible benefit. The bill would have created a “net tangible benefit” standard by prohibiting a creditor from refinancing a loan without making a reasonable good faith determination that the loan would provide a net tangible benefit to the consumer. The bill stated that a loan would not meet the standard if the loan’s costs exceeded the amount of newly advanced principal, without any corresponding changes in the terms of the refinanced loan that were advantageous to the consumer. However, the term “net tangible benefit” was to be defined in regulation by the federal banking agencies. The specific responsibilities of lenders to meet the standards, and the rights of consumers to take action against lenders to claim standards had not been met, depended on the category of the loan. Under the bill, loans are classified into three basic categories: Qualified mortgages would have had relatively low APRs, be insured by FHA, or made or guaranteed by VA. This category was intended to include most prime loans. Specifically, a loan would have been considered a qualified loan if either the APR was less than 3 percent above the yield on comparable Treasury securities, or less than 1.75 percent above the most recent conventional mortgage rate (a term that would have been more explicitly defined in regulation). For second-lien loans, the limits were 5 and 3.75 percent, respectively. Qualified mortgages would have been presumed under the law to meet the “ability to repay” and “net tangible benefit” standards, and for these loans, the creditor’s presumption could not be rebutted by borrowers. Qualified safe harbor mortgages would have fallen outside of the definition of qualified mortgages (i.e., would not have met this standard), but would have met certain underwriting requirements. This category was intended to include subprime loans that did not contain certain high-risk features. Specifically, these mortgages were required to (1) have full documentation, (2) be underwritten to the fully indexed rate, (3) not negatively amortize, and (4) have a fixed rate for at least 5 years, have a variable rate with an APR less than 3 percentage points over a generally accepted interest rate index, or meet a DTI ratio to be established in regulation. Qualified safe harbor mortgages, like qualified mortgages, would have been presumed under the law to meet the “ability to repay” and “net tangible benefit” standards. Unlike borrowers with qualified mortgages, however, borrowers with these mortgages would have had the right to challenge a creditor’s presumption that these loans met the “ability to repay” and “net tangible benefit” standards. Nonqualified mortgages would have fallen outside of the two definitions above (i.e., would not have met either standard). This category was intended to include subprime loans with high-risk features. For these loans, the law would have required lenders to meet the reasonable ability to repay and net tangible benefit standards, as well as provide borrowers with the ability to challenge such determinations by creditors and assignees. As shown in figure 1, the bill would also have imposed restrictions on specific loan terms, depending on the loan category. First, the bill would have prohibited prepayment penalties for loans that were not qualified mortgages and would have required the penalties on all qualified mortgages with an adjustable interest rate to expire 3 months before the initial interest rate adjustment. Second, negative amortization loans to first-time borrowers would have been prohibited, unless the creditor made certain disclosures to the consumer and the consumer had received homeownership counseling from a HUD-certified organization or counselor. Finally, single-premium credit insurance and mandatory arbitration on mortgage loans would have been prohibited for all loans. The bill would have established additional liability for creditors of qualified safe harbor and nonqualified mortgages (see fig. 1). In addition, it would have established limited liability for assignees of nonqualified mortgages. Borrowers would have been able to bring civil actions against creditors or assignees if loans violated the “reasonable ability to repay” or “net tangible benefit” standards. Creditors would have been liable for the rescission of a loan and the borrower’s cost associated with the rescission unless they could make the loan conform to minimum standards within 90 days. In addition, assignees would have been liable for the rescission (i.e., cancellation) of a loan and for borrower costs associated with the rescission unless the loan could be made to conform to the minimum standards within 90 days, or unless the assignee (1) had a policy against buying loans that were not qualified loans or qualified safe harbor loans, (2) exercised reasonable due diligence, as defined in regulation by the federal banking agencies and the SEC, and (3) had agreements with the seller or assignees of loans requiring that certain standards be met and certain steps be taken. The bill included additional provisions to resolve situations in which the parties could not agree on loan changes and set certain time frames for addressing challenges to these changes. Liability would not have been extended to pools of loans, including the securitization vehicles, or investors in pools of loans. According to the House Committee Report on the bill, it was not intended to apply to trustees or titleholders who held loans solely for the benefit of the securitization vehicle. The bill would also have expanded the definition of “high-cost” loans under HOEPA. Specifically, the bill would have included home purchase loans in the definition, reduced the points and fees trigger from 8 to 5 percent—the APR trigger would stay at 8—and expanded the definition of points and fees for high-cost mortgages. The bill would have also added a third high-cost trigger for loans with prepayment penalties that applied for more than 3 years or exceeded 2 percent of the prepaid amount. Further, the bill would have enhanced existing HOEPA restrictions on lending without repayment ability by presuming that creditors engaged in a pattern or practice of making high-cost mortgages without verifying or documenting consumers’ repayment ability were violating HOEPA. Finally, the bill would have established a federal duty of care for mortgage originators; prohibited steering of consumers eligible for qualified mortgages to nonqualified mortgages; established a licensing and registration regime for loan originators; established an Office of Housing Counseling within HUD and imposed additional counseling requirements; made changes to mortgage servicing and appraisal requirements; and provided protections for renters in foreclosed properties. We estimate that almost three-quarters of securitized nonprime mortgages originated from 2000 through 2007 would not have been safe harbor loans. The extent to which mortgages would have met the individual safe harbor requirements varied substantially by origination year, reflecting changes in market conditions and lending practices over the 8-year period. We also found that the proportions of safe harbor and non-safe harbor loans varied across different census tract and borrower groupings. Our statistical analysis of loan data shows that certain variables associated with the safe harbor requirements—documentation of borrower income and assets, in particular—were associated with the probability of a loan default. We found that other variables, such as house price appreciation and borrower credit score, were also associated with default rates. To illustrate the potential significance of the safe harbor requirements under different lending environments and market conditions, we applied those requirements to nonprime mortgages originated from 2000 through 2007 and calculated the proportions of loans that likely would and would not have met the requirements. Because of data limitations and uncertainty about how federal regulators would have interpreted some of the safe harbor requirements, our analysis includes a number of assumptions discussed in this section. (See appendix I for details about our methodology.) We estimate that almost 75 percent of nonprime mortgages originated from 2000 through 2007 would not have met the bill’s safe harbor requirements. More specifically, the estimated proportion of non-safe harbor loans ranged from a low of 58 percent for 2001 to a high of 84 percent for 2006 (see fig. 2). The non-safe harbor loans were primarily ARMs, while the safe harbor loans were largely fixed-rate mortgages. For all 8 years combined, Alt-A mortgages represented about 37 percent of non-safe harbor loans, or slightly more than the Alt-A share of the nonprime market over this period (35 percent). Over this same period, subprime mortgages comprised about 63 percent of non-safe harbor loans, or slightly less that their 65 percent share of the nonprime market. The significance of particular safe harbor requirements varied by origination year. As previously noted, the safe harbor requirements include the following: Documentation and amortization. The mortgage would have to be underwritten based on full documentation of the borrower’s income and assets and could not have a negative amortization feature. Interest rate and debt burden. The mortgage would be required to have either (1) a fixed interest rate for at least 5 years, (2) a DTI ratio within a level to be specified in regulation (we used the 41 percent ratio that serves as a guideline in underwriting FHA-insured mortgages), or (3) an ARM with an APR of less than 3 percentage points over a generally accepted interest rate index. Because the loan data we used did not include APRs, we instead compared the initial interest rate on each loan to the relevant interest rate index. Fully indexed rate. The mortgage would have to be underwritten to the fully indexed interest rate (which the bill defines as the initial interest rate index, plus the lender’s margin). We could not determine from the data we used whether a mortgage was underwritten to the fully indexed rate. We created a proxy by assuming that the mortgage satisfied this requirement if the fully indexed rate was 1 percentage point or less over the initial interest rate, indicating a reasonable likelihood that the borrower could have qualified for a loan underwritten to the fully indexed rate. As shown in figure 3, there was an increasing trend in the proportion of nonprime loans originated from 2000 through 2007 that would not have met the safe harbor documentation and amortization requirements. More specifically, the estimated percentages of nonprime loans without full documentation ranged from a low of 27 percent in 2000 to a high of almost 60 percent in 2007. Also, from 2004 through 2007, the proportion of nonprime loans with a negative amortization feature increased steadily. The growth in these percentages reflects the increased use of low- documentation mortgages in both the subprime and Alt-A markets and mortgages with negative amortization features (e.g., payment-option ARMs) in the Alt-A market. In both cases, these products were originally intended for a narrow population of borrowers but, ultimately, became more widespread. For example, as we reported in 2006, payment-option ARMs were once specialized products for financially sophisticated borrowers who wanted to minimize mortgage payments to invest funds elsewhere or borrowers with irregular earnings who could take advantage of minimum monthly payments during periods of lower income and could pay down principal when they received an increase in income. However, according to federal banking regulators and a range of industry participants, as home prices increased rapidly in some areas of the country, lenders began marketing payment-option ARMs as affordability products and made them available to less creditworthy and lower income borrowers. borrowers. Substantial proportions of the nonprime loans made over the 8-year period we examined also did not meet the safe harbor interest rate and debt burden requirements, although the proportions varied by year: The proportion of nonprime originations that did not have a fixed interest rate for at least 5 years rose from 52 percent in 2000 to 64 percent in 2004 (see fig. 4). This increase can be attributed primarily to a shift in the Alt-A market away from fixed-rate mortgage products to adjustable-rate products. For example, in 2000 about 88 percent of Alt-A loans were fixed rate, but by 2004 this figure had dropped to about 38 percent. Beginning in 2005, the percentage of nonprime originations with adjustable rates began falling, reaching 37 percent in 2007. The decline was due in large part to a trend in the Alt-A market toward fixed-rate mortgages. As figure 4 also shows, the proportion of nonprime originations that did not have a DTI ratio under 41 percent grew over the 8-year period, rising from 43 percent in 2000 to 51 percent in 2006, although it fell slightly in 2007. The generally increasing trend is partly a result of house prices growing faster than borrowers’ incomes over the period and of lenders allowing borrowers to take out larger mortgages relative to their incomes. For example, from 2000 through 2006, average home prices grew by 38 percent nationally, while over the same period, average incomes grew by just 23 percent. Finally, the proportion of nonprime ARM originations with initial interest rates not less than 3 percentage points over a generally accepted interest rate index (3 percent test) ranged from a high of 96 percent in 2002 to a low of 48 percent in 2007 (see fig. 4). The changing proportions over time were largely due to movements in the interest rate indexes used to set ARM interest rates that affected the size of the gap between the initial rates and the index values. For example, when the 2-year Treasury constant maturity rate (a common interest rate index) dropped from 2000 through 2002, the proportion of nonprime ARMs that did not meet the 3 percent test rose. But when the 2-year Treasury rate rose from 2004 through 2006, the proportion declined sharply. The bill’s interest rate and debt burden requirements for safe harbor mortgages were structured so that a loan would only have to meet one of the three requirements. As a result, some loans could have met one of the requirements, but not one or both of the other requirements and still could have qualified as safe harbor loans. To illustrate, of the safe harbor loans that met the bill’s safe harbor requirements by having a fixed interest rate for 5 or more years, almost one-half would not have met the DTI ratio requirement, assuming the 41 percent ratio we used for our analysis. Some of the banking regulators we interviewed said that the DTI ratio was an important factor in assessing a borrower’s ability to repay a mortgage loan. They said that all borrowers should be required to meet some DTI ratio in order for their loans to be eligible for the bill’s safe harbor. Consistent with this view, H.R. 1728, which was passed by the House earlier this year, requires borrowers of safe harbor loans to meet a DTI ratio to be established by regulation. Over the 8-year period we examined, about 38 percent of the nonprime loans originated would not have met the safe harbor fully indexed rate requirement, although the proportions varied by year (see fig. 5). As previously noted, we assumed that if the fully indexed rate—that is, the index rate at origination plus the lender’s margin—was more than 1 percentage point above the initial interest rate, the mortgage did not meet the requirement. The variation by year largely reflected changes in the index used to determine the fully indexed rate. More specifically, during years in which a commonly used index such as the 6-month LIBOR was relatively high (e.g., 2000 and 2005 through 2006), a larger proportion of the nonprime loans would not have met the requirement because the fully indexed rate would have been well above the initial interest rate of the loan. In contrast, during years in which the index was low (e.g., 2001 through 2004), a greater proportion of loans would have met the requirement because the fully indexed rate would have been close to the initial rate. For example, in 2000, when the average 6-month LIBOR was 6.7 percent, the proportion of nonprime loans that did not meet the fully indexed rate requirement was 47 percent. In 2003, when the average 6- month LIBOR was 1.2 percent, the proportion was 9 percent. A potential shortcoming of this requirement is that many ARMs could meet this requirement when interest rates were low, but the mortgages could become unaffordable if interest rates were to rise and the borrower’s payments adjusted upward to reflect the higher rates. However, it may be difficult to design a more stringent fully indexed rate requirement to provide protection during low interest rate environments without possibly reducing the availability of ARMs during high interest rate environments. Prior research has indicated that nonprime lending occurred disproportionately in areas with higher proportions of minority, low- income, and credit-impaired residents. Therefore, in contemplating the potential impact of the Bill, one consideration is the extent to which nonprime mortgages made to these groups of borrowers would have fallen inside or outside of the safe harbor. For groups with higher proportions of non-safe harbor mortgages, the Bill’s impact on the availability of these loans and consumer protections for them may be particularly important. Accordingly, we examined the estimated proportions of safe harbor and non-safe harbor loans within various zip code and borrower groupings. Specifically, we looked at zip codes grouped by race, ethnicity, and income characteristics, as well as borrowers grouped by credit score. Our analysis of safe harbor and non-safe harbor loans by race and ethnicity groupings found that zip codes with higher percentages of households that Census identified as black or African-American had lower percentages of non-safe harbor loans than the nonprime borrower population as a whole. For example, in zip codes where black or African- American households made up 75 percent or more of the household population, the proportion of non-safe harbor loans was 68 percent, compared with 75 percent for all nonprime borrowers (see table 2). In contrast, in zip codes with higher percentages of households that Censusidentified as Hispanic or Latino, the percentages of non-safe harbor loanswere higher than for nonprime borrowers as a whole. For example, in zip codes where Hispanic or Latino households comprised 75 percent or mor of the household population, the percentage of non-safe harbor loans was 80 percent, or 5 percentage points higher than for all nonprime borrowers. of non-safe harbor loans for each grouping was essentially the sam that for the entire nonprime borrower population. Prior research has shown that a number of different loan, borrower, and economic variables influence the performance of a loan. To see if the bill’s provisions appear to fulfill their consumer protection purpose, we developed a statistical model, based on the data available to us, to examine the relationship between safe harbor requirements, as well as a subset of other variables known to affect performance, and the probability of a loan defaulting within the first 24 months of origination. We defined a loan as being in default if it was delinquent by at least 90 days, in the foreclosure process (including loans identified as in real-estate-owned status), paid off after being 90 days delinquent or in foreclosure, or had already terminated with evidence of a loss. We focused on 24-month performance because a large proportion of nonprime borrowers—particularly those with hybrid ARMs—prepaid their loans (e.g., by refinancing) within 2 years. Using a 24-month time frame allowed us to include these loans in our model. The variables we used in the model included variables based on the individual safe harbor requirements, house price appreciation, borrower credit scores, and LTV ratios. We developed the model using data on nonprime mortgages originated from 2000 through 2006 (the latest year for which we could examine 24-month performance). We produced separate estimates for four types of loan products: (1) short-term hybrid ARMs (i.e., 2/28 or 3/27 mortgages), which accounted for 54 percent of the loans originated during this period; (2) longer-term ARMs (i.e., ARMs with interest rates that were fixed for 5, 7, or 10 years before adjusting), which accounted for 10 percent of originations; (3) payment-option ARMs, which represented 6 percent of originations and (4) fixed-rate mortgages, which represented 30 percent of originations. Appendix II provides additional information about our model and estimation results. Consistent with the consumer protection purpose of the bill’s provisions, we found that two safe harbor variables were associated with the probability of default. Across all product types, the safe harbor variable with the largest estimated influence on default probability was documentation of borrower income and assets. For example, less than full documentation was associated with a 5.5 percentage point increase in the estimated probability of default for short-term hybrid ARMs used for home purchases, all other things being equal (see table 4). The corresponding increases in estimated default probabilities for longer-term ARMs, payment-option ARMs, and fixed-rate mortgages were 4.8 percent, 2.0 percent, and 4.6 percent, respectively. The higher default probabilities associated with no- and low-documentation loans may reflect use of this feature to overstate the financial resources of some borrowers and qualify them for larger, potentially unaffordable loans. Our results are generally consistent with prior research showing an association between a lack of documentation and higher default probabilities. A second safe harbor variable that had a significant influence on default probability was the variable representing the difference between the loan’s initial interest rate and the relevant interest rate index (the spread). As previously noted, ARMs with a difference of 3 percentage points or more over a generally accepted interest rate index would not meet one of the bill’s safe harbor interest rate and debt burden requirements. To examine the effect of this variable for each product type, we estimated the default probability assuming the spread was near the 25th percentile (base assumption) for that product and compared this with the estimated default probability assuming the spread was near the 75th percentile (alternative assumption) for that product. We estimated that for short-term hybrid ARMs used for home purchases, moving from the lower spread to the higher one was associated with a 4.0 percentage point increase in default probability, all other things remaining equal (see table 5). The corresponding increases in estimated default probabilities for longer-term ARMs and fixed-rate mortgages were 1.8 percent and 2.6 percent, respectively. These results were generally consistent with other economic research showing a positive relationship between higher interest rates and default probabilities for nonprime mortgages. This relationship may reflect the higher monthly payments associated with higher interest rates and difficulties borrowers may face in making these payments, particularly during times of economic hardship. We also estimated the effect of the DTI ratio at origination and found that for all product types, this variable did not have a strong influence on the probability of default within 24 months. This relatively weak association may be due, in part, to changes in borrower income or indebtedness after loan origination. For example, a mortgage that is affordable to the borrower at origination may become less so if the borrower experiences a decline in income or takes on additional nonmortgage debt. Finally, we estimated the effect of the proxy variable we developed for the safe harbor requirement that loans be underwritten to the fully indexed rate. As previously noted, if the fully indexed rate was 1 percentage point or less over the initial interest rate, we assumed the loan met this requirement. For all product types, we found that this variable did not have a strong influence on the probability of default within 24 months (see app. II). It is possible that other model specifications—such as examining default probabilities beyond 24 months—would have yielded different results. For example, the difference between the initial interest rate and the fully indexed rate might have been more significant using such an alternative specification because the initial interest rates for many short- term hybrid ARMs begin adjusting upward after 24 months. In examining the influence of safe harbor variables on the probability of default within 24 months, we controlled for other variables not associated with the safe harbor requirements, such as house price appreciation, borrower credit score, and the LTV ratio. Because these variables have been shown to influence default probabilities, it was important to control for their effects in order to properly analyze the implications of the safe harbor provisions. Consistent with other economic research, we found that house price appreciation, borrower credit score, and the LTV ratio were strongly associated with default probabilities. The estimated influence of these variables on default probabilities for each product type were as follows: House price appreciation. We found that lower rates of house price appreciation were associated with a higher likelihood of default. For each product type, we estimated the default probability assuming house price appreciation near the 75th percentile for that product (base assumption) and compared this with the estimated default probability assuming house price appreciation near the 25th percentile for that product (alternative assumption). For short-term hybrid ARMs used for home purchases, moving from the higher rate of appreciation to the lower rate was associated with a 13.5 percentage point increase in estimated default probability (see fig. 6). The corresponding figures for longer-term ARMs, payment-option ARMs, and fixed-rate mortgages were 3.7 percent, 1.3 percent, and 3.5 percent, respectively. Borrower credit score. We found that lower credit scores were associated with a higher likelihood of default. For each product type, we estimated the default probability assuming a borrower credit score close to the 75th percentile for that product (base assumption) and compared this with the estimated default probability assuming a borrower credit score close to the 25th percentile for that product (alternative assumption). For short- term hybrid ARMs used for home purchases, moving from the higher credit score to the lower one was associated with a 7.3 percentage point increase in the estimated default probability (see fig. 6). For longer-term ARMs, payment-option ARMs, and fixed-rate mortgages, the corresponding figures were 3.3 percent, 2.1 percent, and 5.5 percent, respectively. LTV ratio. We found that higher LTV ratios were associated with higher probabilities of default. For each product type, we estimated the default probability assuming a LTV ratio close to the 25th percentile for that product (base assumption) and compared this with the estimated default probability assuming a LTV ratio close to the 75th percentile for that product (alternative assumption). For short-term hybrid ARMs used for home purchases, moving from the lower ratio to the higher ratio was associated with a 4.4 percentage point increase in the estimated default probability (see fig. 6). The corresponding figures for longer-term ARMs, payment-option ARMs, and fixed-rate mortgages were 4.7 percent, 6.3 percent, and 3.7 percent, respectively. While some research indicates that anti-predatory lending laws can reduce originations of problematic loans without overly restricting credit, research on state and local anti-predatory lending laws and the views of mortgage industry stakeholders do not provide a consensus view on the potential effects of the bill. The state and local anti-predatory lending laws we reviewed are, in some ways, similar to the bill, but the results of the research on these laws may have limited applicability to the bill for a number of reasons. Mortgage industry and consumer group representatives we interviewed disagreed on the bill’s potential effect on credit availability and consumer protections. For example, mortgage industry representatives said that the safe harbor and assignee liability provisions were too stringent and would restrict and raise the cost of mortgage credit. In contrast, consumer group representatives indicated that the provisions were not strong enough to prevent predatory lending and, thereby, protect borrowers. Several studies have examined the impact of state and local anti-predatory lending laws on subprime mortgage markets. Our review of eight such studies found evidence that anti-predatory lending laws can have the intended effect of reducing loans with problematic features without substantially affecting credit availability, but also that it is difficult to generalize these findings to all anti-predatory lending laws or to the potential effect of the bill. The studies we reviewed fell into two broad categories: those that focused solely on the North Carolina law and those that examined laws in multiple states and localities. In general, the researchers measured the effect of the laws in terms of the volume of subprime originations, the probability of originating a subprime loan, or the probability of originating a loan with predatory characteristics. The three studies on the North Carolina law (which was implemented in phases beginning in October 1999 and ending in July 2000) concluded that the law had a dampening effect on subprime originations in that state, but one found that the drop occurred primarily in the types of loans targeted by the law. For example, using data from nine subprime lenders and controlling for a number of demographic and housing market variables, Elliehausen and Staten estimated that subprime originations fell by 14 percent after the law was first implemented. A second study by Quercia, Stegman, and Davis that used an LP data set with broader coverage and used neighboring states as a control group, found that subprime originations declined 3 percent after the law was fully implemented and that subprime originations in four neighboring states without similar laws rose over the same period. Importantly, the authors also determined that 90 percent of the decline in subprime originations resulted from a decrease in refinance loans with one or more “predatory” characteristics, such as prepayment penalties lasting 3 years or more, balloon payments, or LTV ratios over 110 percent. Finally, a study by Burnett, Finkel and Kaul, which used Home Mortgage Disclosure Act (HMDA) data and also used neighboring states as a control group, found a 0.2 percent increase in subprime originations in North Carolina after implementation of the law. Like the Quercia study, the study by Burnett and others concluded that subprime refinance loans fell sharply in North Carolina over the period examined and that states neighboring North Carolina experienced higher percentage increases in total subprime originations. Additionally, the study noted that the volume of subprime originations in North Carolina fell in census tracts that were more than 50 percent minority but rose in other areas. The five studies that examined multiple state and local anti-predatory lending laws found mixed results but provide insights into the importance of the specific attributes of the laws. For example, using HMDA data, Ho and Pennington-Cross calculated the percentage change in subprime originations in 10 states with anti-predatory lending laws over periods that captured each state’s experience before and after the laws were passed. They compared the changes they found with the corresponding changes during the same periods in a control group of neighboring states without such laws. They found that in 5 of the 10 states (including North Carolina) with anti-predatory lending laws, subprime originations increased less than in the control group, but that in the other 5 states, subprime originations increased more. In another study, Ho and Pennington-Cross developed a legal index to measure the coverage and restrictions of anti- predatory lending laws, and examined how laws in 25 states and 3 localities affected the probability of originating a subprime loan. They found that, controlling for other factors, anti-predatory lending laws can increase, decrease, or have no effect on the flow of mortgage credit. Specifically, they found that: laws with broader coverage (i.e., those affecting a larger portion of the market) increased the estimated likelihood of subprime originations; those with greater restrictions (i.e., those with stricter limits on high-risk loan features) decreased the estimated likelihood of subprime originations; and in some instances, these two effects appeared to cancel each other out. As a result, they noted that the design of the law can have an important impact on the availability of credit in the subprime market. For example, the authors hypothesized that the effect of broader coverage may result from borrowers being more comfortable applying for a mortgage where there is a law to protect them from predatory loans. A study by Bostic and others built on this research by refining the legal index previously discussed, adding an enforcement dimension to the index, and examining a larger set of laws. The study confirmed the earlier findings regarding the impact of the coverage and restriction provisions of anti-predatory lending laws on the subprime market. Additionally, this study found that the strength of a law’s enforcement provisions (e.g., the extent of potential liability for assignees) was not associated with changes in the estimated likelihood of subprime originations. Li and Ernst examined anti-predatory lending laws in 33 states and used LP data on subprime mortgages made from January 1998 through March 2005 to examine the impact of these laws on the origination of loans with predatory features and the cost of subprime credit. They concluded that state anti-predatory lending laws that provided greater consumer protections than HOEPA had the intended effect of reducing subprime mortgages with predatory features. They also concluded that such laws did not lead to any systematic increase in costs to consumers. Pennington- Cross and Ho also examined the impact of predatory lending laws on the cost of subprime credit by reviewing anti-predatory lending laws in 24 states and analyzing HMDA and LP data from 1998 through 2005. They concluded that these laws resulted in, at most, a modest increase to consumers’ cost of borrowing. Although the bill is, in some ways, similar to the state and local laws analyzed in these studies, the results of these studies may have limited applicability to it, for a number of reasons. First, the legal indexes used by some researchers to assess the impact of state and local laws are based on an older set of laws that are similar to HOEPA. According to one of these researchers, the indexes do not take into account a newer generation of laws that, like the bill, have different thresholds and restrictions and cover products that were previously not common in the marketplace (e.g., low- and no-documentation loans). As a result, evaluating the bill, using these analytical tools, could be problematic. Additionally, the impact of a federal law could be different than the effects of state and local laws. For example, lenders or assignees may choose to exit a state or local market rather than comply with that jurisdiction’s anti-predatory lending law but still conduct business in other markets. However, under a federal law, these entities would not have that option. Finally, prior studies examined the impact of laws during a relatively active period in the subprime lending market. If a law similar to the bill were to be passed in the near future, it would be implemented in the wake of a major contraction in the mortgage market that would likely affect the response of both the mortgage industry and consumers to new lending standards. Mortgage industry representatives and consumer groups we interviewed generally agreed that the bill would have little short-term impact on the mortgage market because of existing market conditions. However, they held different views on the long-term impact that key provisions in the bill would have on consumer access to affordable credit and protection from predatory lending practices. Representatives from both groups generally agreed that the bill would have very little impact on mortgage originations in the current financial environment because the overall primary market was highly constrained, with lenders tightening qualifications for all borrowers and the market for private label MBS virtually nonexistent. In addition, representatives from mortgage industry groups expected that the Federal Reserve’s revisions to Regulation Z could lessen the impact of the bill. Specifically, the groups stated that the revisions to Regulation Z would place lender requirements on nonprime loans that were similar to the bill’s safe harbor requirements. For example, both the Regulation Z revisions and the bill’s safe harbor require that borrowers obtaining loans with APRs over certain thresholds provide full documentation of income and assets and qualify for ARMs based on a monthly payment that takes into account scheduled interest rate increases. Mortgage industry representatives we interviewed generally viewed the bill’s safe harbor requirements as overly restrictive and said that these requirements would reduce mortgage options and increase the cost of credit for certain borrowers. Some of these representatives said that lenders would be unwilling to make loans that did not meet the safe harbor requirements. They cited the experience with HOEPA as an example of what might take place if the safe harbor requirements were put in place. Specifically, they noted that since the implementation of HOEPA, very few lenders have been willing to make mortgages considered “high cost” loans under HOEPA’s provisions because they cannot sell them to the secondary market. For example, in 2006, less than 1 percent of mortgages were high cost loans, as defined by HOEPA regulations. The industry representatives also said that specific safe harbor requirements would reduce access to credit for certain types of borrowers. For example, they said that the safe harbor requirement that would prohibit loans with less than full documentation of income and assets could restrict access to credit for borrowers with irregular income streams, such as some small business owners. Some industry representatives acknowledged that many low- and no-documentation mortgages should not have been made, but said that some flexibility should be allowed under this requirement to account for borrowers with nontraditional sources of income. In addition, industry representatives said that borrowers who had responsibly used negative amortization loans in the past could face limited mortgage options under the bill, as the safe harbor requirement would prohibit these loans. Some industry representatives acknowledged that negative amortization products had been used inappropriately in recent years to allow some borrowers to buy homes that they might not have been able to afford, but added that prohibiting this feature would adversely impact borrowers who had used this product responsibly. For example, some borrowers with irregular income have taken out negative amortization loans in order to pay minimum amounts when their income was low and higher amounts when their income increased. One mortgage industry participant suggested that one way to address concerns that these loans subject borrowers to payment shock would be to limit the amount by which the mortgage payments could reset. In contrast, representatives from consumer groups that we interviewed generally indicated that the safe harbor requirements would need to be strengthened and applied to a broader range of loans in order to prevent predatory lending practices to protect borrowers. For example, some representatives supported adding more consumer protection features to the bill, such as prohibiting prepayment penalties, balloon payments, and yield spread premiums. They also said that the bill’s safe harbor requirements should be applied to all mortgages, including FHA-insured mortgages and loans with relatively low APRs, because these loans could also contain predatory features. Most of the consumer group representatives said that strengthening safe harbor requirements and applying them more broadly would not significantly affect the cost or availability of credit. For example, in response to industry concerns that requiring full documentation would restrict some borrowers’ access to credit, consumer group representatives noted that full documentation had already become a marketplace standard. They generally believed that the majority of borrowers, including self-employed consumers, could provide sufficient documentation using their income tax records, but some groups supported limited flexibility in the types of documents that would be accepted. In addition, while industry groups were concerned that prohibiting loans with a negative amortization feature under the bill’s safe harbor provisions could restrict credit to some borrowers, consumer groups supported prohibiting this feature in order to protect consumers from potential payment shock. Some of these representatives acknowledged that negative amortization loans could be suitable for certain borrowers, but they viewed these cases as exceptional and did not think the potential benefits to a small segment outweighed the potential costs to the larger portion of the market. Mortgage industry representatives we interviewed generally said that the bill’s assignee liability provisions would increase the cost of credit for borrowers and deter secondary market participants from reentering the nonprime market. Specifically, these representatives said that the cost of complying with the bill’s assignee liability provisions, including secondary market participants’ cost of due diligence procedures, would increase the cost of credit and cause some secondary market participants to stop securitizing loans. Some industry representatives stated that mortgage originators were better positioned to conduct due diligence to ensure that loans were responsibly underwritten and argued that mortgage reform legislation should focus on enhancing the primary market’s underwriting standards. Mortgage industry representatives also said that lack of certainty in what assignees could be held liable for under the bill would deter participants from reentering the secondary market. For example, some representatives noted that the bill did not clearly define the standards that assignees would be held to, such as “ability to repay” and “net tangible benefit.” They cited Georgia’s 2002 anti-predatory lending law as an example of how the lack of clarity concerning assignee liability could adversely impact the market. As we have reported, because of the uncertainty surrounding potential liability under the Georgia law, secondary market participants withdrew from the mortgage market in Georgia until the provisions were repealed. In contrast, consumer group representatives generally believed that enhanced regulation and accountability in the secondary market would provide consumers with greater protections against predatory lending practices. These representatives generally supported strengthening the bill’s assignee liability provisions. For example, some consumer group representatives said that the bill’s assignee liability provisions should not allow for any exemptions from liability, such as allowing assignees to cure a loan (i.e., modify or refinance the loan so that it meets the bill’s minimum lending standards) to avoid liability. They noted that some assignees might choose to cure the relatively few loans that violate the bill’s minimum lending standards, rather than invest the resources in due diligence policies and procedures that would help prevent predatory lending practices. Further, consumer groups said that the bill should not preempt state assignee liability laws because these laws could potentially provide consumers with an ability to seek redress if they obtain a predatory loan. Finally, representatives of consumer groups also said that applying the assignee liability provisions more broadly, beyond the bill’s nonqualified mortgages, could also help prevent predatory lending on a wider variety of mortgages. They contended that stronger and broader assignee liability provisions would not significantly impact the cost of or access to credit and would set a standard to which secondary market participants would eventually adapt. Mortgage industry representatives preferred that any federal legislation on mortgage lending preempt all state anti-predatory lending laws, not just assignee liability laws, in order to reduce the cost of and increase the availability of credit. They stated that a uniform set of mortgage standards for lenders would significantly reduce the cost of doing business and that these savings could be passed on to consumers. According to one mortgage industry participant, under the current legal and regulatory environment, lenders’ costs are higher because lenders are required to develop systems to track laws and regulations in up to 50 states, monitor these laws and regulations, and ensure they are in compliance with them. Some industry representatives stated that federal preemption could also lower consumer costs by applying uniform standards and supporting competition between state- and federally licensed mortgage originators. Mortgage industry representatives also said that full federal preemption would provide a uniform set of standards that would renew activity in the secondary market, thereby, allowing lenders to make more credit available to consumers. In contrast, consumer group representatives generally believed that federal legislation should not preempt state laws, because consumers benefited from states’ abilities to enact stronger consumer protection laws. For example, some consumer groups said that in the past, states had responded faster to predatory lending abuses than federal regulators in enacting anti-predatory lending laws, and expected this to continue if a federal bill did not preempt state laws. Further, some of these representatives said that state and federal regulations existed in a complementary framework in other areas, such as civil rights and the environment, and generally did not think that compliance costs would be significant in light of the benefits to consumers and the long-term sustainability of the mortgage market. They viewed states’ experimentation with mortgage reform as an important source of useful information on changes in market conditions and industry responses to different approaches. We provided a draft of this report to the Board of Governors of the Federal Reserve System, Federal Deposit Insurance Corporation, Office of the Comptroller of the Currency, Office of Thrift Supervision, National Credit Union Administration, Department of Housing and Urban Development, Federal Trade Commission, and Securities and Exchange Commission. We received written comments from NCUA, which are summarized below. Appendix III contains a reprint of NCUA’s letter. The Federal Reserve, FDIC, OCC, HUD, and FTC provided technical comments, which we incorporated into this report, where appropriate. In its written comments, NCUA reiterated several of our findings and noted that the findings supported its view that ensuring borrowers have a reasonable ability to repay is in the best interest of credit unions and their members. We are sending copies of this report to the Ranking Member, House Financial Services Committee and other interested parties. We will also send copies to the Federal Reserve, FDIC, OCC, OTS, NCUA, HUD, FTC, and SEC. The report also will be available at no charge on the GAO Web site at http://www.gao.gov. If you or your staff have questions about this report, please contact me at (202) 512-8678 or shearw@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs are on the last page of this report. GAO staff who made major contributions to this report are listed in appendix IV. Our objectives were to (1) assess the proportion of recent nonprime loans that would likely have met and not met the Mortgage Reform and Anti- Predatory Lending Act of 2007’s (bill) safe harbor requirements, and how variables associated with those requirements affect loan performance; and (2) discuss relevant research and the views of mortgage industry stakeholders concerning the potential impact of key provisions of the bill on the mortgage market. The scope of our analysis was limited to the nonprime mortgages. To assess the proportions of nonprime loans originated from 2000 through 2007 that would likely have met and not met the bill’s safe harbor requirements, we analyzed data on subprime and Alt-A (nonprime) mortgages from that period. Specifically, we analyzed information from LoanPerformance’s (LP) Asset-backed Securities database, which contains loan-level data on nonagency securitized mortgages in subprime and Alt-A pools. About three-quarters of subprime mortgages were securitized in recent years. For purposes of this report, we defined subprime loans as mortgages in subprime pools and Alt-A loans as mortgages in Alt-A pools. The LP database covers the vast majority of mortgages in nonagency subprime and Alt-A securitizations. For example, for the period 2001 through July 2007, the LP database contains information covering (in dollar terms) an estimated 87 percent of securitized subprime loans and 98 percent of securitized Alt-A loans (see table 6). Nonprime mortgages that were not securitized (i.e., mortgages that lenders held in portfolio) may have different characteristics and performance histories than those that were securitized. For our analysis, we used a random 2 percent sample of the database that amounted to almost 300,000 loans for the 2000 through 2007 period. Our sample included purchase and refinance mortgages and loans to owner- occupants and investors, and excluded second-lien mortgages. We assessed the reliability of the data by interviewing LP representatives about the methods they use to collect and ensure the integrity of the information. We also reviewed supporting documentation about the database, including LP’s estimates of the database’s market coverage. In addition, we conducted reasonableness checks on the data to identify any missing, erroneous, or outlying figures. We found the data elements we used to be sufficiently reliable. To estimate the proportion of loans that likely would have met and not met the safe harbor requirements, we used variables in the LP database that directly corresponded with the requirements and developed proxies when the database did not contain such variables (see table 7). To compare the demographic characteristics (e.g., race, ethnicity, and income level) of safe harbor and nonsafe harbor loans, we incorporated data from the Census Bureau. More specifically, whenever possible, we linked the zip code for each loan reported in the LP data to an associated census tract in a metropolitan statistical area (MSA). We grouped the zip codes according to the percentage of households that Census identified as black or African-American and Hispanic or Latino. The groupings in our analysis were: (1) less than 5 percent, (2) 5 to 24 percent, (3) 25 to 74 percent, and (4) 75 percent or greater of household populations. We also grouped zip codes according to the median income of the MSA of a given zip code. The specific groupings in our analysis were low-, moderate-, and upper-income zip codes, defined as those with median incomes that were less than 80 percent, at least 80 percent but less than 120 percent, and 120 percent and above, respectively, of the median income for the associated MSA. To analyze nonsafe harbor loans by borrower credit score, we used the FICO scores in the LP database. FICO scores, generally based on software developed Fair, Isaac and Company, are a numerical indicator of a borrower’s creditworthiness. The scores range from 300 to 850, with higher scores indicating a better credit history. For our analysis, we used 4 ranges of scores: 599 and below, 600 to 659, 660 to 719, and 720 and above. To examine factors affecting the performance of nonprime loans, we developed an econometric model to estimate the relationship between variables associated with the safe harbor requirements, as well as other variables, and the probability of a loan defaulting within 24 months of origination. We developed the model using data on mortgages originated from 2000 through 2006 (the latest year for which we could examine 24- month performance). Detailed information about our model and our estimation results are presented in appendix II. To describe relevant research on the bill’s potential effect on the mortgage market, we identified and reviewed empirical studies on the impact of state and local anti-predatory lending laws on key nonprime mortgage indicators, such as subprime mortgage originations and the cost of credit. While we identified a number of such studies, we narrowed our scope to eight studies that used control groups (e.g., comparison states without anti-predatory lending laws) or statistical techniques that controlled for factors other than the laws that could affect lending patterns. The studies we reviewed fell into two broad categories: three studies that focused solely on North Carolina’s 1999 anti-predatory lending law and five that examined laws in multiple states and localities. In general, the researchers measured the effects of the laws in terms of the volume of subprime originations, the probability of originating a subprime loan, or the probability of originating a loan with predatory characteristics. Our review of these eight studies included an examination of the methodologies used, the data and time periods used, the limitations of the studies, and the conclusions. We also interviewed selected authors to ensure that we interpreted their results correctly and to obtain their views on whether the results from their studies might apply to the potential impact of the bill on the mortgage market. To obtain the views of mortgage industry stakeholders, we reviewed written statements and congressional testimony about the bill by officials from the federal banking regulatory agencies and organizations representing mortgage lenders, mortgage brokers, securitizers, and consumer interests. We also interviewed officials from a number of these organizations, including the Mortgage Bankers Association, American Securitization Forum, American Financial Services Association, American Bankers Association, Independent Community Bankers of America, National Association of Mortgage Brokers, Center for Responsible Lending, National Community Reinvestment Coalition, National Consumer Law Center, Neighborhood Association of Consumer Advocates, and Consumer Federation of America. In addition, we interviewed officials from a large mortgage lender and a major investment bank involved in the securitization of mortgages. Finally, we interviewed officials from the federal banking regulatory agencies, the Department of Housing and Urban Development (HUD), the Federal Trade Commission (FTC), and the Securities and Exchange Commission (SEC). We conducted this performance audit from March 2008 to July 2009, in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives. This appendix describes the econometric model we developed to examine the relationship between variables associated with the bill’s safe harbor requirements, as well as other variables, and the probability of a loan entering default. Safe harbor requirements include features related to documentation of borrower income and assets, limits on debt-service-to– income (DTI) ratios, the duration before which any interest rate adjustments may occur, limits on the relationship between a loan’s annual percentage rate and other prevailing interest rates at origination, and prohibitions on mortgages that allow negative amortization. The safe harbor requirements limit features that may increase the risk of default, but they may also restrict the number and types of mortgages lenders are willing to originate. Since the requirements were not in effect during the recent past, we do not know in what ways lenders and securitizers may have responded to their introduction. Therefore, we characterize our evaluation as an assessment of whether mortgages with safe harbor characteristics performed better than those without them, as opposed to an assessment of the effects of the introduction of a safe harbor. Our investigation focused on a recent set of nonprime mortgages and controlled for a variety of loan, borrower, and housing market conditions that are likely to affect mortgage performance. To do this work, we analyzed a 2 percent random sample of securitized nonprime loans originated from 2000 through 2006 from LoanPerformance’s (LP) Asset-backed Securities database. Our sample was comprised of the approximately 92 percent of loans for which the associated property was located in an area covered by the Federal Housing Finance Agency’s house price indexes for metropolitan areas. The LP database has been used extensively by regulators and others to examine the characteristics and performance of nonprime loans. The database provides information on loan characteristics, from which we developed variables that indicated or measured relevant safe harbor requirements. We determined the status of each loan 24 months after the month of first payment. We used loan performance history through the end of December 2008. We defined a loan as being in default if it was delinquent by at least 90 days, in the foreclosure process (including loans identified as in real-estate-owned status), paid off after being 90-days delinquent or in foreclosure, or had already terminated with evidence of a loss. We categorized loans as follows: short-term hybrid adjustable rate mortgages (ARM) (essentially 2/28 and 3/27 mortgages), fixed-rate mortgages, payment-option ARMs, and other longer-term ARMs (i.e., ARMs with 5-, 7-, and 10-year fixed-rate periods). We included only first- lien loans for which the borrower is identified as an owner-occupant, and we estimated default probabilities for purchase money loans separately from loans for refinancing except for payment-option ARMs, for which we examined purchase and refinancing loans together. Our primary reason for examining performance by mortgage type is that borrower incentives and motivations may vary for loans with different characteristics. For example, short-term hybrid ARMs provide a strong incentive for a borrower to exit from a mortgage by the time the interest rate begins to reset. We estimated separate default models for each mortgage type, although the general underlying structure of the models was similar. We used a logistic regression model to explain the probability of loan default, based on the observed pattern of actual defaults and the values of safe harbor variables and a subset of other variables known to be associated with loan performance (see table 8). Many loan and borrower characteristics are likely to influence the status of a mortgage over time. Some factors describe conditions at the time of mortgage origination, such as the loan- to-value (LTV) ratio and the borrower’s credit score. Other important factors may change over time, sometimes dramatically, without being observed by a lender, loan servicer, or researcher. For instance, an individual household’s income may change due to job loss, increasing the probability of default. Other conditions vary over time in ways that can be observed, or at least approximated. For example, greater house price appreciation (HPA) contributes to greater housing equity, thus reducing the probability that a borrower, if facing financial distress, views defaulting on a loan as a better option than prepaying. We focused on whether a loan defaulted within 24 months as our measure of performance because a large proportion of nonprime borrowers had hybrid ARMs and prepaid their loans (e.g., by refinancing) within 2 years. Using a 24-month time frame allowed us to include these loans in our model, as well as loans originated in 2006, a year in which many nonprime loans were originated. For reasons described below, some of the variables associated with the safe harbor requirements are included in all four models, while others are only included in certain models: Full documentation of borrower income and assets: This variable is in all four models. Negative amortization feature: This variable is only in the model for longer-term ARMs. We did not include it in the models for the other mortgage types because the negative amortization feature was essentially never present (in the case of fixed-rate mortgages and short-term hybrid ARMs) or was essentially always present (in the case of payment-option ARMs). The lack of variation within these mortgage types made estimating the marginal effects of the negative amortization variable problematic. Fully indexed proxy: This variable is in three of the models, but we do not include it in the model for fixed-rate mortgages because it is only relevant to loans with adjustable interest rates. DTI ratio: In the context of the bill’s safe harbor requirements, this variable would only apply to short-term hybrid ARMs and payment-option ARMs. However, we include it in all four models because the DTI ratio is an important measure of the borrower’s ability to repay. Spread over relevant interest rate index: In the context of the bill’s safe harbor requirements, this variable would only apply to short-term hybrid ARMs. However, we include it in all four models because loans with higher interest rates may be at greater risk of default due to their higher monthly payments. Tables 9 through 12 provide information on the number of loans and mean values for each of the mortgage types for which we estimated default probabilities. Short-term hybrid ARMs were the most prevalent type of mortgage, and refinance loans were more prevalent than purchase loans. In addition, more loans were originated in the later portion of the time period we examined than the earlier portion. Default rates were highest for short-term hybrid ARMs, lower for loans originated in the middle years of the time period and higher for purchase loans than for refinance loans. The results of our analysis are presented in tables 13 through 16. We ran seven regressions: separate purchase loan and refinance loan regressions for three of the product types (short-term hybrid ARMs, fixed-rate mortgages, and longer-term ARMs) and a single regression combining purchase and refinance loans for payment-option ARMs. For this set of regressions, we only included the 63 percent of loans for which DTI information was available. We also ran a second set of regressions that used all of the loans for each mortgage type and binary variables indicating DTI ranges, including categories for missing information. We found that the results were very similar to those for the first set of regressions. We presented coefficient estimates, as well as a transformation of the coefficients into a form that can be interpreted as the marginal effect of each variable on the estimated probability of default. This marginal effect is the calculation of the change in the estimated probability of default that would result if a variable’s standard deviation were added to that variable’s mean value, while all other variables are held at their mean values. This permits a comparison of the impact of different variables within and across mortgage types. In general, combined LTV ratio, HPA, and FICO score had substantial marginal effects across different mortgage types and loan purposes. Specifically, higher LTV ratios, lower HPA, and lower FICO scores were associated with higher likelihoods of default. The observed effects for DTI ratio were relatively small. Among safe harbor characteristics, documentation of borrower income and assets and a loan’s spread over the applicable Treasury rate had substantial marginal effects. Less than full documentation and higher spreads were associated with higher default probabilities. Our results for full documentation of borrower income and assets were not sensitive to alternative specifications. Including the loan amount as an additional variable, adding or substituting different interest rates, and changing the form in which house price appreciation or FICO scores entered the model all had no effect on our general conclusion that the presence of full documentation was strongly associated with lowering the probability of default. Our conclusion concerning high cost loans—that larger spreads over specified Treasury rates at the time of origination are associated with increased default probability—is somewhat more nuanced. In some respects, the spread variable is capturing something about the effect of higher interest rates generally. For example, alternative specifications which substituted the initial interest rate or the Treasury rate for the spread variable yielded similar results. However, when the Treasury rate and the spread variables are included in the model, both variables are significant and have large marginal effects. As an alternative specification for short-term hybrid ARMs, we included a variable indicating whether each mortgage was a safe harbor or a non-safe harbor loan, in contrast to including variables for separate safe harbor requirements. We found that this variable had a small marginal effect, most likely because many non-safe harbor loans met some of the safe harbor requirements. In particular, a substantial percentage of non-safe harbor loans had full documentation of borrower income and assets but failed to meet other safe harbor requirements. In addition to the individual named above, Steve Westley, Assistant Director; Bill Bates; Stephen Brown; Emily Chalmers; Rudy Chatlos; Randy Fasnacht; Tom McCool; John McGrail; Mark Metcalfe; Rachel Munn; Susan Offutt; Jasminee Persaud; José R. Peña; Scott Purdy; and Jim Vitarello made key contributions to this report.

Summary: H.R. 3915 (2007), a bill introduced, but not enacted by the 110th Congress, was intended to reform mortgage lending practices to prevent a recurrence of problems in the mortgage market, particularly in the nonprime market segment. The bill would have set minimum standards for all mortgages (e.g., reasonable ability to repay) and created a "safe harbor" for loans that met certain requirements. Securitizers of safe harbor loans would be exempt from liability provisions, while securitizers of non-safe harbor loans would be subject to limited liability for loans that violated the bill's minimum standards. In response to a congressional request, this report discusses (1) the proportions of recent nonprime loans that likely would have met and not met the bill's safe harbor requirements and factors influencing the performance of these loans, and (2) relevant research and the views of mortgage industry stakeholders concerning the potential impact of key provisions of the bill on the availability of mortgage credit. To do this work, GAO analyzed a proprietary database of securitized nonprime loans, reviewed studies of state and local anti-predatory lending laws, and met with financial regulatory agencies and key mortgage industry stakeholders. GAO estimates that almost 75 percent of securitized nonprime mortgages originated from 2000 through 2007 would not have met H.R. 3915's safe harbor requirements, which include, among other things, full documentation of borrower income and assets, and a prohibition on mortgages for which the loan principal can increase over time. The extent to which mortgages met specific safe harbor requirements varied by origination year. For example, the percentage of nonprime mortgages with less than full documentation rose from 27 percent in 2000 to almost 60 percent in 2007. Consistent with the consumer protection purpose of the bill, GAO found that certain variables associated with the safe harbor requirements influenced the probability of a loan entering default (i.e., 90 or more days delinquent or in foreclosure) within 24 months of origination. For example, on the basis of statistical analysis, GAO estimates that, all other things being equal, less than full documentation was associated with a 5 percentage point increase in the likelihood of default for the most common type of nonprime mortgage product. GAO also found that other variables--such as house price appreciation, borrowers' credit scores, and the ratio of the loan amount to the house value--were associated with default rates. Research on state and local anti-predatory lending laws and the perspectives of mortgage industry stakeholders do not provide a consensus view on the bill's potential effects on the availability of mortgage credit. Some research indicates that anti-predatory lending laws can have the intended result of reducing loans with problematic features without substantially affecting credit availability. However, it is difficult to generalize these findings to all anti-predatory lending laws or the potential effect of the bill, in part, because of differences in the design and coverage of these laws. Mortgage industry and consumer group representatives with whom GAO spoke disagreed on the bill's potential effect on credit availability and consumer protection. For example, mortgage industry officials generally said that the bill's safe harbor, securitizer liability, and other provisions would limit mortgage options and increase the cost of credit for nonprime borrowers. In contrast, consumer groups generally stated that these provisions needed to be strengthened to protect consumers from predatory loan products.