Two types of residential mortgage loans are common: fixed-rate mortgages, which have interest rates that do not change over the entire term of the loans, and adjustable-rate mortgages (ARM), which have interest rates that change periodically based on changes in a specified index. Residential mortgages also fall into several loosely defined categories: Prime mortgages are made to borrowers with strong credit histories and provide the most attractive interest rates and loan terms; Near-prime mortgages (also called Alt-A mortgages) generally serve borrowers whose credit histories are close to prime, but the loans have one or more higher-risk characteristics such as limited documentation of income or assets or higher loan-to-value ratios; Subprime mortgages are generally made to borrowers with blemished credit and feature higher interest rates and fees than prime loans; and Government-insured or -guaranteed mortgages primarily serve borrowers who may have difficulty qualifying for prime loans and feature interest rates similar to those for prime loans. HUD’s Federal Housing Administration (FHA), VA, and the Rural Housing Service operate major federal programs that insure or guarantee mortgages. The nonprime market segment (Alt-A and subprime) features a number of nontraditional products and characteristics: Hybrid ARM—interest rate is fixed during an initial period, then “resets” to an adjustable rate for the remaining term of the loan. Payment-option ARM—borrower has multiple payment options each month, including negative amortization (minimum payments lower than needed to cover any of the principal or all the accrued interest, which may increase the outstanding loan balance over time). Interest-only—borrower can pay just the interest on the loan for a specified period, usually the first 3-10 years, thereby deferring principal payments. Low and no documentation loans—require little or no verification of a borrower’s income or assets. High loan-to-value ratios—borrower would make a small down payment, causing the ratio of the loan amount to the home value to be relatively high. The higher the ratio when a loan is originated, the less equity borrowers will have in their homes. Prepayment penalties—borrower incurs a fee if he or she pays off the loan balance before it is due. Balloon payment loans—mortgages that do not fully amortize over the term of the loan, leaving a balance due at the end of the balloon period. Mortgages can fall into any one of several payment status categories: Current—borrower has met scheduled payments. Delinquent—borrower has missed one or more scheduled monthly payments. Default—borrower is 90 or more days delinquent. Foreclosure—borrower has been delinquent for more than 90 days and the lender has elected to initiate a legal process against the borrower that has several possible outcomes. Generally, the borrower loses the property because it is sold to repay the outstanding debt or is repossessed by the lender. Prepaid—borrower has paid the entire loan balance before it is due. Prepayment often occurs as a result of the borrower selling the home or refinancing. After the loan has been made, originating lenders can retain their loans in portfolio or sell them to investors on the secondary market, either as whole loans to other financial institutions or (directly or indirectly through other financial institutions) as loan pools that are held in trusts and administered by a trustee. The loan pools become asset-backed securities that are issued and sold to investors and are referred to as mortgage-backed securities. This process, often referred to as securitization (see fig. 1), plays an important role in providing capital for mortgage lending by generating funds that can be used to originate more loans. Investors assume the interest rate, prepayment, and credit risk associated with the loans backing these securities, unless they are covered by mortgage insurance or guarantees on the securities. The secondary market for residential mortgages consists of three major categories of securitizations—enterprise (Fannie Mae and Freddie Mac), Ginnie Mae, and private label. Fannie Mae and Freddie Mac are congressionally chartered, for-profit, shareholder-owned companies known as government-sponsored enterprises and have been under federal conservatorship since 2008. They generally purchase conforming loans, which are mortgage loans that meet certain criteria for size, features, and underwriting standards. In addition, the enterprises require that loans they purchase with loan-to-value ratios in excess of 80 percent have a credit enhancement mechanism, such as private mortgage insurance. Loans above this limit are known as jumbo loans. After purchasing mortgages, the enterprises create mortgage-backed securities and guarantee investors in these securities that they will receive timely payments of principal and interest. Ginnie Mae (a government corporation) guarantees securities that are issued by approved private institutions and backed by federally insured mortgages (FHA, VA, and USDA). Private institutions are also involved in the creation of private- label securities backed by mortgages that do not conform to the enterprises’ purchase requirements (because the mortgages are too large or do not meet specified underwriting criteria). Private securitizing institutions include investment banks, retail banks, mortgage companies, and real estate investment trusts. Other participants to a private securitization transaction include, but are not limited to, credit rating agencies that assess the creditworthiness of the securities and deal with underwriters hired by securitizers to market and sell the securities to investors. Each type of securitization retains a mortgage servicer to collect mortgage payments from borrowers and disburse interest and principal payments to mortgage trustees, who pass them to investors. Servicers also manage delinquent loans that may lead to loss mitigation (such as a loan modification or a repayment plan) with the borrower or foreclosure. The ATR/QM regulations set forth minimum requirements lenders must consider in relation to making the required good faith determination of a consumer’s reasonable ability to repay. To satisfy the ability-to-repay requirements, lenders generally must consider eight underwriting factors: (1) current or reasonably expected income or assets; (2) current employment status; (3) the monthly payment on the covered transaction (the monthly payment must be calculated based on any introductory rate or fully indexed rate for the loan, whichever is higher, and substantially equal, fully amortizing monthly payments); (4) the monthly payment on any simultaneous loan; (5) the monthly payment for mortgage-related obligations; (6) current debt obligations, alimony, and child support; (7) the monthly debt-to-income ratio or residual income; and (8) credit history. To satisfy the QM requirements, the loan must meet certain restrictions on product features and points and fees as well as meet certain underwriting requirements. The loan must not have risky features such as negative amortization, interest-only payments, or balloon payments (except in certain circumstances). The term of the loan should not exceed 30 years. Point and fees should be less than or equal to 3 percent of the loan amount (higher percentages are allowed for loans of less than $100,000). Finally, the loan also must meet certain underwriting requirements. The creditor must take into account the monthly mortgage payment utilizing a fully amortizing schedule using the maximum rate that may apply during the first 5 years after the first payment. The creditor must consider and verify income or assets and current debt obligations, alimony, and child support. The rule also sets out three main categories of QMs that are presumed to comply with the ability-to-repay requirements: general, temporary, and small creditor. Under the general category, all loans to borrowers with a monthly debt-to-income ratio of 43 percent or less that meet the restrictions on product features, points and fees, and underwriting requirements described above are QMs. Under the temporary category, loans that meet the restrictions on product features, and points and fees described above, and are eligible for purchase, insurance, or guarantee by Fannie Mae, Freddie Mac, FHA, USDA and its Rural Housing Service, or VA are QMs, but are not subject to a specific debt-to-income ratio. Under the small-creditor category, loans must meet some restrictions on QMs such as product features and points and fees. Creditors must evaluate consumers’ debt-to-income ratio or residual income, but the loans are not subject to a specific debt-to-income ratio. Generally, these loans must be held in portfolio by a small creditor for at least 3 years. However, there is another category for small creditors in rural and underserved areas in which mortgages with balloon payments originated by such creditors can be QM loans. If a lender originates a mortgage that meets the QM requirements and has an annual percentage rate (APR) within certain limits, the lender is presumed to have satisfied the ability-to-repay requirements and receives certain protections from liability. That is, these QMs have a safe harbor (a conclusive presumption that the lender has satisfied the ability-to-repay requirements) that immunizes the lender from claims related to the borrower’s ability to repay. Lenders still can receive some protection from liability if they originate higher-priced QMs (those with APRs above certain limits). That is, lenders are still presumed to have satisfied the ability-to-repay requirements, but borrowers can rebut the presumption. Borrowers can try to prove that based on information available to the lender at loan origination, the borrower would not have enough income left for living expenses after paying the mortgage and other debts. Lenders also may make non-QM loans if they choose. However, these lenders will not benefit from the safe-harbor or rebuttable presumption liability protections afforded QM loans. The Dodd-Frank Act generally requires securitizers of asset-backed securities to retain not less than 5 percent of the credit risk of the assets collateralizing the security. The act includes exemptions, including one for securities collateralized exclusively by residential mortgages that are “qualified residential mortgages.” The Dodd-Frank Act specifies that the QRM definition cannot be broader than the QM definition (that is, the QRM criteria can be more but not less restrictive than the QM criteria). The act also requires agencies to specify criteria for QRMs, taking into consideration underwriting and product features that historical loan performance data indicate result in a lower risk of default; permissible forms of risk retention and the minimum duration for ways of allocating risk between securitizers and originators; and the possibility of permitting a lower risk-retention requirement (less than 5 percent) for any securitization collateralized by non-QRMs that meet underwriting standards the agencies develop in regulations. In the final risk-retention rule, issued in December 2014, the QRM definition was aligned with the QM definition.that meet the QM requirements outlined previously are considered to be QRM loans. Thus, securities collateralized solely by QM loans (and therefore QRM loans) are not subject to risk-retention requirements. Congress intended the risk-retention regulations to help address problems in the securitization markets by requiring securitizers to retain an economic interest in the credit risk of certain assets they securitized. As a result, securitizers would have an incentive to monitor and ensure the quality of the assets underlying a securitization transaction, which also would help align their interests with the interests of investors. More specifically, loans In relation to risk retention, sponsors of securitizations will be required to retain at least 5 percent of the credit risk associated with a securitization that contains any non-QRM loans, unless an exemption applies. Under certain circumstances, sponsors may allocate the retention obligation to an originator, which agrees to retain that risk, if the originator has contributed at least 20 percent of the balance of a loan pool collateralizing mortgage-backed securities. The final rule requires this risk to be held by originators in the same way the risk was held by the securitizer. The Dodd-Frank Act transferred consumer protection oversight and other authorities over certain consumer financial protection laws from multiple federal regulators to CFPB. CFPB’s responsibilities include ensuring that consumers are provided with timely and understandable information to make responsible decisions about financial transactions; ensuring that consumers are protected from unfair, deceptive, or abusive acts and practices, and from discrimination; and ensuring that markets for consumer financial products and services operate transparently and efficiently to facilitate access and innovation. The Dodd-Frank Act also gave CFPB supervisory authority over certain nondepository institutions, including certain kinds of mortgage market participants. Such institutions generally lacked federal oversight before the financial crisis of 2007–2009. Finally, the Dodd-Frank Act requires CFPB to conduct an assessment of each significant rule it adopts, such as the ATR/QM rule, and publish a report of the assessment no later than 5 years after the effective date of the rule.2019. The factors the assessments are to address include the rule’s effectiveness in meeting the purposes and objectives of Title X of the Dodd-Frank Act. Generally, Executive Orders and related implementation guidance from OMB require executive agencies and encourage independent regulatory agencies to develop and implement retrospective review plans. In addition, OMB encourages agencies to preplan efforts to retrospectively review their regulations and give careful consideration about how best to promote empirical testing of the effects of rules both in advance and retrospectively. OMB states that agencies may find it useful to engage in retrospective analyses of the costs and benefits (quantitative and qualitative) of regulations and suggests that independent regulatory agencies identify metrics to evaluate regulations and ensure they have high-quality data and robust models to conduct effective outcome-based reviews. These directives and guidance also encourage agencies to solicit public comments and make the results of these reviews available to the public. Finally, agencies are encouraged to coordinate when conducting their retrospective reviews and consider the combined effects of their regulations. During 2000-2014, originations for residential mortgage loans rose dramatically, then plummeted, and showed some signs of recovery in recent years. Available data indicate that low levels of riskier loan types have been originated since 2007. Additionally, measures of credit risk associated with mortgages, such as borrower credit scores and debt-to- income ratios, were consistent with an overall tightening of loan underwriting standards since 2008. The composition of the securities market for residential mortgages also changed during this period; in particular, the market share for private-label securities significantly diminished after 2007. As shown in figure 2, mortgage origination volume peaked in 2003, sharply declined in 2008, and then remained above 2008 levels (with mixed increases and declines) through 2013 but declined in 2014—due to declines in refinancing. In dollar terms, origination volume declined from $3.7 trillion in 2003 to $1.2 trillion in 2014. The lower volume potentially indicates lower credit availability, decreased demand, or both. A range of factors contributed to mortgage market activity from 2000 through 2014. Refinances. During the years of rapidly increasing mortgage origination (2000–2003), decreasing interest rates and increasing home prices provided opportunities for borrowers to refinance to lower monthly payments or take equity out of their homes for consumption and investment. As shown in figure 2, the volume of refinances increased to $2.8 trillion in 2003, and then decreased and remained at roughly $1.5 trillion from 2004 through 2007. Refinances as a percentage of mortgage originations peaked at 76 percent in 2003 and remained at roughly 70 percent from 2009 to 2013. Refinances declined to 44 percent in 2014. Similarly, the number of subprime cash-out refinances increased significantly from 2000 through 2005 (from about 246,000 in 2000 to about 1.2 million in 2005) and then declined to about 195,000 in 2007. As part of monetary policy, the Federal Reserve, through the Federal Open Market Committee, sets the federal funds rate at a level it believes will foster financial and monetary conditions consistent with achieving its monetary policy objectives, and it adjusts that target in line with evolving economic developments. availability of credit for the purchase of houses.” The large-scale purchase program was an integral component of the Federal Reserve’s efforts to ease financial conditions and provide policy accommodation in the crisis. Starting in September 2007 and on several occasions afterward, the Federal Reserve reduced the federal funds rate with the last reduction occurring in December 2008. Decreasing or increasing the federal funds rate—the rate at which depository institutions lend to other depository institutions overnight—can influence the cost and supply of credit, including mortgages. Mortgage rates are generally a product of the supply of and demand for mortgages. Other factors, such as the prevalence of mortgage defaults, unemployment rates, and home prices also can determine the supply and demand for mortgages and thus also influence costs. Default and foreclosure. Default and foreclosure rates peaked in 2010 but trended downward through 2013. From 2000 through 2006, mortgage performance was relatively stable. The rate of default was below 1 percent, and the foreclosure inventory rate—the percentage of total mortgage loans in foreclosure—was below 2 percent (see fig. 2). These rates then rose to historic levels, the default rate reaching nearly 5 percent and the foreclosure inventory rate reaching 4.6 percent in the first quarter of 2010. Through 2013, the rates declined, suggesting some recovery in the housing and mortgage market. But at the end of 2013, the foreclosure inventory rate remained at 2.9 percent, according to data from the Mortgage Bankers Association. As we reported earlier, more aggressive lending practices—that is, an easing of underwriting standards and wider use of certain loan features associated with poorer loan performance—contributed to the increases in default and foreclosure rates that began in the third quarter of 2006.house prices left borrowers more likely to have negative equity (owing more on a mortgage loan than the property is worth), which also contributed to the increases in defaults. Higher default rates may result in higher total losses for lenders on their loans. Originations of riskier loan types declined to low levels after 2007. For example, the share of nonprime mortgages (Alt-A and subprime) decreased from about 40 percent in 2006 to less than 5 percent in 2008 (see fig. 3). As noted in our 2009 report, the nonprime market segment featured a number of nontraditional products and characteristics.of the features of these products, such as low or no documentation of borrower income and assets, are prohibited or limited under the final ATR/QM rule. Since the decline in originations of riskier loan types, the market share of other loan types and products increased. For example, conforming and government-insured or guaranteed loans constituted the majority of loan originations from 2008 through 2014 (see fig. 3). More specifically, such loans accounted for about 80 percent or more of the market during this period. Furthermore, the share of jumbo loans hit a low in 2009 (5.5 percent), and then generally increased through 2014 (20.1 percent). Although larger than the conforming loan limit established by the enterprises, jumbo mortgages are generally considered prime mortgages and not Alt-A or subprime. Although the data on ARMs with risky features are limited, those data suggest that the availability of these features declined between 2005 and 2007. For example, originations of subprime ARMs and Alt-A option ARMs increased rapidly from 2000 through 2005, but fell markedly in subsequent years. About 262,000 subprime ARMs were originated in 2000, but this number grew seven-fold to about 1.8 million originations in 2005 (the peak of the market for subprime ARMs). By 2007, the number of these loans declined to about 214,000. Likewise, originations of Alt-A ARMs increased substantially, from about 10,000 loans in 2000 to more than 893,000 in 2005, but declined to about 249,000 by 2007. These nontraditional loans generally had fixed interest rates for short initial periods and then would convert to indexed rates higher than traditional ARMs—which could result in payment shock (large increases in monthly payments). Also, some lenders may have determined a borrower’s ability to repay an ARM based on the initial monthly payment, rather than the higher payments if rates were to increase. As we and others have found, subprime hybrid and Alt-A option ARMs had significantly higher rates of serious delinquency (in default or foreclosure) than other subprime and Alt-A loans. Since 2008, measures of the credit risk of purchase mortgages (such as borrower credit scores and debt-to-income ratios) were consistent with lenders tightening underwriting standards. Underwriting standards, such as those of FHA and the enterprises, include assessments of these measures. For example, the enterprises have a debt-to-income ceiling of 45 percent. A credit score is a numeric value that represents a borrower’s potential credit risk, based on his or her credit history. Generally, a higher score indicates greater credit quality and potentially lower likelihood of default. Lenders continue to use credit scores as a primary means of assessing whether to originate a loan to a borrower. As shown in figure 4, credit scores for purchase loans fluctuated but exhibited an upward trend since 2004. For example, average scores for these borrowers rose from 704 in January 2004 to 750 in December 2013. As shown in figure 4, the average debt-to-income ratio for purchase loans increased to a high of about 40 percent in early 2008 and subsequently decreased to 34 percent in December 2013. Lenders use debt-to-income ratio as a key indicator of a borrower’s capacity to repay a loan. The ratio represents the percentage of a borrower’s income that goes toward all recurring debt payments, including the mortgage payment. A higher ratio is generally associated with a higher risk that the borrower will have cash flow problems and may miss mortgage payments.income ratios is consistent with a tightening of credit availability for borrowers with higher debt burdens. However, the data provider and others have noted that the data are often missing debt-to-income information and debt-to-income ratios are often calculated inconsistently. A decline in debt-to- Nonetheless, research by CoreLogic suggests that lenders in recent years originated loans with lower debt-to-income ratios. Finally, average (mean) loan-to-value ratios for purchase loans increased since 2006. For example, from January 2003 to August 2006, average monthly loan-to-value ratios hovered around 80 percent. From September 2006 to November 2009, average monthly loan-to-value ratios increased about 5 percentage points to 85.6 percent. Since then, the ratios declined slightly, but remained higher than 2003–2006 levels. The continuing prevalence of higher ratios may be due in part to the increasing share of originations from FHA, which had an average loan-to-value ratio of about 96 percent for purchase loans originated from October 1999 to July 2014. of borrowers obtaining both first- and second-lien mortgages— ”piggyback” loans—that may not be reflected in the previous statistics.The higher the loan-to-value ratio when a loan is originated, the less equity borrowers will have in their homes and the more likely they are to default on mortgage obligations especially during times of financial stress. FHA provided the average loan-to-value ratio data. 2005 and 2006.less than 1 percent of the market. Overall, agencies, market participants, and observers estimated that the QM and QRM regulations would not have a significant effect initially because many loans made in recent years already met QM and QRM criteria before these regulations were promulgated. Our review of economic analyses showed that researchers estimate that the majority of mortgages originated in recent years likely would have met the requirements for QM and QRM loans. The recently finalized risk-retention rule aligns the definition of QRM with QM. Estimates from the studies we examined pertaining to loans made in recent years suggest that if lenders continued current practices, a The studies majority of loans would meet requirements for QM loans.used a variety of methodologies, including trend analysis with historical data, comparisons with established baselines, and surveys of market participants. Furthermore, in a July 2011 report, we found that the majority of loans originated from 2001 through 2010 would have met most of the individual QM criteria. The Federal Reserve estimated that 14 percent of Fannie Mae and Freddie Mac refinance mortgages in 2010 had debt-to-income ratios above 43 percent. In comparison, the Federal Reserve estimated that 25 percent of Fannie Mae and Freddie Mac purchase mortgages and 31 percent of Fannie Mae and Freddie Mac refinance mortgages in 2006 had debt-to-income ratios above 43 percent. Board of Governors of the Federal Reserve System,Mortgage Market Conditions and Borrower Outcomes: Evidence from the 2012 Data and Matched HMDA-Credit Report Data, Federal Reserve Bulletin vol. 99, no. 4 (Washington, D.C.: November 2013). underserved areas can make mortgages with balloon payments and those mortgages can qualify as QM loans. Although the QM regulations were not expected to have a significant effect on the overall mortgage market initially, some researchers and participants estimated that they could adversely affect certain borrowers. For example, a study we reviewed indicated that a narrow debt-to-income threshold may disproportionately affect minorities and people living in high-cost areas. Specifically, the higher cost of housing in certain areas can increase these ratios. In addition, some market participants raised the concern that lenders might be restricting lending to borrowers near the 43 percent debt-to-income or the 3 percent points and fees thresholds, out of concern that calculation errors could result in a non-QM loan. Due to data limitations, the researchers were not able to identify the entire universe of QM loans. all defaults during this period. However, the study also found a number of performing loans that did not appear to meet the QM standard. Specifically, 25 percent of nondefaulting mortgages made between 2005 and 2008 did not appear to meet the QM standards. Some observers noted that because the QM standards do not include a measure of creditworthiness (such as credit score) or a loan-to-value ratio requirement, some QM loans may have characteristics associated with higher default rates. As we reported in 2005 and 2010, loans with higher credit scores, lower loan-to-value ratios, or both perform better than loans with low credit scores, higher loan-to-value ratios, or both, all else being Because non-QM loans present higher liability risks, lenders may equal. impose stricter underwriting requirements for those loans, such as higher credit scores, lower loan-to-value ratio thresholds, or both. GAO, Mortgage Financing: Actions Needed to Help FHA Manage Risks from New Mortgage Loan Products GAO-05-194 (Washington, D.C.: Feb. 11, 2005); and Nonprime Mortgages: Analysis of Loan Performance, Factors Associated with Defaults, and Data Sources, GAO-10-805 (Washington, D.C.: Aug. 24, 2010); and GAO-08-78R. regulations would have a measurable reduction in credit availability, and two-thirds of respondents characterized the impact as moderate. The survey found mixed expectations on whether availability of all or only certain segments of mortgages would decline in response to the QM regulations. For example, 41 percent expected a reduction across all mortgages, and 40 percent of lenders expected a reduction only in non-QM lending. Furthermore, a third of lenders reported that they planned to restrict lending to QM segments only, and 29 percent indicated that they primarily would originate QM loans and only originate non-QM loans in targeted markets. The Federal Reserve administered a survey of senior loan officers in July 2014 in which loan officers reported that approval rates decreased for some mortgage types in response to the ATR/QM regulations. The survey found that the reductions in approval rates were often smaller for larger banks. Among the surveyed banks, the majority stated that approval rates did not decline for prime conforming loans, but about a third reported a reduction. (Prime conforming loans include loans eligible for purchase by the enterprises—which include loans automatically designated as QM.) Among all banks surveyed that made nontraditional mortgages, more than half indicated that loan approval rates were lower for nontraditional purchase mortgages—which are often non-QM due to their product features—because of the ATR/QM regulations. Finally, more than half of the respondents indicated that the QM regulations had reduced application approval rates for prime jumbo home- purchase loans. However, in January 2015, another Federal Reserve survey of senior loan officers found that several large banks had eased lending standards for a number of categories of residential mortgages over the preceding 3 months, about 12 to 13 percent of the large banks surveyed indicated an easing of credit standards for QM and non-QM jumbo loans. An article posted by the Urban Institute in August 2014 examined the effect the QM regulations might have on certain borrower and loan characteristics—such as borrowers with debt-to-income ratios above 43 percent, interest-only loans, adjustable-rate mortgages, and loans with small loan amounts—finding little variation in the proportion of such loans before and after implementation of QM regulations.example, the share of loans with debt-to-income ratios above 43 percent remained relatively steady at approximately 17 percent for Fannie Mae and Freddie Mac loans, 35 percent for Ginnie Mae loans, and 10 percent for bank portfolio loans. However, from January through July 2014, the share of loans with higher debt-to-income ratios declined slightly for enterprise loans. These statements and observations were made shortly after the QM regulation became effective. Market participants with whom we spoke stated that the QM standards were unlikely to have a significant effect on the securitization of residential mortgages, largely because the majority of loans originated were expected to be QM loans. Representatives of credit rating agencies with whom we spoke indicated that they did not plan to require any additional credit enhancements when rating securities backed solely by QM safe-harbor loans. Market observers, including two credit rating agencies also told us that there had been a relatively small volume (number and size) of private- label securitizations recently, consistent with the overall securitization trends we noted earlier. According to one of the larger credit rating agencies, the market issued 27 residential mortgage-backed securities in 2014, most of which contained only QM loans. Another larger credit rating agency told us that it rated 10 prime residential mortgage-backed securities in 2014 that included QM loans. Although three of the ten included non-QM loans, the proportion of non-QM loans was never greater than 2 percent in any transaction. Neither rating agency believed that a completely non-QM transaction was rated in 2014. Some observers told us that many non-QM loans originated after the QM regulations became effective had been held in portfolio, indicating they had not been securitized. However, observers noted that some securities have included non-QM loans and firms have discussed creating non-QM securities in the future. According to federal agency officials, the primary costs associated with the QM regulations are increased litigation and compliance costs. Generally, lenders, investors, and borrowers incur litigation costs when borrowers file a legal claim challenging a lender’s efforts to assess the borrower’s ability to repay. Lenders incur compliance costs to ensure that they comply with QM regulations, such as by documenting their efforts to assess borrowers’ ability to repay. Estimates for potential litigation costs associated with the QM regulations varied. Lenders’ costs may increase due to potential litigation costs. The absence of safe harbor protection exposes higher-priced QM and non- QM loans to increased litigation risk. Both CFPB and credit rating agencies estimated increased litigation costs associated with non-QM loans. In contrast to CFPB, credit rating agencies also estimated increased litigation costs associated with higher-priced QM loans. However, CFPB stated that its estimated costs for nonqualified mortgages “should reasonably serve as an upper bound for the costs of qualified mortgages.” CFPB’s estimate assumed that 20 percent of borrowers in foreclosure with non-QM loans would challenge a lenders’ compliance with the ability-to-repay regulations. In contrast, the estimates of credit rating agencies about the probability of litigation ranged from 5 to 50 percent among borrowers in foreclosure with non-QM loans. Most significantly, the credit rating agencies considered if the borrower was located in a nonjudicial or judicial state. CFPB also assumed that 20 percent of the borrowers challenging the lender would prevail in litigation. In contrast, the credit agencies’ estimates for borrower success ranged from 10 to 75 percent. Credit rating agencies estimates differed from CFPB’s because of the different assumptions and methodologies used in their analyses. Depending on the risk and costs to lenders associated with any additional litigation, they might manage these costs by passing them to borrowers in the form of higher loan costs or limiting the volume of loans originated that likely would be subject to litigation risk. For example, CFPB estimated that the potential for increased litigation costs would cause interest rates for non-QM loans to increase by approximately 2.5 basis points. However, CFPB did not generate a similar estimate for high- priced QM loans. Following CFPB’s rule, the credit rating agencies published credit enhancement adjustments, which are used to offset potential investor losses due to increased risk of litigation, for high-priced QM and non-QM loans. Fitch estimated an adjustment of 65 basis points for high-priced QM loans and 40 basis points for non-QM loans. In contrast, Standard and Poor’s estimated an adjustment of 9 basis points for high-priced QM loans and 30 basis points for non-QM loans. Likewise, the addition of these credit enhancements ultimately may increase the cost of funding these loans. The effect would be difficult to estimate because it is largely dependent on future housing market conditions, including the level of competition among lenders and among securitizers. Although these estimates provide insights about the costs associated with the QM regulations, agency officials and observers with whom we spoke said that the estimates were limited by the unique legal requirements for originators and investors under the Dodd-Frank Act that we discussed earlier. The observers noted that they expected to revise their estimates when litigation had taken place. Thus, the actual litigation costs associated with QM may not be known for some time. Market participants and industry observers did not believe that compliance costs associated with the ATR/QM regulations would hinder the functioning of the overall market, but they identified compliance costs that were likely to be passed to consumers. For example, they noted that complying with the documentation standards creates additional work and adds processing time, both of which result in increased costs. Costs also could rise if institutions needed to take additional steps to properly disclose information in their financial statements about QM and non-QM loans. But market participants also noted that compliance costs may vary by institution and the degree to which an institution could realize certain economies of scale. Some indicated that compliance costs were significant for all originators, regardless of size, but added that these costs were related to more than just QM regulations, and included implementing Basel III standards. According to agency officials and observers, the QRM regulations, which were finalized in December 2014, were unlikely to have a significant effect on the availability of residential mortgages under current market conditions. A loan meeting QM standards automatically is QRM-eligible; therefore, securities collateralized solely by QM loans will not require securitizers to retain any of the risk. Securitizers generally must retain at least 5 percent of the credit risk associated with any securitization collateralized by any non-QRM loans. Securitizers may allocate the retention obligation to an originator, if the originator has contributed at least 20 percent of the balance of a loan pool collateralizing mortgage- backed securities. As discussed earlier, agency officials and market observers anticipate that the majority of loans will conform to QM standards and therefore believe that the QRM regulations will not have a substantial effect on the availability of residential mortgages for most borrowers. Since the risk-retention rule equated QRM with QM, mortgage market participants likely would incur few or low additional costs, if any, in ensuring that loans met the definition of QRM. As discussed earlier, the primary costs associated with the QM regulations are litigation and compliance costs. These additional costs may be passed to borrowers. To ensure compliance with the QRM regulations, lenders and securitizers might need to take additional steps to properly disclose information in their financial statements about QRM and non-QRM loans. According to the regulators, aligning the QRM definition with QM would meet the statutory goals and directives to limit credit risk and preserve access to affordable credit, while at the same time facilitating compliance. Specifically, the agencies in the final QRM regulations noted that the markets for those residential mortgages exempted under the final rule (that is, QRM mortgages) are expected to be large, and result in significant liquidity, economies of scale, and little-to-no impact on securitization of these mortgages. For non-QRM securities, the Federal Reserve estimated in October 2014 that a risk-retention requirement of 5 percent would add 25 basis points at most to a borrower’s costs. However, studies we reviewed and mortgage market participants with whom we spoke did not believe these costs would disrupt mortgage market function. The effect of the QRM regulations on the securitization of residential mortgages is likely to be limited in the current market. By equating the definition of QRM with QM, the majority of loans currently being originated likely would be considered to be QRM-eligible and, therefore, not subject to risk retention. However, changes to the role of the federal government in relation to the structure of the market for residential mortgage-backed securities could change the expected effects of the QRM regulations. The final QRM regulations exempt certain securitizations from the risk- retention requirements, including securitizations that have the full guarantee of the enterprises and securitizations guaranteed by Ginnie Mae. Mae and Freddie Mac operate under federal conservatorship. This consideration is separate from the QM temporary exemption for enterprise loans discussed earlier.Finance, the enterprises had a dominant share of the residential securitization market during 2013, with about 66 percent of mortgage originations made through the enterprises. Ginnie Mae guaranteed about 22 percent of the residential securitization market in 2013. 79 Fed. Reg. 77749(§__.8) (Dec. 24, 2014) and 79 Fed. Reg. 77761 (§__.19(b)(1)) (Dec. 24, 2014). small compared with the volume and size of such securitizations from 2005 through 2007. According to the credit rating agencies with which we spoke, the majority of the loans that make up these recent securities met the QM definition and therefore would be considered to be QRM-eligible. Observers estimated that non-QRM loans sold to the private-label secondary market likely would be low-risk loans, such as interest-only loans to high-wealth borrowers. However, some have cautioned that the equation of QM and QRM might restrict the secondary market for non-QRM loans and therefore limit the origination of these loans. For example, the risk-retention rule states that “the agencies recognize that aligning the QRM and QM definitions has the potential to intensify any existing bifurcation in the mortgage market that may occur between QM and non-QM loans, as securitizations collateralized by non-QMs could have higher funding costs due to risk- retention requirements in addition to potential risk of legal liability under the ability-to-repay rule.” The agencies acknowledged this risk but decided that not aligning QRM and QM definitions likely would result in even greater segmentation in the securitization market and higher costs for consumers. Furthermore, the final risk-retention rule requires that securitizations with blended pools of QRM and non-QRM loans be subject to the risk-retention requirements. As noted in the preamble to the rule, the QRM agencies (FDIC, Federal Reserve, FHFA, HUD, OCC, and SEC) anticipated that “QM and non-QM loans are less likely to be combined in a pool because of the different risk profiles and legal liabilities associated with these loans.” Some industry observers pointed out that the small volume of non-QRM loans, which will be subject to risk- retention requirements, may not be sufficient to result in a fully functioning securitization market for such loans. Similarly, the preamble to the rule states that “securitization typically is a more cost-effective source of funding when the underlying pool includes a large number of loans.” Although some private-label securities included both QM and non-QM loans in the same securitization in 2014, one rating agency noted that it had not rated any transactions that consisted entirely of non-QM loans and did not believe that such a transaction had closed during 2014. At least one sponsor plans to create a mortgage-backed security that is wholly non-QRM, according to one rating agency. Although some lenders have been making and holding non-QRM loans in their portfolios, the lack of a robust market for non-QRM securities may limit some lenders’ willingness to underwrite non-QRM loans. Some investors expressed the concern that the adopted QRM regulations did not increase investor protections for higher-risk loans that were QM- eligible. Specifically, the QRM regulations permit security sponsors to include QM-eligible loans with high-risk characteristics, such as high loan- to-value ratios and low credit scores, without imposing a risk-retention requirement. The risk-retention rule does not incorporate requirements for a loan-to-value ratio or a borrower’s credit history because of concerns that the additional requirements might disproportionately affect low- and moderate-income, minority, or first-time homebuyers. Furthermore, the agencies believe the QRM requirements appropriately minimize regulatory compliance burdens in the origination of residential mortgage loans. According to an institutional investor advisor, investors would prefer to rely on risk retention as a method for holding mortgage originators and securitizers accountable. Outside of the risk- retention/QRM regulations, investors now have access to additional information that they could use to require sponsors to retain some of the credit risk of loans that make up the mortgage-backed security. Previously, investors typically lacked detailed information about the pool of loans that made up securities. However, SEC recently revised regulations for registered offerings of asset-backed securities to require that certain loan-level information for residential mortgage-backed securities (among other asset classes) be made available at the time of the offering and on an ongoing basis. Due to the unavailability of certain important data elements, researchers faced challenges when analyzing the short-term and long-term potential effects of the QM and QRM regulations. Similarly, we previously reported that this issue makes evaluating the potential effects of the QM and QRM regulations difficult, as detailed in the following examples. Debt-to-income ratios are key elements to identify QM and non-QM loans. However, as we and others have found, this information is often unreliable or missing. Datasets frequently do not contain debt- to-income information for subprime and Alt-A loans, and available data often may be unreliable. Information on the points and fees borrowers incur are also key elements to identify QM and non-QM loans. However, this information is not maintained in any available database, according to agency officials and observers. Without this information, it is difficult to determine if a loan complied with the QM requirement for a 3 percent cap on points and fees. For these reasons, conclusively identifying the universe of QM loans is difficult. Instead, the studies must rely on other indicators of QM loans such as the lack of certain prohibited features or markers for the loan being fully documented. Researchers also often faced challenges establishing a baseline for assessing the effect of the QM regulations. As discussed earlier, the housing market is highly cyclical, but the early 2000s saw a major expansion in many segments of the market. As such, the choice of a baseline can significantly affect a study’s findings. For example, choosing an immediate precrisis baseline may make it appear that regulations were having a larger effect than they would with a postcrisis baseline. Baseline choices can result in different findings on the potential future effect of QM. Mortgage market participants also told us that it would be difficult to isolate the effect of the regulations on the availability of mortgages because of other changes affecting the mortgage market. For example, many mortgage originators are also subject to the new CFPB servicing requirements. As a result, it is difficult to attribute any changes observed in the mortgage market directly to the finalization of the QM and QRM regulations. The long-term implications of the QM and QRM regulations on the mortgage market depend on several factors that are difficult to predict. For example, lender willingness to make non-QM loans (particularly to certain borrowers such as those with high debt-to-income ratios) and the cost of these loans are unknown. In addition, the future role of the enterprises in the residential mortgage market has yet to be determined and the mortgage activities of federal agencies may change (many proposals have been introduced to change the single-family housing finance system). Moreover, the QM and QRM regulations may change over time. For example, CFPB took action to expand the exemption for small lenders after the rule had been finalized. Finally, the activities of nongovernmental and private participants can change over time In a 2014 report that assessed protection for mortgage securities investors, we found that the ATR/QM regulations might set a floor to the loosening of credit and help prevent a repeat of the deterioration of lending standards that contributed to the 2007–2009 financial crisis. The QM and QRM regulations provide incentives to originate QM and QRM loans. For example, originating a QM loan provides litigation protection for the lender and assignee if the loan is sold to an investor. Similarly, securitization sponsors are not required to retain any portion of the credit risk of QRM loans if the securitization exclusively comprises QRM loans. Should underwriting standards begin to loosen and lenders become more willing to offer loans that do not meet QM or QRM standards, these incentives may deter some lenders from loosening standards beyond the limits specified in the regulations. Although the regulations may help limit high-risk mortgage lending in future market expansions, some activities are not forbidden by statute (for example non-QM mortgage loans still can have negative amortization and interest-only payments). Nonetheless, lenders must assess the borrowers’ ability to repay for all loans, including any non-QM loans lenders may originate and sponsors may securitize. CFPB and HUD have begun planning for their reviews of the QM regulations. CFPB identified potential outcomes, data sources, and analytical methods for examining its QM regulations, but had not finalized its plans. HUD identified outcomes and potential data sources, but had not identified specific metrics, baselines, and analytical methods for examining its regulations. The agencies responsible for the QRM regulations identified outcomes and potential data sources and analytical methods, but had not yet identified specific metrics and baselines for examining the QRM regulations. In response to the Dodd-Frank requirement to review significant rulemakings, CFPB has made efforts to identify data, but as of May 2015 had not finalized a plan that specified what outcomes and methodologies—such as metrics, baselines, and analytical methods—it will use to examine the effects of the QM regulations. CFPB discussed some potential plans to review the QM regulations in the final ATR/QM rule but has not since finalized a plan for its analysis. The Dodd-Frank Act requires CFPB to assess “the effectiveness of the rule or order in meeting the purposes and objectives of this title [Title X— Bureau of Consumer Financial Protection] and the specific goals stated by the Bureau.” Furthermore, Executive Order 13563 states that the regulatory system “must measure, and seek to improve, the actual results of regulatory requirements.”completed plans for how it intends to examine the QM regulations. For instance, a review addressing the purposes of the title might include outcomes such as the effects of the regulations on the overall housing market, cost or availability of credit to borrowers, regulatory burden on industry participants, or protection of consumers from unsustainable mortgage products. The choice of outcomes to be examined plays a key role in the selection of appropriate or relevant data, baselines, and But CFPB has not yet analytical methods. For example, examining the cost and availability of mortgage credit could require different data elements and analysis than examining the effectiveness of the QM regulations in preventing defaults and foreclosures. To date, CFPB has identified several potential data sources it could use to examine the QM regulations. For example, CFPB identified data collected to meet the requirements of the Home Mortgage Disclosure Act (HMDA). HMDA data currently include information about mortgage applications, originations, and loans purchased on the secondary market. However, HMDA currently does not contain information to determine if a loan is QM or non-QM. The Dodd-Frank Act directs CFPB to expand HMDA data reporting requirements. For example, it directs the collection of points and fees information, interest rate spreads, and certain other loan features. CFPB also has proposed to collect additional information (such as borrowers’ debt-to-income ratios and whether the loan meets the QM standard) that could be used to examine the QM regulations. However, the data elements may not be finalized as proposed and may not be available at the time CFPB conducts its analysis (the report on the review must be published no later than Jan. 10, 2019). CFPB had not finalized the HMDA proposal as of April 2015. Once the new HMDA reporting requirements are finalized, CFPB officials said lenders will need time to modify their systems to comply with the new reporting requirements, collect the data, and report the data to CFPB.officials indicated that the earliest the new data might be collected would CFPB be in 2017. Moreover, HMDA data do not include and are not planned to include information about the performance of loans—such as default, delinquency, and foreclosure. According to agency officials, loan performance information would be important to fully examine the effects of the QM regulations. CFPB also entered into a partnership with FHFA to build the National Mortgage Database (NMDB), which will contain loan-level information about the mortgage, borrower, and property for a nationwide sample of 5 percent of borrowers from credit bureau files. information from a credit bureau (such as borrowers’ credit scores and payment history on the mortgage) will be supplemented with data from other sources, such as HMDA and property valuation models, to create a comprehensive profile for each mortgage in the database. FHFA officials said NMDB is planned to include borrower’s debt-to-income ratios, points and fees, interest rate of the loan, and information on loan performance. Although the data used to create NMDB includes personally identifiable information, the database will not contain personally identifiable information, according to CFPB officials. The database is not yet available. FHFA officials anticipated merging the data sources in 2015 and conducting analyses using the database at the end of 2015 or 2016. FHFA officials have noted some concerns about the reliability of some of the data, such as inconsistent definitions used for the debt-to-income ratio at loan origination. Furthermore, many loan records do not contain any information for some data elements, such as debt-to-income ratio. Ultimately, FHFA officials hope to obtain debt-to-income information from HMDA, which they anticipate will be a reliable data source. But, as noted earlier, the expanded HMDA data will not be collected until at least 2017. According to CFPB and FHFA officials, the agencies have worked together to develop the specifications of the database, such as identifying data elements. CFPB has provided financial support to create the database and FHFA has developed the infrastructure and hardware for NMDB. contain data similar to HMDA (such as origination data) and the forthcoming NMDB (such as loan performance information). CFPB suggested that it could use these datasets to conduct analysis similar to the one it conducted when developing the ATR/QM rule. For example, CFPB used data from the two private vendors to estimate the percentage of loans that would have qualified as QMs from 1997 through 2003 and in 2011. However, according to CFPB officials, CoreLogic and BlackBox LLC data do not contain any information on points and fees or reliably contain borrowers’ debt-to-income ratios. CFPB officials said they could estimate the points and fees by deriving them from the stated interest rate and APR of the loan, but cautioned that determining what charges were included in the APR calculation was complex. Any analyses utilizing this approach would need to consider and potentially correct for any bias in the missing data. CFPB officials said they have been collecting qualitative information from various sources to monitor the initial effects of the QM regulations on the residential mortgage market. For example, CFPB officials said they have been tracking industry news, reviewing reports from media outlets, and reviewing reports published by institutions and market participants (such as credit rating agencies and some lenders) and the Federal Reserve. In addition, CFPB officials said they have held informal conversations with lenders at industry events and conferences to obtain their views on the effects of the QM regulations. CFPB officials said this information alone would not be enough to examine the QM regulations, but would inform their approach for examining the regulations. OMB encourages agencies to preplan efforts to retrospectively review their regulations to improve the effectiveness of the reviews. OMB suggests that agencies identify metrics to evaluate regulations, identify baselines for their planned analyses, and ensure they have robust models to conduct their analyses. Furthermore, when promulgating regulations, OMB encourages agencies to give careful consideration about how to promote empirical testing of the effects of the rules during retrospective reviews. We found in a July 2007 report that agencies would be better prepared to undertake reviews if they identified what data and measures would be needed to assess the effectiveness of a rule before they started a review and, indeed, before they promulgated the rule. CFPB officials told us that they had not yet finalized a plan for their retrospective review because they had been focusing first on developing and finalizing the mandated regulations. Congress required CFPB to issue the QM regulations within 18 months of the “designated date” for the transfer of consumer financial protection functions under section 1061 of the Dodd-Frank Act to CFPB from other agencies. CFPB officials told us that a plan to assess the QM regulations is critical. But, as of May 2015, CFPB officials were working to finalize a review plan and officials could not tell us what outcomes they would measure and what data and methodologies they would use to examine the effectiveness of these regulations. Without a plan to assess the QM regulations, CFPB may be limited in its ability to effectively examine the regulations by the mandated deadline. Such a plan will be particularly important because of the uncertainty about the availability and timing of needed data, which may necessitate consideration of alternative analytic strategies and data sources. P.L. 111-203. Sec. 1400(c). See Pub. L. No. 111-203, §1062 for the requirement that the Secretary of the Treasury designate a date for the transfer of responsibility, among others, for promulgating regulations under various federal consumer financial laws to CFPB. See 75 Fed. Reg. 57252 (Sept. 20, 2010) for Treasury’s designation of July 21, 2011, as the transfer date. wide plan for retrospective review of regulatory actions.Lenders can use a borrower’s residual income as one measure of ability to make a mortgage payment. HUD does not maintain key data that it would need to conduct the reviews—such as information on points and fees and interest rate spreads (criteria for determining if a loan is safe harbor or rebuttable presumption) and data needed to calculate residual income. To mitigate the data gaps, HUD officials said they have considered using HMDA and NMDB data. But as we discussed previously, the availability dates of the expanded HMDA and NMDB data—such as information on points and fees—are not known. As of May 2015, the agency also had not identified how it would measure the effects of these regulations, including metrics, baselines, and analytical methods. HUD officials stated that they have not finalized plans for their review of the QM regulations because of the uncertainty about the availability of data resources, such as NMDB. They noted that once the NMDB database was released, they would be able to determine whether it could be used as a resource to monitor and examine QM lending. But, without a plan to identify how to obtain necessary data and identify metrics, baselines and analytical methods, HUD may be limited in its ability to effectively review its regulations and achieve the intended outcomes of its reviews. Agency efforts to assess the QRM regulations included identifying outcomes and potential data sources and methodologies, but have not yet identified specific metrics, baselines, or analytical methods. The six agencies responsible for the QRM regulations—FDIC, FHFA, Federal Reserve, HUD, OCC, and SEC—have committed to commence a review of the QRM definition no later than 4 years after the effective date of the final rule (Dec. 24, 2015, for the QRM-related provisions), and every 5 years thereafter. In the risk-retention final rule, the agencies recognized that mortgage and securitization market conditions and practices change over time, and therefore stated it would be beneficial to review the QRM definition. More specifically, the agencies would consider the structures of securitizations, roles of the various transaction parties, relationships between enterprise and private-label markets, and trends in mortgage products in various markets and structures. They also stated that they would review how the QRM definition affected residential mortgage underwriting and securitization under evolving market conditions. The agencies noted the timing would help ensure the initial review of the QRM definition benefitted from CFPB’s review of the ability-to-repay rules, including the QM definition, and would help the agencies in determining whether the QRM definition should continue to fully align with the QM definition in all aspects. Agency officials said their efforts have included identifying potential data sources for the review of the QRM regulations. For example, they noted that they likely would use mortgage data sources similar to those utilized when developing the QRM regulations, such as loan-level data from the enterprises and information on private-label mortgage-backed securities from a private data vendor. However, agency officials acknowledged that the data available from these sources are missing key information, such as points and fees and borrower’s debt-to-income ratios, needed to determine if a loan is QM or non-QM, and consequently QRM eligible. In addition, agency officials identified HMDA and NMDB as possible data sources. However, the databases currently do not collect information on points and fees and debt-to-income ratios, which may limit their usefulness for examining the QRM regulations. Finally, the agencies have considered using data collected through the Fannie Mae Mortgage Lender Sentiment Survey and the Mortgage Bankers Association’s Mortgage Credit Availability Index to help examine the QRM definition. Although agency officials have identified several data sources, they have not established which data elements to select or how they would be used to assess the QRM regulations. The Mortgage Lender Sentiment Survey is a quarterly online survey among senior executives of Fannie Mae’s leading institution partners. The survey covers industry topics such as credit standards, consumer mortgage demand, and mortgage execution. The monthly Mortgage Credit Availability Index is calculated using a borrower’s credit score, loan type, and loan-to-value ratio, among other factors. The index is a summary measure that indicates the availability of credit at a point in time. Agency officials said their efforts also have included identifying potential methodologies to assess the QRM regulations. For example, they plan to use information collected through their ongoing efforts to monitor broad trends and developments in the residential mortgage market, such as mortgage applications, originations, products, and securitizations as well as loan performance. They also have considered examining loan volumes for QRM and non-QRM loans, as well as QM safe harbor and rebuttable presumption loans. Furthermore, they may conduct a trend analysis by comparing market data before and after the risk-retention rules were effective. Finally, they said that they may look at early payment delinquencies and defaults of newly originated mortgages, as well as different kinds of QM loans, such as those covered under the QM temporary exemption for enterprise loans. Although the agencies identified several retrospective review components—such as outcomes to examine and potential data sources and methodologies—they have not developed a plan that identifies specific metrics and baselines or committed to specific analytical methods. Agency officials stated that they have not developed more specific plans because their ongoing efforts to monitor broad mortgage market trends were sufficient. Additionally, agency officials expected additional information on the housing and mortgage market to be available for their review of the QRM regulations. They explained that the information would be important in determining whether the QRM definition was appropriate under prevailing market conditions. However, the timing, accuracy, and completeness of the data that may be available in time for the agencies to conduct their retrospective reviews (commencing no later than Dec. 24, 2019) are unclear. As we discussed previously, agencies can be better prepared to undertake their reviews and may be able to overcome or mitigate data challenges by identifying specific data sources, metrics, baselines, and analytical methods well before conducting the review, ideally before promulgating the rule. Moreover, although agency officials acknowledged that the review of the QRM regulations necessitates interagency collaboration and plan to collaborate, the agencies have not yet identified specific mechanisms to promote effective collaboration. According to agency officials, the QRM agencies and CFPB held interagency meetings as agreed to during the promulgation of the QM and QRM regulations. The agencies plan to hold interagency meetings to conduct the reviews of the QRM regulations. OMB guidance encourages agencies with overlapping jurisdiction or expertise to determine how the agencies will coordinate to conduct retrospective reviews. In prior reports, we identified key practices to effective agency collaboration, including (1) agreeing on agency roles and responsibilities, (2) defining and articulating a common outcome, (3) establishing mutually reinforcing or joint strategies, and (3) identifying and addressing needs by leveraging resources. Without establishing a framework for collaboration, such as specifying the roles each will play and responsibilities, the agencies involved in the QRM reviews may be limited in their ability to measure the effects of the regulations within the established time frames for their review. In promulgating the QM and QRM regulations, the federal agencies attempted to balance the goals of protecting borrowers and investors from the abuses that contributed to the recent housing crisis with the goal of maintaining access to affordable credit. While the QM and QRM regulations likely will have limited initial effects in the current mortgage market, the long-term implications of the regulations on the mortgage market depend on several factors that are difficult to predict. As such, it will be important for the agencies to conduct retrospective reviews of these regulations. However, federal agencies’ efforts to prepare for examining the QM and QRM regulations have not yet incorporated some important elements of effective reviews as described below. Although CFPB, HUD, and the QRM agencies identified potential data sources (such as HMDA and NMDB), these data sources do not maintain information needed to reliably identify QM and QRM loans. CFPB and FHFA have been taking steps to expand these data sources. However, it is not clear if the expanded data will be available for the initial reviews. HUD has not identified specific metrics, baselines, or analytical methods to conduct its analyses. Although the QRM agencies identified potential analytical methods to conduct their analyses, they have not identified specific metrics and baselines. The six agencies conducting the review of the QRM regulations have not specified mechanisms to promote effective collaboration, such as agreements on agency roles and responsibilities. Finalizing plans to retrospectively review the mortgage regulations and incorporating these key elements will better position the agencies to measure the effects of the regulations and identify any unintended consequences. The agencies also could better understand data limitations and methodological challenges and have sufficient time to develop methods to deal with these limitations and challenges. Furthermore, the QRM agencies could identify opportunities to effectively collaborate and assign duties and responsibilities to help ensure effective use of available resources. We are making the following three recommendations. To enhance the effectiveness of its preparations for conducting a retrospective review of its QM regulations, CFPB should complete its plan. The plan should identify what outcomes CFPB will examine to measure the effects of the regulations and the specific metrics, baselines, and analytical methods to be used. Furthermore, to account for and help mitigate the limitations of existing data and the uncertain availability of enhanced datasets, CFPB should include in its plan alternate metrics, baselines, and analytical methods that could be used if data were to remain unavailable. To enhance the effectiveness of its preparations for conducting a retrospective review of its QM regulations, HUD should develop a plan that identifies the metrics, baselines, and analytical methods to be used. Furthermore, to account for and help mitigate the limitations of existing data and the uncertain availability of enhanced datasets, HUD should include in its plan alternate metrics, baselines, and analytical methods that could be used data were to remain unavailable. To enhance the effectiveness of their preparations for conducting a retrospective review of the QRM regulations, the agencies responsible for the QRM regulations—FDIC, FHFA, Federal Reserve, HUD, OCC, and SEC—should develop a plan that identifies the metrics, baselines, and analytical methods to be used and specify the roles and responsibilities of each agency in the review process. Furthermore, to account for and help mitigate limitations of existing data and the uncertain availability of enhanced datasets, the six agencies should include in their plan alternate metrics, baselines, and analytical methods that could be used if data were to remain unavailable. We requested comments on a draft of this report from CFPB, FDIC, Federal Reserve, FHFA, HUD, OCC, and SEC. We received written comment letters from each of the seven agencies, which are presented in appendixes III through IX. We also received technical comments from the agencies (except OCC) that we incorporated as appropriate. In response to our QM-related recommendations, CFPB concurred and HUD agreed with the draft report recommendations in their comment letters. CFPB stated that it was on track to finish its retrospective review on time. In addition, CFPB provided additional details about the general approach, data, metrics, and analytical methods that were likely to be used in its review. To better recognize these planning steps, we expanded our description of CFPB’s planning efforts, and modified the recommendation to emphasize that CFPB should complete its plan. In response to our QRM-related recommendations, two of the six agencies (HUD and FDIC) stated that they agreed with the recommendations in their comment letters. The other four agencies (the Federal Reserve, FHFA, OCC, and SEC) did not explicitly agree with our recommendations but outlined activities or efforts related to planning for the retrospective review of the QRM definition. For example, the agencies discussed their ongoing data analysis of mortgage market trends and efforts to identify sources for data not currently available, such as debt-to- income ratios and points and fees. Furthermore, SEC identified several potential metrics it could use to examine the QRM definition. For example, SEC expects to examine delinquencies by debt-to-income ratios, among other things. The Federal Reserve noted that it was fulfilling much of our recommendation as part of its regular business operations. However, the agencies did not provide specific time frames for finalizing their approach for the retrospective reviews or how they plan to address uncertainty about the availability of key data needed for the review, such as debt-to-income ratios. For example, the Federal Reserve and SEC stated that their precise analytical approach to reviewing the definition of QRM will depend on data availability and mortgage market conditions. Additionally, all the agencies indicated that they planned to work collaboratively in conducting their retrospective reviews. FHFA and OCC stated they planned to begin preparing for the review after the QRM definition was effective (December 2015). Finally, two letters identified some mechanisms that could promote effective collaboration. For example, FDIC and SEC noted that the agencies intended to divide responsibilities according to agency expertise and resources. But the agencies could and should be doing more to finalize their plans to retrospectively review the mortgage regulations. As we discussed in the draft report, agencies can be better prepared to undertake their reviews and may be able to overcome or mitigate data challenges by identifying specific data sources, metrics, baselines, and analytical methods well before conducting the review, ideally before promulgating the rule. It will be particularly important to have plans that address these elements because of the uncertainty about when and if needed data will be available, which may necessitate consideration of alternative analytic strategies and data sources Incorporating these key elements also will better position the agencies to measure the effects of the regulations and identify any unintended consequences. The comment letters of the agencies involved in the QRM reviews also outlined a general approach to collaboration. However, without establishing a specific framework for collaboration, such as specifying the roles each agency will play and their responsibilities and defining and articulating a common outcome, the agencies involved in the QRM reviews may be limited in their ability to measure the effects of the regulations within the established time frames for their review. As agreed with your offices, unless you publicly announce the contents of this report earlier, we plan no further distribution until 30 days from the report date. At that time, we will send copies of this report to the Chairs of FDIC, the Federal Reserve, and SEC; Comptroller of the Currency; Directors of CFPB and FHFA; and the Secretary of HUD; and other interested parties. In addition, the report is available at no charge on the GAO website at http://www.gao.gov. If you or your staff have any questions about this report, please contact me at (202) 512-8678 or sciremj@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs are listed on the last page of this report. GAO staff who made major contributions to this report are listed in appendix X. This report (1) describes selected trends in the origination and securitization of residential mortgages in 2000–2014; (2) discusses the expected effects of the qualified mortgage (QM) and qualified residential mortgage (QRM) regulations on the residential mortgage market; and (3) examines the extent to which federal agencies have plans in place to monitor and assess the effects of the QM and QRM regulations on the residential mortgage market. To describe trends of residential mortgages from 2000 through 2014, we reviewed a range of mortgage market data generated by federal agencies, mortgage market participants, and observers and identified indicators that may be useful to gauge the effects of QM and QRM regulations. We selected indicators associated with the origination and securitization of residential mortgages (including the volume of originations by certain characteristics, interest rates, foreclosure and default rates, and volume of mortgage-backed security issuances) that are described below: To describe the volume of mortgage originations by certain characteristics, we relied on summary data published by Inside Mortgage Finance and data provided by CoreLogic LLC. For example, we examined Inside Mortgage Finance data describing the volume of originations by loan type—including conventional conforming, Alt-A, subprime, jumbo, and government-insured; type of interest rate (fixed- and adjustable-rate); and loan purpose (purchase and refinance). The Inside Mortgage Finance summary data do not include loans guaranteed by the Department of Agriculture. We did not independently confirm the accuracy of the Inside Mortgage Finance data. To determine the reliability of the data, we reviewed publicly available information on the data source and queried a knowledgeable official about the accuracy of the data. In addition, we examined CoreLogic LLC data describing the volume of loan originations by borrowers’ credit score, debt-to-income ratio, and loan- to-value ratio. The CoreLogic summary data include conventional loans as well as loans insured or guaranteed by the Federal Housing Administration and other federal programs. These data are restricted to first-lien mortgages for the purchase of properties. CoreLogic officials estimated 99 percent of the loans were for single-family residential properties (1-4 units). These data provide wide coverage of the national mortgage market—that is, approximately 85 percent of mortgages, according to CoreLogic officials. Due to the proprietary nature of CoreLogic’s estimates of its market coverage, we could not directly assess the reliability of this estimate. We have used CoreLogic data in prior reports in which we concluded the data were sufficiently reliable for our purposes. Nevertheless, because of limitations in the coverage and completeness of the data, our analysis may not be representative of the mortgage market as a whole. To determine the reliability of the CoreLogic data, we reviewed information on the data source and queried a knowledgeable official about the process CoreLogic used to collect its data and generate the summary data. Although the CoreLogic data have certain limitations— for example, certain data fields are not fully reported—we concluded that the data we used were sufficiently reliable for our purposes. To describe mortgage interest rates, we relied on published data in Freddie Mac’s Primary Mortgage Market Survey. To determine the reliability of these data, we reviewed publicly available information on the data source. We determined the data were sufficiently reliable for our purpose, which was to provide information about how residential mortgage interest rates had changed over the relevant time period. To describe the volume of mortgages in default and foreclosure and recession periods, we relied primarily on a prior GAO report that identified and analyzed key national housing market indicators.used data collected for the prior report and reviewed our prior data reliability assessment. Based on this review, we determined that the data were reliable for our purposes. To update the data and analyses, we relied on several data sources including the National Delinquency Survey data issued by the Mortgage Bankers Association, and data issued by the National Bureau of Economic Research. Generally, we updated our assessments of the reliability of these data by reviewing existing information about data quality and corroborating key information. We determined that the data were sufficiently reliable for our purposes. To describe the volume of mortgage-backed security issuances, we relied on summary data published by Inside Mortgage Finance. We did not independently confirm the accuracy of the data we obtained. However, we reviewed publicly available information on the data source and queried a knowledgeable official about the accuracy of the data. We determined these data were sufficiently reliable for our purposes. To discuss the expected effects of the QM and QRM regulations on the residential mortgage market, we identified and reviewed 24 economic analyses examining the potential effects of these regulations. We identified these analyses through means that included consultation with subject-matter experts (internal and external to GAO), electronic searches of scholarly databases, and reviews of studies conducted by agencies to inform the rulemakings. Generally, the analyses examined the effects the regulations may have on the cost, origination, availability, and securitization of residential mortgages and were performed by federal agencies, academics, industry observers, and industry participants. To review the 24 analyses, we designed a data collection instrument to ensure we collected consistent information from each. To develop the data collection instrument we identified important characteristics for high- quality analyses from sources that included internal GAO guidance on reviewing economic analyses and other federal requirements and best practices for conducting economic reviews during the rulemaking process. GAO staff separately subjected each analysis to a primary and secondary review and independently verified that the collected information was accurate. The staff also used the data collection instrument to identify methodologies and any methodological concerns that may have precluded us from using the economic analyses. We did not exclude any of the economic analyses from our review. The team reviewed the information collected to identify trends across the analyses and identify estimated effects of the regulations. We believe the economic analyses are generally reliable for reporting the range of estimates of the effects of the regulations. We noted instances in which the analyses may have had methodological challenges or data were either missing or unreliable. We discussed any specific concerns about methodology or scope in this report. In addition to the 24 analyses, we reviewed three studies on the initial effects of the QM regulations that were conducted after the rule became effective. (See app. II for a list of the 27 studies we reviewed.) We did not apply our data collection instrument to these studies, but reviewed the findings and the methodologies of these studies. We believe the three studies were sufficiently reliable for the purposes of describing immediate effects of the QM regulations. We also reviewed additional sources that contained information about potential effects of the QM and QRM regulations on the residential mortgage market. For example, we reviewed Federal Register releases and comment letters associated with the promulgation of the QM and QRM regulations. We also interviewed agency officials, stakeholders, and others to obtain their viewpoints about potential effects of these regulations. For example, we interviewed officials from the Consumer Financial Protection Bureau (CFPB), Department of Housing and Urban Development (HUD), Department of the Treasury’s Office of Financial Research, Federal Deposit Insurance Corporation (FDIC), Federal Housing Finance Agency (FHFA), Board of Governors of the Federal Reserve System (Federal Reserve), Financial Stability Oversight Council, Office of the Comptroller of the Currency (OCC), and Securities and Exchange Commission (SEC). Stakeholders and others we interviewed included credit rating agencies; groups representing mortgage lenders, securitizers, and investors; groups representing consumer interests; and academics. We chose these groups and individuals because they had a range of views. To examine the extent to which agencies have plans in place to monitor and assess the effects of the QM and QRM provisions on the residential mortgage market, we identified and reviewed requirements and guidance relating to agencies’ efforts to monitor and assess regulations (criteria). Specifically, we reviewed provisions of the Dodd-Frank Wall Street Reform and Consumer Protection Act (Dodd-Frank Act) that requires CFPB to assess its significant rules and publish a report of its assessment. We also identified and reviewed Executive Orders related to agencies’ efforts to conduct retrospective reviews. Moreover, we identified and reviewed Office of Management and Budget (OMB) memorandums associated with these Executive Orders. Finally, we reviewed prior GAO reports that examined agencies efforts to conduct retrospective reviews of regulations. To examine efforts and plans to monitor and assess the effects of the QM and QRM regulations, we focused our review on the retrospective review activities of CFPB, HUD, and the six agencies responsible for the QRM regulations—FDIC, FHFA, Federal Reserve, HUD, OCC, and SEC. We did not evaluate the efforts of the Departments of Agriculture and Veterans Affairs to review their QM regulations because they had not promulgated their own rules when we began our analysis and because their programs represent a smaller portion of the residential mortgage market. To understand federal agencies’ efforts and plans to monitor and assess the effects of the QM and QRM regulations, we reviewed Federal Register releases and other agency documents pertaining to retrospective reviews. For example, we identified and reviewed agency publications that contained plans to conduct retrospective reviews of the QM and QRM regulations, such as CFPB’s 2013 and 2014 strategic plans, as well as HUD’s final QM regulations, its 2014 and 2015 retrospective review plan, and its 2014-2018 strategic plan. During our review, we also examined CFPB’s efforts to expand reporting requirements for Home Mortgage Disclosure Act (HMDA) data and examined the extent to which the expanded reporting might include data useful to monitor and assess the QM and QRM regulations. For example, we reviewed CFPB’s 2014 proposed rule to expand HMDA reporting. Similarly, we reviewed FHFA’s efforts to develop a National Mortgage Database and the extent to which it may include data to monitor and assess the QM and QRM regulations. We also interviewed federal agency officials (from CFPB, FDIC, FHFA, Federal Reserve, HUD, OCC, and SEC) about their plans to conduct retrospective reviews of the QM and QRM regulations. We conducted this performance audit from November 2013 to June 2015 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. American Bankers Association. 21st Annual ABA Real Estate Lending Survey Report. Washington, D.C.: 2014. Ashworth, Roger, Laurie Goodman, Brian Landy, and Lidan Yang. “The Coming Crisis in Credit Availability.” Amherst Mortgage Insight. May 30, 2012. Bai, Bing. Board of Governors of the Federal Reserve System. July 2014 Senior Loan Officer Opinion Survey on Bank Lending Practices. Washington, D.C.: August 4, 2014. Board of Governors of the Federal Reserve System. Changes in U.S. Family Finances from 2007 to 2010: Evidence from the Survey of Consumer Finances. Washington, D.C.: June 2012.Board of Governors of the Federal Reserve System. Report to the Congress on Risk Retention. Washington, D.C.: October 2010. Bureau of Consumer Finance Protection. Ability-to-Repay and Qualified Mortgage Standards under the Truth in Lending Act. Washington, D.C.: January 2013. Coalition for Sensible Housing Policy. Updated QRM Proposal Strikes Balance: Preserves Access While Safeguarding Consumers and the Markets. Washington, D.C.: October 24, 2013. DBRS. Assessing U.S. RMBS Pools under the Ability-to-Repay Rules. New York, N.Y.: May 2014. Department of Housing and Urban Development. Economic Analysis Statement: Qualified Mortgage Definition for Insured or Guaranteed Single Family Mortgages. Washington, D.C.: November 2013. Department of Housing and Urban Development. Economic Analysis Statement: Qualified Mortgage Definition for Insured or Guaranteed Single Family Mortgages. Washington, D.C.: (undated). Federal Housing Finance Agency. “Qualified Residential Mortgages.” Mortgage Market Note, 11-02. Washington, D.C.: April 11, 2011. Fitch Ratings. U.S. RMBS Qualified and Nonqualified Mortgage Criteria. New York, N.Y.: March 2014. Goldman Sachs. “Assessing the Impact of QM.” The Mortgage Analyst. New York, N.Y.: October 10, 2013. Moody’s Analytics. Moody’s Approach to Assessing Incremental Risk Posed by the Ability-to-Repay Rules in U.S. RMBS. New York, N.Y.: March 25, 2014. Moody’s Analytics. Cost of Housing Finance Reform. New York, N.Y.: November 2013. Mortgage Bankers Association. MBA Comment on Reopened Comment Period for QM Rule. Washington, D.C.: July 9, 2012. Office of Financial Research. 2013 Annual Report. Washington, D.C.: December 2013. Quercia, Roberto G., Lei Ding, and Carolina Reid. Balancing Risk and Access: Underwriting Standards and Qualified Residential Mortgages. Chapel Hill, N.C.: Center for Community Capital at the University of North Carolina, and Center for Responsible Lending, January 2012. Reid, Carolina, and Roberto G. Quercia. Risk, Access, and the QRM Reproposal. Chapel, Hill, N.C.: Center for Community Capital at the University of North Carolina, September 2013. Schwartz, Faith A., Margarita S. Brose, and Stuart I. Quinn. QRM and Risk Retention Standards: Foundations for a Sound Housing Market. Irvine, Calif.: Corelogic, December 2013. Schwartz, Faith A. and Margarita S. Brose. ATR/QM Standards: Foundations for a Sound Housing Market. New York, N.Y.: CoreLogic, February 12, 2013. Seidman, Ellen, Jun Zhu, and Laurie Goodman. “QRM, Alternative QRM: Loan Default Rates.” Urban Wire: Housing and Housing Finance. Washington, D.C.: Urban Institute, October 17, 2013. Seidman, Ellen, Jun Zhu, and Laurie Goodman. “QRM vs. Alternative QRM: Quantifying the Comparison.” Urban Wire: Housing and Housing Finance. Washington, D.C.: Urban Institute, October 7, 2013. Standard and Poor’s. Methodology and Assumptions for Adjusting RMBS Loss Severity Calculations for Loans Covered under Ability-to-Repay and Qualified Mortgage Standards. New York, N.Y.: January 23, 2014. The Center for Responsible Lending, Consumer Federation of America, and The Leadership Council on Civil and Human Rights. Request for Comment on Qualified Mortgage. Durham, N.C.: July 9, 2012. White, Joshua, and Scott Bauguess. Qualified Residential Mortgage: Background Data Analysis on Credit Risk Retention. Washington, D.C.: Securities and Exchange Commission (Division of Economic and Risk Analysis), August 2013. In addition to the individual named above, Harry Medina (Assistant Director), Anne A. Akin (Analyst-in-Charge), Emily Chalmers, Tisha D. Derricotte, Donald P. Hirasuna, Robert D. Lowthian, John McGrail, Barbara Roesmann, Jena Sinkfield, Andrew Stavisky, and Jim Vitarello made major contributions to this report. Timothy Bober and Janet Eackloff also contributed to this report.

Summary: Amid concerns that risky mortgage products and poor underwriting standards contributed to the recent housing crisis, Congress included mortgage reform provisions (QM and QRM) in the Dodd-Frank Wall Street Reform and Consumer Protection Act. CFPB's regulations establishing standards for QM loans became effective in January 2014. More recently, six agencies jointly issued the final QRM rule that will become effective in December 2015. GAO was asked to review possible effects of these regulations. This report (1) discusses views on the expected effects of the QM and QRM regulations, and (2) examines the extent of agency planning for reviewing the regulations' effects, among its objectives. GAO's methodologies included identifying and reviewing academic, industry, and federal agency analyses on the expected effects of the regulations. GAO also reviewed federal guidance on retrospective reviews and interviewed agency officials to assess agency efforts to examine the effects of the QM and QRM regulations. Federal agency officials, market participants, and observers estimated that the qualified mortgage (QM) and qualified residential mortgage (QRM) regulations would have limited initial effects because most loans originated in recent years largely conformed with QM criteria. The QM regulations, which address lenders' responsibilities to determine a borrower's ability to repay a loan, set forth standards that include prohibitions on risky loan features (such as interest-only or balloon payments) and limits on points and fees. Lenders that originate QM loans receive certain liability protections. Securities collateralized exclusively by residential mortgages that are “qualified residential mortgages” are exempt from risk-retention requirements. The QRM regulations align the QRM definition with QM; thus, securities collateralized solely by QM loans are not subject to risk-retention requirements. The analyses GAO reviewed estimated limited effects on the availability of mortgages for most borrowers and that any cost increases (for borrowers, lenders, and investors) would mostly stem from litigation and compliance issues. According to agency officials and observers, the QRM regulations were unlikely to have a significant initial effect on the availability or securitization of mortgages in the current market, largely because the majority of loans originated were expected to be QM loans. However, questions remain about the size and viability of the secondary market for non-QRM-backed securities. Agencies have begun planning their reviews of the QM and QRM regulations (due January and commencing December 2019, respectively); however, these efforts have not included elements important for conducting effective retrospective reviews. Federal guidance encourages agencies to preplan their retrospective reviews and carefully consider how best to promote empirical testing of the effects of rules. To varying degrees, the relevant agencies have identified outcomes to examine, potential data sources, and analytical methods. But existing data lack important information relevant to the regulations (such as loan performance or borrower debt to income) and planned data enhancements may not be available before agencies start the reviews. The Bureau of Consumer Financial Protection (CFPB) has proposed expanding Home Mortgage Disclosure Act data reporting requirements, but the earliest that the enhanced data will be available is 2017. Similarly, the Department of Housing and Urban Development (HUD) identified how it intends to examine its QM regulations and some potential data sources but has yet to determine how it would measure the effects of these regulations, including metrics, baselines, and analytical methods. Agencies also have not specified how they will conduct their reviews, including determining which data and analytical methods to use. Finalizing plans to retrospectively review the mortgage regulations will position the agencies to better measure the effects of the QM and QRM regulations and identify any unintended consequences. Additionally, the agencies could better understand data limitations and methodological challenges and have sufficient time to develop methods to deal with these limitations and challenges. CFPB, HUD, and the six agencies responsible for the QRM regulations should complete plans to review the QM and QRM regulations, including identifying specific metrics, baselines, and analytical methods. CFPB, HUD, and one QRM agency—the Federal Deposit Insurance Corporation—concurred or agreed with the recommendations. The other QRM agencies did not explicitly agree with the recommendations, but outlined ongoing efforts to plan their reviews.