The National Housing Act authorized HUD’s Office of Housing to accept assignment of and sell defaulted single-family mortgage loans. Additionally, Office of Management and Budget (OMB) Circular No. A-11 (2016) states that under the Debt Collection Improvement Act of 1996, credit agencies with over $100 million in loan assets are expected to sell defaulted loan assets that are more than 1 year delinquent, with some exceptions. The OMB Circular further states that the agency may not be required to sell loan assets if a serious conflict exists between selling loans and policy goals. In 2017, FHA insured over $1 trillion in single- family mortgage loans, including more than 200,000 loans in default. Consistent with the National Housing Act and OMB Circular, FHA uses DASP to reduce its backlog of defaulted loans by selling loans that are severely delinquent. As of 2016, loans must be at least 8 months delinquent to be eligible for sale through DASP. In addition, servicers must evaluate borrowers for all FHA loss mitigation options in order for loans to be eligible for sale through DASP. FHA has called its single-family forward loan sales program by different names over the years, but it became known as DASP beginning with FHA’s third loan sale in 2012. We use DASP throughout this report to refer to FHA loan sales, regardless of the timing or the program name. Between 2010 and 2016, FHA held a total of 16 sales, with between one and four sales annually. As seen in figure 1, the number of loans sold varied significantly among the sales. Figure 2 shows the extent to which FHA has sold defaulted loans in each state in 2013-2016. The map also indicates states with longer expected foreclosure timelines. The foreclosure process is governed by state laws and differs across states. FHA establishes expected timelines for completing foreclosure and acquiring title to the property in each state. As discussed later, the foreclosure process involves a number of costs, which may be higher in states with longer expected foreclosure timelines. Additional information on the loans sold through DASP can be found in appendix II. A loan becomes delinquent after the borrower misses a single payment and goes into default after it is at least 31 days—two full payments—past due, including when a borrower may miss payments sporadically over time without repaying the missed amount. Loan servicers—which can be large mortgage finance companies or commercial banks—are responsible for accepting payments from borrowers and managing mortgages. FHA requires the servicers to provide monthly reports on each loan with one or more missed payments through its Single Family Default Monitoring System (default monitoring system). Before initiating foreclosure actions, FHA requires servicers to contact the borrower, collect information on the borrower’s finances, and evaluate the borrower using the following ordered steps, referred to as the waterfall of loss mitigation priorities: informal forbearance through an oral agreement allowing for reduced or suspended payments for a period of 3 months or less; formal forbearance with written repayment plans, which combine a suspension or reduction in monthly mortgage payments with a repayment period; special forbearance of up to 12 months for borrowers who are unemployed; FHA-Home Affordable Modification Program (HAMP), which works to get a borrower to return to making regular payments (reperforming); FHA-HAMP offers qualified borrowers a loan modification that results in an affordable monthly payment amount that does not exceed 40 percent of the borrower’s gross monthly income by reamortizing the debt for a new 30-year term at a fixed interest rate at or below the market rate and, under certain circumstances, deferring the payment of principal through the use of a partial claim; and non-retention disposition methods, including a preforeclosure sale (also known as a short sale) in which the borrower sells a property and the mortgage is satisfied for less than the amount that is owed, or deed-in-lieu of foreclosure in which the borrower voluntarily transfers a property to FHA to release all mortgage obligations; FHA may also provide move-out incentive payments to borrowers for short sales and deeds-in-lieu of foreclosure. To qualify for most of these actions, borrowers must be in default. A servicer must evaluate a borrower for the loss mitigation options monthly, but a borrower may not qualify for any option. However, a borrower’s circumstances are fluid and eligibility can change. For example, borrowers who previously did not qualify for any loss mitigation options could be eligible to be evaluated for loss mitigation options again after starting a new job. FHA provides servicers with incentive payments of varying size for taking certain loss mitigation actions. FHA generally requires servicers to either use a loss mitigation option for which a borrower qualifies or initiate foreclosure within 6 months of the default date, but a loan also may become eligible for disposition through a DASP sale when loss mitigation has been exhausted and it meets other eligibility criteria. FHA provides servicers with a list of loan eligibility criteria in the servicer agreement for each sale. Servicers use the criteria to identify which loans are eligible for a DASP sale. For example, eligibility criteria include that a loan must be FHA-insured, have no more than four dwelling units, and have an unpaid principal balance (amount owed) greater than $20,000. Other criteria relate to length of delinquency, loan-to-value (LTV) ratio, and the condition of the property. Loans that qualify for loss mitigation or have a foreclosure date scheduled or completed during the sale period are not eligible for DASP. Information on changes to loan eligibility criteria throughout the history of the program can be found later in this report. Each of the disposition methods FHA uses when loss mitigation on defaulted loans is exhausted has different costs to FHA’s MMI Fund (see table 1). For the nonretention disposition methods of short sale, deed-in- lieu of foreclosure, third-party sale, or foreclosure—which we refer to as “out of home” methods—FHA pays a claim to the servicer in the amount of the unpaid mortgage balance and other expenses. In addition, for a deed-in-lieu of foreclosure or foreclosure—in which the property enters HUD’s inventory of real estate owned (REO) property—FHA also incurs costs associated with maintaining, repairing, and selling the property. This generally results in a greater loss to the MMI Fund. In the case of a DASP sale, FHA avoids interest and servicing costs during the foreclosure period as well as REO-related expenses, but incurs the cost of the difference between the unpaid balance and expenses and the amount FHA receives for the loan it sells. The loan sale process has three distinct phases: presale, due diligence and bid, and postsale (see figs. 3, 4, and 5, respectively). FHA contractors (the transaction specialist, the compliance analytics contractor, and the program financial advisor) facilitate and perform various tasks throughout these phases. The summary below reflects the process according to 2016 sales documents (the most recent DASP sales documents available), other supplemental information, and interviews with FHA officials and contractors. Figure 3 shows the presale phase. During this phase, FHA or its contractor notifies interested servicers and communicates loan eligibility criteria to servicers through the servicer agreement. Servicers that plan to participate in the sale identify a list of eligible loans, certify the accuracy and eligibility of the loans, and provide the list to FHA for review through the Claim Submission Report. The servicer uploads information on the loans submitted to FHA. FHA creates the submitted loan database, which includes each accepted loan’s current unpaid balance, payment history, and an estimate of the underlying property value. According to FHA staff, FHA reviews the eligible loans submitted by servicers and, with the advice of its transaction specialist contractor, groups them into pools based on geography and other factors. FHA sells loans in national pools or Neighborhood Stabilization Outcome (NSO) pools, for which purchasers must meet specific neighborhood stabilization outcomes for 50 percent or more of the properties in the pool. Next, an FHA contractor notifies prospective purchasers about the upcoming sale via email, and notices are posted in the Federal Register, industry publications, and newspapers. Purchasers can include private equity firms, hedge funds, rental housing companies, and nonprofit organizations. Prospective purchasers must submit to FHA a Confidentiality Agreement and a Qualification Statement. FHA reviews the documentation to determine whether the purchaser qualifies to participate in the sale. Figure 4 depicts the due diligence and bid phase of a DASP sale. During this phase, prospective purchasers receive access to the data room—a shared data website—to review materials including the loan information provided by servicers (due diligence materials); bid instructions; and sale agreement that describes representations, warranties, and postsale requirements, among other things. The servicer, FHA staff, and FHA contractors continue to verify the eligibility of the loans. Prospective purchasers place bids on each loan in a pool and deposit a percentage of their total bid amount. FHA evaluates the bids and selects the highest bidder for each pool based on the total of the loan-level bids. FHA then notifies that bidder and provides an executed purchaser agreement that describes postsale servicing and reporting requirements. Purchasers must agree to follow the terms of the purchaser agreement including avoiding finalizing foreclosures for 6 or 12 months (depending on whether the sale occurred prior to July 2015), evaluating borrowers for loan modification, and reporting outcomes to FHA. Figure 5 depicts the postsale phase. During the postsale phase, FHA provides the list of sold loans to the servicer and winning purchaser, which together determine servicing transfer dates. After bid day, servicers verify that loans continue to meet eligibility criteria for the sale and begin submitting insurance claims to FHA. Purchasers pay FHA for the loans that are sold, and servicers transfer loan information and complete mortgage files to the purchasers. When servicers submit claims to FHA for sold loans, they must report the reason any loans are not transferred. For example, a loan might not be transferred due to ongoing loss mitigation activity or another reason, such as no longer meeting delinquency eligibility criteria, and would remain with the servicer and FHA insured. Following the final transfer of loan documentation, servicing is transferred from the servicer to the purchaser. The servicer notifies the borrowers of the transfer of servicing and termination of their FHA mortgage insurance. Following the transfer, the purchaser sends the borrowers a similar notice of transfer and any required disclosures. Following the final settlement date, the purchaser submits the first of 16 quarterly reports on the status of the sale portfolio using the format provided in FHA’s Post-Sale Reporting tool. If a purchaser demonstrates a pattern of failing to report, FHA may disqualify the purchaser from future sales. During the first 12 months of the reporting period, purchasers must evaluate borrowers for a HAMP modification or a substantially similar modification. Additionally, the purchaser must avoid foreclosure for 12 months unless the home is vacant or there are extenuating circumstances. The purchaser agreement allows the purchaser 10 months starting with the servicing transfer date to notify HUD of any alleged breach of FHA’s representations and warranties on purchased loans. For example, a breach could be that a loan does not meet eligibility requirements, is not covered by a valid hazard insurance policy, or has an outstanding mechanic’s lien. After notifying the original servicer and reviewing any response, FHA determines whether there is a breach and the appropriate remedy. The breach remedy can include a cure of the breach (such as by the servicer paying an outstanding lien), reduction in claim payment, or repurchase by the servicer. The servicer has 60 days to comply with the remedy. If a breach results in the repurchase of the loan by the original servicer, the purchaser will transfer servicing back to the original servicer. FHA made changes to DASP by adding borrower protections and made efforts to increase the participation of nonprofit organizations. FHA also changed loan eligibility criteria and bidding processes to increase recoveries to the MMI Fund. Other changes included automating and streamlining processes. FHA has added to DASP protections for borrowers and requirements to help stabilize neighborhoods in response to concerns raised by various stakeholders. For example, borrower protections included extending the moratorium on foreclosures from 6 months to 12 months and requiring the purchaser to offer a HAMP or substantially similar modification to qualified borrowers beginning with its July 2015 loan sale. In September 2016, FHA also added payment shock protection, which limited increases in a borrower’s interest rate to 1 percent per year following a 5-year reduced rate period. In an effort to stabilize neighborhoods, FHA added a requirement in 2016 prohibiting purchasers from walking away from vacant properties. In a hearing before the House Committee on Financial Services in July 2016, the HUD Secretary stated that the changes that FHA made to the program in 2015 and 2016 were designed with input from a broad range of stakeholders and were assessed for how well the changes would fulfill the agency’s goal of strengthening neighborhoods. In 2015, FHA made several outreach efforts to expand the participation of nonprofit organizations in DASP. These efforts included offering nonprofit organizations a “first look” at vacant REO properties, allowing purchasers to resell to nonprofit organizations, and conducting a webinar to educate and encourage the participation of nonprofit organizations. These efforts came about following a September 2014 report from the Center for American Progress and suggestions from other stakeholders that FHA make it easier for nonprofit organizations to participate in DASP. In 2016, FHA set a target that 10 percent of bids come from nonprofit organizations and local governments, including offering loans in targeted distressed areas. In 2015 and 2016, FHA offered nine pool sales directed at nonprofit organizations only. Some members of Congress expressed concern over FHA’s efforts to encourage participation of nonprofit organizations, stating that FHA would likely get lower bids than it would normally receive from private companies. According to FHA officials, FHA changed its loan eligibility criteria for inclusion in DASP sales in order to decrease losses to the MMI Fund and to give servicers more time to work with borrowers on loss mitigation. FHA lists the eligibility criteria to qualify loans for FHA’s loan sale program in each servicer agreement. Our analysis of the servicer agreements from 2010 through 2016 showed that some criteria remained the same during the period, such as the requirement that servicers must have evaluated borrowers for all loss mitigation actions in accordance with FHA regulations or that loans in certain types of bankruptcy were ineligible. Other criteria changed during that period, including the following examples: Delinquency requirements for eligible loans changed from six full payments past due to eight full payments past due beginning with the first DASP sale in 2016; and FHA changed its eligible LTV ratio. Between the 2010 sale and the second DASP sale in 2012, FHA set a minimum LTV ratio for loan sales at 85 percent or higher—meaning that to qualify for sale, the ratio of the amount owed on the loan to the estimated value of the property was required to be 85 percent or higher. Beginning with the first DASP sale in 2015, FHA set minimum eligible LTV ratios by state—70 percent in New York and New Jersey and 85 or 100 percent for other states, with about half the states in each percentage category. FHA officials said that they analyzed loan-level bid amounts and found that they had greater recoveries relative to REO disposition on loans with shorter delinquencies and higher LTV ratios. According to the officials, this was because these loans had a higher probability of modification by purchasers. Further, they said that the changes in eligibility criteria related to delinquency and LTV ratio were intended to decrease losses to the MMI Fund. In addition, FHA lowered limits on loan-level bid pricing to minimize the potential negative effects of ineligible loans being removed from sales after bidding. Purchasers could use loan-level bid pricing to strategically take advantage of the expected removal of ineligible loans after bidding. Because a purchaser pays only for the loans that are actually transferred and some loans are removed from sales due to ineligibility, such as due to changes in loss mitigation or foreclosure status, FHA receives less in actual returns on the sale than the winning—highest—bid. For selected loan pools in the second sale in 2013 and the first sale in 2014, FHA analyzed the bid amounts of loans that became ineligible after purchasers had bid. Before the 2015 sale, FHA lowered its maximum purchasers’ loan-level bid amount from 200 to 175 percent of the unpaid balance of a loan. FHA contractors deployed tools in 2015 and 2016 to automate previously manually intensive processes of collecting data and emails from about 30 different purchasers and tracking the status of sold loans. FHA, contractors, and purchasers we interviewed said that these processes improved data quality, efficiency, and communication among parties. A postsale reporting tool and data repository enables the contractor to send mass emails and target email reminders of upcoming due dates, including report deadlines, to purchasers that have not submitted required documents. In addition, the tool validates data by checking for logic and data type. A loan sale system conducts automated checks of data in the submitted loan database for completeness and accurate file layout. The system also checks whether all required documents are included on the shared data website that purchasers use to perform due diligence and determine bid amounts. The system automatically generates a report of errors that is sent to servicers. A web-based breach tracking tool that streamlines and centralizes tracking of loans that breach—that is, were transferred to purchasers but did not meet eligibility standards. The tool allows the purchasers to submit breach requests, notifies servicers automatically about pending breaches, and allows auction stakeholders to review breaches and update the status of the loan. Servicers identify eligible loans for inclusion in a DASP sale, certify eligibility, and update loan information and remove ineligible loans prior to bid day. FHA staff and contractors described the various checks they conduct to generally verify a loan’s continued eligibility by reviewing the loan’s default status in FHA’s default monitoring system and in some cases other servicer data before a sale. Specifically, both FHA staff and the compliance analytics contractor conduct eligibility tests by checking each submitted loan’s default status. The transaction specialist contractor told us it conducts automated checks of the loan submission and related data that servicers submit to check for data completeness and valid formatting. Additionally, this contractor also checks that the loans match eligibility criteria and that all required documents were submitted. Starting in 2015, FHA officials told us that FHA and its three primary contractors began to verify that all loans submitted for sale had an eligible default status as part of their quality-control process. FHA officials said that any updates or changes servicers make to the status of submitted loans require the program financial advisor contractor to repeat its quality- control procedures. In addition, servicers are expected to ensure that loans meet eligibility criteria until the loan is sold and servicing responsibilities are transferred to the purchaser. The servicer agreement states that an eligible mortgage loan meets all eligibility criteria as of the date it is submitted for sale and continues to meet all such requirements as of the claim date. FHA officials said that servicers check eligibility at the loan submission date, approximately 3 weeks prior to the bid day when they update loan information, and at the claim date. Servicers should remove ineligible loans from the sale. In 2014, FHA required servicers to self-certify the accuracy of the default status of loans. FHA officials told us that it also has absolute discretion to exclude one or more loans from the sale. According to FHA officials, FHA has two different provisions in place to correct when a loan should not have been sold. One provision, as described earlier, allows the purchaser to initiate the breach process and the servicer either corrects the reason for the breach or FHA repurchases the loan. Another provision is the “claw-back” provision. Under this provision, FHA or the former servicer can require the purchaser to return the loan to FHA in exchange for the amount the purchaser paid for the loan. However, we found examples of potentially ineligible loans that were submitted for sale and were sold in DASP auctions. Of the 12,210 loans sold in 2016, a small percentage of loans (about 2.65 percent) did not meet eligibility criteria based on their default status on the date loans were submitted. The error rate was similar at the bid date for the 12,210 loans sold in 2016. In particular, about 2.67 percent of these loans did not meet eligibility criteria based on their default status on the bid date. These loans were ineligible for varied reasons, including because they did not meet FHA’s length of delinquency requirement, were involved in certain types of bankruptcy, or were undergoing loss mitigation and therefore should have remained under FHA insurance protection. Ineligible loans may have been sold because the status of loans changed after the servicer and FHA completed their eligibility checks. FHA’s staff and contractors conduct multiple eligibility checks concurrently during the presale and due diligence and bid phases—about 12 to 14 weeks before bid day according to FHA officials. These early checks conducted by FHA’s staff and contractors do not necessarily occur in a specific order or according to specific timelines. FHA officials told us that FHA relies on the servicers to perform eligibility checks a few weeks before bid day and again after the sale when the servicer submits the claim. However, the status of delinquent loans can be very fluid. According to our analysis of FHA data, 23 percent of loans from 2010 to 2016 were removed between the bid date and the claim date. FHA officials told us that servicers remove loans after FHA’s reviews to maintain compliance with representations and warranties under the servicer agreement. FHA officials also explained that loan removal was due to changes in loans’ eligibility status, such as entering into loss mitigation or the scheduling of a foreclosure sale. We reviewed a nongeneralizable sample of 10 loans that appeared to be ineligible and interviewed FHA officials about these loans. We found that some changes in the eligibility of loans could be missed due to the length of time between eligibility checks and data updates. The status of loans can change multiple times during a sale process. FHA requires servicers to self-report the status of defaulted loans on a monthly basis to the default monitoring system, usually within the first 5 days of the month, but servicers may report changes throughout the month if a loan’s status changes. However, FHA officials told us that the system updates once a month. FHA’s eligibility checks may have occurred before the updates were posted to the default monitoring system. FHA officials told us that FHA relies on the controls in place and contractual agreements with the servicers that require them to ensure that loans are eligible when submitted to FHA for sale and when they file a claim with FHA. As a result, FHA may not be aware of a change in loan eligibility that was reported in the default monitoring system after its eligibility checks were completed. Federal internal control standards require that management design control activities to achieve objectives and respond to risks. Control activities can be either preventive or detective. A preventive control activity prevents an entity from failing to achieve an objective or address a risk. Although FHA has implemented a number of controls to prevent ineligible loans from being sold, these controls may miss loans that change status after the eligibility check because FHA staff and contractors do not have a designated time in the process to conduct the eligibility check. Without spacing the timing of the various checks throughout the process, including some checks that occur closer to the bid date, FHA staff and contractors do not have the most reliable and updated data from which to make decisions regarding loan eligibility, and FHA could be selling some ineligible loans. If FHA sells a loan that is ineligible to be sold because of ongoing loss mitigation, it pays a claim for a loan that may become reperforming and never require a claim. Likewise, borrowers could lose access to benefits such as reevaluation for the suite of FHA loss mitigation options. FHA has begun to centralize its existing written guidance, but policies for when program changes should be evaluated are not documented in this guidance. A July 2017 report from the HUD OIG found that HUD did not develop formal guidance or procedures for its single-family note sales program and recommended that the agency develop and implement formal procedures and guidance for DASP. FHA responded to the OIG that the operations of the DASP sales were documented in a series of procedures used internally by staff and externally by stakeholders. In May 2018, FHA officials told us that in response to the OIG’s recommendation, they were consolidating their current written procedures and guidance into one Asset Sales Handbook to centralize the information for internal and external stakeholders. (See app. III for a description of these documents.) FHA officials told us the key documents governing a DASP sale include the servicer agreement, purchaser agreement, detailed instructions for bid day, and specific requirements for qualified servicers. However, we found that if FHA were to compile these existing documents into an Asset Sales Handbook, it would still be missing some important program policies. As of February 2019, FHA officials confirmed that they had no written policies documenting when program changes should be evaluated. When FHA described its process for evaluating program changes, officials stated that the informal practice was to consider changes when planning for a new sale. However, as stated earlier, FHA made a number of changes in 2015 and 2016 but has not held a DASP sale since 2016. FHA officials said the date of the next DASP sale is unknown. FHA also experienced another period when no sales were conducted between 2005 and 2009. Federal internal control standards require that management implement control activities through policies. This includes documenting in policies the internal control responsibilities of the organization and periodically reviewing policies, procedures, and related control activities for continued relevance and effectiveness in achieving the entity’s objectives. For example, the standards state that if there is a significant change in an entity’s process, management reviews the process in a timely manner after the change to determine that the control activities are designed and implemented appropriately. However, FHA officials told us that they had not evaluated whether the most recent program changes were effective or should be revised because they were not planning a new sale yet. With several years between sales, written policies for regular consideration and review of program changes can help to ensure that FHA is reviewing the effectiveness of previous changes and controls and considering potential new changes in a timely manner. FHA has a DASP program objective of maximizing recoveries to the MMI Fund and has some specific targets to assess whether it is meeting this objective. On a quarterly basis, FHA measures how recovery for asset sales compares to foreclosure with REO dispositions and other disposition types, such as short sales and claims without conveyance of title. FHA officials explained that they maximize recovery by holding open and competitive auctions for nonperforming single-family loans, with the highest bidder as the winner. In addition, the Office of Risk develops a reserve price—an estimate of the expected REO recovery value of each loan in a sale and a benchmark for comparison with the bids received—to minimize the risk that FHA will not get the best recovery for the loan. In the past, when FHA received a bid below the reserve price, it opted to not sell the pool. As a result, the reserve price serves as a critical target in the agency’s determination of whether to sell. In contrast, FHA has not developed specific targets for meeting what appear to be additional DASP objectives, based on a variety of program documents and recent program changes. In 2016, for example, the HUD Secretary testified before Congress that DASP has a dual goal— ”support recoveries to the Fund while preserving homeownership and help stabilize neighborhoods.” Similarly, in HUD’s 2016 Post-Sale Report to the FHA Commissioner, HUD explained that it designed DASP “to maximize recoveries to the , and when possible, help keep borrowers—otherwise headed to foreclosure— in the home.” HUD’s recent changes to DASP likewise appear to recognize program objectives in addition to maximizing recoveries to the MMI Fund. When HUD extended the prohibition against foreclosure from 6 months to 12 months in 2015, for instance, a HUD press release stated that such changes “not only strengthen the program but help to ensure it continues to serve its intended purposes of supporting the MMI Fund and offering borrowers a second chance at avoiding foreclosure.” And when HUD changed DASP in 2016 to prohibit purchasers from abandoning low- value properties in high-foreclosure neighborhoods, it declared that this was done to help stabilize neighborhoods. Despite these repeated department statements that DASP has a “two- fold” goal and multiple “intended purposes,” FHA officials told us that preserving homeownership and stabilizing neighborhoods are “ancillary benefits”—positive consequences that flow from DASP’s objective of maximizing recoveries for the MMI Fund—but not objectives themselves. Because FHA does not consider homeownership preservation and neighborhood stabilization to be program objectives, the agency has not developed targets to meet them. FHA officials explained that they measure and monitor the extent to which purchasers meet requirements for NSO pools, for instance, by collecting loan outcome data from purchasers for 4 years. These purchasers must have no less than 50 percent of the loans in each NSO pool achieve outcomes such as keeping borrowers in their homes and properties occupied through rentals. However, FHA does not have a similar target for national pools, which represent about 80 percent of the sold loans. FHA requires purchasers of national pools to report on borrower outcomes quarterly for 4 years, but does not measure the extent to which these outcomes meet a specific target and are achieving program objectives. Prior GAO work identified key attributes of successful performance measures and indicated that performance measures should be clear, have measurable numerical targets, and demonstrate results. In addition, according to federal internal control standards, management should define objectives clearly to enable the identification of risks and define risk tolerances. This includes, for example, defining objectives in specific and measurable terms to allow for the assessment of performance toward achieving objectives. Although FHA officials told us that DASP has one objective with resulting “ancillary benefits,” it also cited these same benefits as additional program goals and purposes in the recent past. Without clarifying the program’s objectives in light of relevant laws, regulations, and agency statements and setting measurable targets to achieve these objectives, particularly for national pools, FHA cannot ensure that DASP is achieving optimal results. FHA has not used performance data to establish criteria for the timing of DASP sales. FHA officials said they have not set criteria for when to hold sales, such as the size of the portfolio of defaulted loans or other considerations. In contrast, Fannie Mae estimates the number of defaulted loans needed to be sold to achieve its goals and assesses market conditions to produce a detailed schedule of sales for the year. Our analysis of FHA’s default monitoring system data shows that several years after the housing crisis, FHA continues to insure a backlog of defaulted loans with six or more missed payments (see fig. 6). FHA officials stated that, in July 2018, FHA had about 300,000 defaulted loans, which is similar to the number of loans as in years when the DASP program was active. Most servicers we talked to told us that they preferred selling defaulted loans through DASP rather than taking them through the REO disposition process due to the servicing responsibility and costs associated with foreclosure. However, FHA officials told us that they did not know when the next sale would be. The GPRA Modernization Act of 2010 established an expectation that agencies use evidence and performance data in decision making. Specifically, the act changed agency performance management roles, planning and review processes, and reporting to ensure that agencies use evidence and performance data in decision making. Our prior work has stated that although the act’s requirements apply at the agency-wide level, they can also serve as leading practices at other organizational levels, such as component agencies, offices, programs, and projects. Because specific criteria for when to hold sales are not in place, FHA’s timing of and decisions to hold DASP sales were inconsistent. FHA held 16 DASP sales between 2010 and 2016. These sales occurred at varying frequencies. For example, FHA held between one and four sales per year, and the number of months between sales ranged from 2 to 10 months. Officials stated that DASP should be used to address a large buildup of defaulted loans and because of its lower loss severity compared with REO dispositions. Officials also told us they have not developed criteria because FHA operates DASP as a pilot program and continues to make changes after each sale. However, without analyzing the performance data of the portfolio of defaulted loans to identify criteria for the timing of DASP sales—even as a pilot program—FHA cannot make fully informed decisions about when to hold sales and may not be optimizing its use of the program in achieving its objectives. FHA does not evaluate loan outcomes for loans sold through DASP and does not monitor the modifications offered by individual purchasers. Our analysis of FHA outcome data found that in aggregate, sold loans were less likely to avoid foreclosure than similar, unsold loans. However, our analysis also found that for some sales and some purchasers, sold loans were more likely to avoid foreclosure compared to unsold loans. A number of factors may contribute to differences in outcomes between sold and unsold loans by sale and purchaser, including increased postsale servicing and reporting requirements and the types of modifications offered by individual purchasers. FHA does not use the data it collects to evaluate outcomes for loans sold through DASP compared to outcomes for similar, unsold loans. We reviewed a contractor report and FHA’s periodic reports on DASP outcomes and found that they lacked critical outcome information. Specifically, in 2017, a contractor analyzed home equity preserved as a result of the foreclosures avoided through DASP, and then estimated the effect of avoided foreclosures on surrounding areas. However, the contractor did not estimate the effect of foreclosure avoidance relative to unsold loans. Borrowers with unsold loans may also avoid foreclosure, for example, if their circumstances change and they become eligible for foreclosure mitigation options again. FHA’s periodic reports on outcomes also do not compare outcomes between sold and unsold loans. FHA officials told us they had not conducted such a comparison because they expect all loans eligible for sale to be foreclosed. A foreclosed mortgage with an REO property disposition results in the greatest losses to the MMI Fund. However, our analysis of FHA data does not support these claims. When we compared loans sold through DASP to unsold loans with similar characteristics, we found that some unsold loans achieved an outcome other than foreclosure—21 to about 34 percent at various times within a 4-year period. FHA officials also told us that they evaluate loan outcomes by tracking the extent to which purchasers are meeting NSO requirements. However, because about 80 percent of loans were not sold through NSO pools, FHA’s evaluation covers only about 20 percent of DASP loans. In addition, FHA’s NSO requirements are targeted toward achieving specific outcomes for a property or community—such as donating the property to a land bank—rather than an individual loan or borrower. Our analysis indicates that sold loans had higher foreclosure rates than unsold loans regardless of whether they were sold through national or NSO pools. estimated current loan-to-value ratio, and The matched comparison attempted to minimize differences between sold and unsold loans across these factors in order to isolate the effect on outcomes of being sold out of FHA’s insurance program. We have previously found that evaluations often involve creating a comparison group. Furthermore, HUD policy states that its evaluations use methods that isolate to the greatest extent possible the effects of the program from other influences. FHA could use loans not sold through DASP to estimate what outcomes would have been observed in the absence of the program and the associated losses to the MMI Fund. A process to evaluate outcomes for sold loans relative to similar, unsold loans could help FHA determine whether DASP is meeting its financial objective of maximizing recoveries to the MMI Fund and understand the extent to which DASP is helping struggling homeowners. In its reports on DASP outcomes, FHA periodically reports at an aggregate level the change in monthly payments resulting from the modifications offered by purchasers. However, FHA does not track or report the change in payments by individual purchasers. A 2016 white paper prepared by the Department of the Treasury in conjunction with HUD and FHFA defined loss mitigation sustainability as offering solutions that work the first time. It further stated that modifications that provide meaningful payment reduction will decrease the chance of a homeowner redefaulting. Additionally, we reported in 2012 that the change in a borrower’s monthly mortgage payment is among the factors that can significantly influence the success of a modification. Since 2015, FHA has required purchasers to offer eligible borrowers HAMP-like modifications or substantially similar modifications designed to lower borrowers’ monthly payments to an affordable and sustainable amount. However, FHA does not monitor the extent to which individual purchasers complied with the requirement to offer payment-lowering modifications to eligible borrowers. We found that while the majority of the modifications offered to borrowers whose loans were sold in 2015 or later decreased monthly payments by more than 20 percent, about 8 percent of modifications increased or did not result in a change in payment. Not all borrowers are eligible for a payment-lowering modification, and, according to FHA officials, some modifications could increase monthly payments for borrowers with a large number of missed payments. As discussed later, our analysis found that outcomes can vary greatly by purchaser, and purchasers may not offer comparable modification options. See appendix IV for information on the types of modifications purchasers have used. Furthermore, FHA may not have the data it needs to evaluate whether payment-lowering modifications offered by purchasers remain sustainable. In the second 2016 sale, FHA began requiring that modified interest rates be fixed for at least 5 years and thereafter that they not increase by more than 1 percent per year. FHA also began requiring purchasers to report data related to interest rates for modified loans, including the modified interest rate and the number of years it would remain fixed. However, based on our review of reported modification information, none of the purchasers from this sale reported these data. Additionally, about 22 percent of the modifications offered to borrowers whose loans were sold in the 2015 sale or later included a deferment. Under deferment, borrowers are allowed to temporarily stop making payments toward some or all of their principal balance, interest, or other indebtedness, and deferment may result in a balloon payment at a later date. Other than type of deferment, FHA does not require purchasers to report details of the deferment or the effect on payments following the deferral period. As a result, we could not determine the long-term effect on monthly payments for many modifications offered by purchasers. Some advocacy group representatives we spoke with expressed concerns about purchasers offering unsustainable modifications. For example, one advocacy group representative told us that some purchasers may offer modifications that initially lower monthly payments but later adjust to levels that are higher than what they were prior to modification. FHA requires purchasers to report some information that would allow it to determine the types of modifications offered by individual purchasers as well as the sustainability of these modifications. As mentioned previously, FHA officials said they expect all loans eligible for sale to be foreclosed and consider any nonforeclosure outcome achieved by purchasers to be an improvement. This expectation may deter FHA from evaluating the modifications offered by individual purchasers or the sustainability of modifications. Federal internal control standards state that management should use quality information to achieve its objectives, which includes identifying information requirements needed to achieve the objectives, evaluating the data it receives from internal and external sources to ensure they are sufficiently reliable for use in making informed decisions, and using the data for effective monitoring. Without monitoring individual purchasers’ modifications or collecting key data elements, FHA cannot determine whether purchasers are meeting the postsale requirements or the extent to which eligible homeowners obtain sustainable modifications. Our analysis showed that sold loans were more likely to experience foreclosure than similar, unsold loans overall within a 48-month period after servicing transfer (see fig. 7). In the aggregate, the probability of experiencing foreclosure was greater overall for sold loans compared to unsold loans. For example, the probability of foreclosure 24 months after the servicing transfer date was 43 percent for sold loans and about 36 percent for unsold loans, a statistically significant difference. Additionally, we analyzed the probability that a borrower reperformed, received a temporary action such as forbearance or a trial modification, or received a short sale or deed-in-lieu of foreclosure—foreclosure avoidance outcomes. In the aggregate, the probability that sold loans avoided foreclosure ranged from about 15 to 24 percent at various times within a 3-year period beginning 12 months after the servicing transfer date. Foreclosure avoidance rates for unsold loans were higher, ranging from 21 to about 34 percent during this period. We found that sold loans were less likely to result in owners staying in their homes compared to unsold loans due to out-of-home actions (see fig. 8). The probability of reperforming was greater overall for unsold loans compared to sold loans. Additionally, unsold loans were more likely to receive an in-home temporary action. In contrast, sold loans were more likely to result in a short sale or a deed-in-lieu of foreclosure, through which borrowers avoid foreclosure but lose the title to their homes. See appendix VI for a comparison of reperforming, short sale or deed-in-lieu of foreclosure, and temporary action outcomes between sold loans and unsold loans. Although we found that sold loans were more likely to experience foreclosure in aggregate, for later sales, after about 12 months, rates of avoiding foreclosure were similar or greater for sold loans compared to unsold loans, and for some purchasers rates of foreclosure were similar or smaller for sold loans compared to unsold loans. For the second 2013 sale through the 2015 sale, we found that sold loans were less likely to avoid foreclosure compared to unsold loans (see fig. 9). In the 2016 sales, however, after about 12 months the sold loans were more likely to avoid foreclosure compared to similar unsold loans. Further, after an additional 12 months—24 months after the servicing transfer date—loans sold in the first sale in 2016 avoided foreclosure at a rate that was 5 percentage points greater than unsold loans. Loans sold in the second sale in 2016 were also consistently less likely to foreclose compared to unsold loans. We discuss potential explanations for these differences among sales in the section that follows. We also found differences in the rates of foreclosure and some outcomes that avoid foreclosure achieved by different purchasers (see fig. 10). For example, the probability of a loan reperforming 24 months after the servicing transfer date ranged from about 0.2 to about 25 percent for selected DASP purchasers. While most of these purchasers fell below the reperforming estimate of 18 percent for similar, unsold loans, one purchaser exceeded this rate. Foreclosure and short sale or deed-in-lieu of foreclosure probabilities 24 months after the servicing transfer date also differed among these purchasers, ranging from 31 to about 90 percent and from 8 to about 30 percent, respectively. These rates generally exceeded the foreclosure and short sale or deed-in-lieu of foreclosure estimates for similar, unsold loans (34 and about 9 percent, respectively). Purchasers told us that the outcome they pursue for a loan depends in part on the borrower’s preference. According to purchasers, for borrowers who want to keep their homes, the best option is to try to modify the loan and achieve reperformance status. Purchasers also said that for borrowers who do not want a modification or for whom a modification is not possible, they may pursue a short sale or deed-in-lieu of foreclosure, which have a less negative effect on borrowers’ credit than a foreclosure. Representatives of a consumer advocacy group and a research organization told us that foreclosure has the most negative effect on the borrower’s credit. A Fair Isaac Corporation (FICO) study found that, in some cases, foreclosure had a more negative effect on comparable borrowers’ credit profiles than a short sale or deed-in-lieu of foreclosure. FHA officials, purchasers, and servicers said that purchasers have more flexibility and are in a better position than FHA servicers to provide more generous mitigation options. A senior FHA official emphasized that purchasers have more financial flexibility because they generally buy the defaulted loans at a discount from FHA (that is, less than the unpaid principal balance). According to different DASP stakeholders, purchasers can forgive a portion of the principal, offer a deferment that is greater than 30 percent of unpaid principal extend the term of a loan beyond 30 years, reduce the interest rate below the current market rate, offer more than one modification in a 2-year period, and offer more generous terms for deeds-in-lieu of foreclosure and short sales. In contrast, FHA is restricted in the loss mitigation options it can offer. FHA officials told us that it does not offer debt forgiveness, but may defer a limited amount of principal through a partial claim. FHA officials also said they generally set loan term ranges to meet requirements for securitization in the secondary mortgage market, including a fixed interest rate and a 30-year term. In addition, FHA’s loss mitigation alternatives to foreclosure, such as short sales and deeds-in-lieu of foreclosure, are restricted or approved by FHA based on their chance of success and the associated financial effect on the MMI Fund. However, representatives of some advocacy groups told us that borrowers generally benefit from their loans remaining insured and unsold because FHA’s loss mitigation process is more transparent. They said that information on the loss mitigation process under FHA is publicly available, while it can be difficult to access information about some purchasers’ loss mitigation processes. Also, starting in 2012, FHA policies attempted to provide a more consistent loss mitigation process for borrowers across all FHA servicers. In contrast, purchasers can have varying processes for offering loss mitigation options. A number of factors may contribute to differences in outcomes between sold and unsold loans by DASP sale and purchaser, such as increased postsale servicing and reporting requirements, variations in purchaser participation across sales, and differences in the modifications offered by purchasers. Changes in postsale servicing requirements may account for higher reperforming rates for sold loans in the 2016 sales. As discussed previously, FHA introduced additional servicing requirements in 2015 aimed at offering additional protections to borrowers whose loans were sold through DASP. For example, FHA began requiring purchasers to evaluate borrowers for HAMP or substantially similar modifications aimed at lowering borrowers’ monthly payments and offer these modifications to eligible borrowers. Further, the share of loans sold through NSO pools relative to national pools has increased, which may also account for higher reperforming rates for sold loans in the 2016 sales. As noted previously, NSO and nonprofit pools have additional postsale outcome requirements. We compared outcomes for loans sold in NSO pools to outcomes for loans sold in national pools and found that loans sold in NSO pools were more likely to reperform, possibly due to higher occupancy rates in NSO pools compared with national pools. As shown in figure 11, the share of loans sold through NSO and nonprofit pools relative to loans sold through national pools increased between 2013 and 2016, from about 12 percent of the total loans in our scope for the 2013 sales to about 45 percent of loans in the 2016 sales. In addition, FHA introduced a reporting requirement in 2015 that purchasers continue reporting the outcome status of loans even after selling them to new buyers, as opposed to reporting the loans as resold with no further outcome updates. Purchasers may have returned these loans to performing status before selling them because performing loans are more profitable, but the performing status would not have been reported before 2015. The use of resales as a status was substantially lower in the second sale in 2016 compared to the first sale in 2013—0.04 percent of reported statuses compared to 29 percent of reported statuses. This change could be reflected in the higher reperforming outcomes we observed for sold loans in 2016. Our analysis indicated that individual purchasers did not consistently buy loans across sales and the share of loans bought by individual purchasers varied. For example, about 42 percent of the purchasers in our scope bought loans in one sale, while about 27 percent of purchasers bought loans in three or more sales. The share of loans bought by individual purchasers has also varied by sale (fig. 12). For example, one purchaser bought about 4 percent of the loans sold in the second sale in 2013 but about 82 percent of the loans sold in the first sale in 2016. This purchaser had higher reperforming and lower foreclosure outcomes compared to other purchasers. In addition, purchasers may not consistently offer modification options. Approximately 18 percent of the sold loans in our scope received one or more modifications. However, individual purchasers offered modifications at varying rates, from no modifications to 46 percent of the loans they purchased. Our analysis also indicates that the type of modifications offered may differ by purchaser. For example, we found that about 88 percent of the modifications that had decreased monthly payments by 30 percent or more were offered by two of the 25 purchasers that reported modifying loans. In addition, the share of modifications offered by individual purchasers that resulted in no payment change or an increase in payment varied. For example, eight purchasers reported either no change or an increase in payment in 51 to 75 percent of the modifications they offered. In contrast, three other purchasers reported either no change in payment or an increase in payment in less than 10 percent of their modifications. Purchasers’ investment goals and expertise could affect borrower outcomes. DASP purchasers include investment firms, rental housing companies, and nonprofit organizations with varying investment goals. In interviews, purchasers cited various goals for purchased loans. For example, an executive of a nonprofit organization said its primary goal was to help borrowers avoid foreclosure, while representatives of an investment firm told us that their goal was to maximize the return for each purchased loan. A representative of one advocacy group told us that purchasers’ different areas of expertise could make different foreclosure and foreclosure avoidance options more or less profitable for them. For example, purchasers with an extensive background in loan servicing may be able to offer modifications at a lower cost, while rental companies may consider DASP as a source for inventory for properties to rent if loss mitigation fails. Additionally, purchasers can have varying levels of success in contacting borrowers to discuss modifications or disposition options for the loans they purchased. Most purchasers noted that it was often difficult to make contact with borrowers because houses were vacant or borrowers avoided contact. For example, one purchaser said it was unable to reach about 25 percent of borrowers for the loans it purchased. Another purchaser said it was unable to reach about half of the borrowers. Furthermore, while several purchasers said they primarily contacted borrowers via the notice of servicing transfer and by phone, one purchaser also said that a more successful outreach method involved in- person visits to borrowers’ homes, but that such visits may not always be feasible due to resource constraints. FHA announces bid dates in the Federal Register and industry publications but does not communicate long-range notice of upcoming sales. FHA held multiple sales in 2011, 2012, 2013, 2014, and 2016, but the sales were not held at set intervals or at set dates throughout the years. FHA has not held any DASP sales since September 2016, and officials stated that they do not know when FHA will hold another sale. Our interviews indicate that communicating long-range notice of sales could help keep participation robust and increase bid amounts. One purchaser told us that it was eager for FHA to restart DASP sales. However, purchasers would like to receive additional notice of sales. One purchaser told us that additional notice of FHA sales would allow it the time to plan or raise additional capital needed to participate in a DASP sale. Another purchaser said that, without knowledge of when another sale will occur, it will invest elsewhere. Losing bidders to other entities’ sales could affect bid amounts in DASP sales. According to economic literature, increasing the number of bidders in an auction generally should increase bid amounts—a financial objective for the program. Federal internal control standards state that management should externally communicate the necessary quality information so that external parties can help the entity achieve its objectives and address related risks. For example, although Fannie Mae does not publish an annual schedule, market participants know when to expect Fannie Mae sales because it has held them multiple times a year. In contrast, FHA does not hold regular sales or signal to the market when it will hold its next sale through its outreach because DASP remains a pilot program. FHA officials said they change program parameters with each sale, so it is difficult to schedule sales in advance. We previously noted that, even implementing DASP as a pilot program, FHA could use performance data to establish criteria for the timing of sales and to help optimize the use of the program to achieve its objectives. Similarly, by communicating long- range notice of upcoming sales to market participants, FHA could encourage bidder participation and potentially help meet its objective of maximizing recoveries to the MMI Fund. As discussed in appendix VII, characteristics of successful auctions include attracting sufficient interest in the auction and in designing the auction to meet its objectives. Without communicating long-range notice, FHA may be recovering less than it could for the MMI Fund. FHA sets reserve prices—a minimum amount that it is willing to accept as the winning bid—to help ensure that the MMI Fund is minimally affected by the sale. FHA generates a reserve price for each loan and adds those prices together to generate a pool reserve price. If FHA does not receive a bid on a pool that is at or above its reserve price, FHA may choose not to sell the pool. Any amount of the bid above the reserve price represents additional potential proceeds to the MMI Fund. FHA officials stated that they expect that all DASP loans would be foreclosed and the properties placed in its REO inventory had they not been sold. FHA officials stated that they establish each loan’s reserve price considering the percentage of the unpaid balance FHA expects to recover through foreclosure and REO disposition. A recent HUD OIG report found that for loans sold in 2015 and 2016, FHA experienced a 3 percent lower loss rate compared with similar loans that were foreclosed and the associated property placed into FHA’s REO inventory. Loss estimates have varied over time and by location of the property associated with the loan, but generally an REO disposition results in the greatest loss to the MMI Fund. For example, FHA’s Office of Risk estimated that from fiscal year 2013 through the first quarter of 2017, FHA lost 61 percent (recovering about 39 percent) of the unpaid balance on REO dispositions compared to about 46 percent (recovering 54 percent) of the unpaid balance on other nonloan sale dispositions. FHA officials stated that unsold defaulted loans would likely result in foreclosure and being placed in the REO inventory. However, our analysis of outcomes showed that comparable unsold loans resulted in a range of outcomes, not just foreclosure and REO disposition. Specifically, our analysis of outcomes in sales between 2013 and 2016 showed that about 66 percent of unsold loans with characteristics similar to sold loans resulted in foreclosure or remained unresolved. The remaining 34 percent of these unsold loans resulted in a range of nonforeclosure outcomes (including returning the loan to performing status), all of which could produce smaller losses to the MMI Fund compared with REO disposition. Further, our analysis found that about 14 percent of the loans returned to performing status or were terminated as paid in full, thereby generating very little to no loss to the MMI Fund. FHA may be setting its reserve prices too low in some cases. FHA sets a loan’s reserve price considering the percentage of the unpaid balance it expects to recover through an REO disposition to guarantee the minimum recovery proceeds to the MMI Fund. However, when the expected losses to the MMI Fund for some loans are smaller—such as in the case of a different disposition method or a terminated loan—the reserve price would need to be higher to guarantee the minimum recovery proceeds to the MMI Fund. If FHA could recover more of the unpaid loan balance through a non-REO disposition method, setting the reserve price at the expected recovery of the unpaid balance from an REO disposition would be too low. See figure 13 for an illustrative example of how reserve prices could be affected based on different expectations of loan dispositions. The extent to which the MMI Fund could be negatively affected depends on how reserve prices compare to the actual winning bids. In figure 13, if FHA set the reserve price of pool A at $3,900,000, FHA would sell the pool to the highest bidder that bid at least $3,900,000. If the highest bid was less than $3,900,000, FHA may not sell the pool. If the highest bid for the pool was at least $3,900,000 but less than $5,054,000, the MMI Fund would be negatively affected because FHA could have recovered more by not selling the pool. If the highest bid was at least $5,054,000, the MMI Fund may not be negatively affected by the sale. Using a simplified method to calculate reserve prices that does not consider differences in local housing markets, we estimate that 31 percent of the loan pools FHA sold in its 2013–2016 sales had winning bids greater than FHA reserve prices but less than our calculated reserve prices. For about 14 percent of the pools, our calculated reserve price was 10 percent or more below the winning bid, and for 7 percent of the pools, our calculated reserve price was 25 percent or more below the winning bid. Federal internal control standards state that management should use quality information to achieve the entity’s objectives. This includes designing a process that uses the entity’s objectives and related risks to identify the information requirements needed to achieve the objectives and address the risks. However, FHA is not considering information on the range of potential outcomes for loans in setting its reserve pricing because it expects all sold loans to result in foreclosure and REO disposition. Without considering other disposition methods in its reserve pricing, FHA risks recovering less for the MMI Fund in loan sales than if the loans had not been sold and risks not meeting its objective. FHA’s eligibility criteria specify the characteristics of the loans that can be selected for a loan sale, but FHA does not analyze its portfolio to identify loan characteristics for which DASP would be the lowest-cost disposition method or consider market information before setting the criteria. FHA has analyzed bid amounts from previous sales and made changes to eligibility criteria related to length of delinquency and LTV ratio, in part, intended to increase MMI Fund recoveries. For example, using analysis of its 2014 sales, FHA determined the LTV ratios that produced the highest loan-level recoveries relative to REO dispositions and changed the loan eligibility criteria for the minimum LTV ratios by state for its 2015 sale. According to FHA, this change was intended to make more loans eligible for disposition through DASP sales in certain states that had long foreclosure processes. However, FHA does not analyze its portfolio of defaulted loans to identify characteristics of loans that, if sold, would minimize the loss to the MMI Fund relative to all other disposition methods to inform eligibility criteria for sales. FHA may have missed an opportunity to evaluate when loan sales would be the most effective disposition method to maximize recoveries to the MMI Fund—a financial objective of the program. FHA contracted with CoreLogic in 2016 to develop a tool to determine the lowest-cost disposition for defaulted loans in FHA’s portfolio but did not include loan sales as a potential disposition method. The tool is intended to generate estimates of property values and holding costs and determine the lowest cost disposition method for a given loan at a given time. Used broadly, this information could help FHA identify loan criteria for which DASP sales would be the most effective disposition method and set loan eligibility criteria for DASP loans. However, FHA excluded DASP because, according to the contractor, the data on DASP had been too inconsistent to be reliably included in the CoreLogic tool. Therefore, FHA cannot use the tool to identify loan characteristics for which DASP could be the lowest-cost disposition method or to inform its decisions in setting loan eligibility criteria. Further, FHA determines eligibility criteria before considering current market information. FHA’s transaction specialist gathers market information before the sale, but FHA does not consider it before setting eligibility criteria and soliciting eligible loans from servicers. The transaction specialist analyzes the market and develops a sales strategy report using the loans submitted by the servicers. The report contains information on available capital for key purchasers, the number and type of loans purchasers are interested in buying, other entities’ upcoming sales, and potential pooling strategies for the loans submitted. FHA uses the information to develop pools intended to maximize the sale proceeds, but not to identify characteristics of loans meeting purchasers’ preferences and inform decisions in setting eligibility criteria. FHA’s current approach risks setting criteria that may not maximize recovery to the MMI Fund because it may be selling loans that could result in a smaller loss to the MMI Fund than if they had remained under FHA insurance. FHA generally analyzes how to maximize sales proceeds after setting loan eligibility criteria and reviewing the servicers’ submitted loans because servicers select the loans, voluntarily participate, and may not submit all eligible loans. Further, setting loan eligibility criteria that increase servicers’ cost to identify loans may reduce servicer participation. In addition, FHA does not use current market information because, according to officials, they use data from past sales to determine market preferences and their primary concern is the effect on the MMI Fund. However, FHA has not held a sale since 2016, so market preferences may have changed. Additionally, purchaser participation may decline if loans do not match their preferences. Generally, fewer bidders indicate less interest in the pools and could result in decreased prices, which would reduce returns to the MMI Fund. By implementing DASP, HUD intended to maximize recoveries to the MMI Fund. Without analyzing its loan portfolio to identify when loan sales would be the most cost-effective disposition method and considering market information before setting loan eligibility criteria, FHA cannot appropriately calibrate its loan eligibility criteria to maximize recovery to the MMI Fund. Based on our analysis of comparable mortgage industry auctions, FHA’s auction structure mirrors the industry standards of pooled, highest bidder, sealed bid auctions. Other auction structures we examined, such as single loan sales and adding a winner-take-all option, would involve tradeoffs. For example, an analysis by DebtX, a loan sale advisor, showed that FHA would have earned higher proceeds in a prior DASP sale if it had awarded based on single-loan bids rather than the pool-level bids. However, our interviews with FHA officials and purchasers revealed uncertainty in how proceeds from single-loan bids would compare to bids for pooled loans. For example, FHA officials said they benefit from economies of scale when offering larger pools and that administrative costs associated with servicing transfers would be higher if FHA sold loans individually. Furthermore, purchasers may decline to bid on individual loans. Purchasers we interviewed expressed interest in sets of loans rather than individual loans, in part to manage risk. When asked about smaller pools, FHA officials stated that they have used small pools to attract nonprofit bidders, but we found that these pools had a low number of bidders and many were not traded. The effect on the MMI Fund of adding a winner-take-all option to FHA’s auction structure is uncertain. Such a structure could result in increased bid amounts. In a winner-take-all option, each bidder would choose to either participate at the sale level or pool level in the winner-take-all option. In either case, the bidder would place loan-level bids that would be rolled up to the pool or sale level. If a winner-take-all bid exceeds the aggregate of the highest pool-level bid for each pool, all pools are awarded to the winner-take-all bidder. By definition, if a winner-take-all bidder won the auction, the resulting bid would increase FHA’s overall sale proceeds. However, a winner-take-all structure could discourage bidder participation, which could lead to reduced bid amounts. Smaller entities and larger nonwinning bidders may be less likely to participate in future sales because of the costs associated with participating. According to auction theory, the higher the cost of performing due diligence and qualifying for and participating in the auction, the more bidder participation will be discouraged. Although the extent of purchasers’ due diligence checks differed, all the purchasers we interviewed told us that they expend funds to purchase property valuations on at least a sample of loans to check whether the valuations listed in the servicer data were reasonable. Some purchasers also expend funds to examine servicing records or perform legal searches related to the loans. Additionally, bidders are required to submit deposits with their bids that FHA will return if the bidder is not awarded the pool or pools. One purchaser told us it was reluctant to spend the money on due diligence if it did not have a reasonable chance at winning the pool or pools. According to economic literature, having fewer bidders in an auction generally results in decreased prices and an increased opportunity for bidders to form strategic partnerships that would decrease competition. See appendix VII for more information on auction structures. It is unclear whether changes to FHA’s pooling strategy—that is, its approach for selecting loans to include in its loan sale pools—would result in more bidders or higher bid amounts. We compared the pooling practices and pool-level data of FHA with those of Freddie Mac and Fannie Mae (the enterprises) to determine whether pooling strategy affected the number of bids. The enterprises started selling defaulted loans in 2015—much later than FHA—and have continued to do so, with Freddie Mac and Fannie Mae both holding sales in October 2018. FHA held three DASP sales in fiscal years 2015 and 2016 that overlapped with the time frame of the enterprises’ sales. FHA and enterprise pools had different financial characteristics—loans in FHA pools were less delinquent, the properties were more likely to be occupied, and the loans had lower underlying property values compared to loans in enterprise pools (see fig. 14). Nonetheless, FHA received similar numbers of bids and bid amounts relative to the estimated property values as the enterprises. Generally, the number of bidders for FHA and the enterprises was between three and six, and bid amounts were typically between 58 and 71 percent of the underlying estimated property value. Many of the purchasers of FHA’s DASP loan pools also purchased the enterprises’ pools of defaulted loans. It is unclear whether adjusting the pooling strategy to focus on specific loan characteristics would increase the number of bidders for FHA. Enterprise officials told us that they pool by geography, occupancy, and LTV ratio and also try to create loan pools such that all loans have the same servicer. Unlike the enterprises, FHA does not pool loans by similar characteristics, and pools frequently have loans from more than one servicer. FHA officials told us they primarily use geography and pool size to pool loans. However, FHA officials also told us they try to include loans to make the pools attractive to different types of purchasers. Loans may be valued differently by bidders with unique strengths—such as strong default servicing infrastructures or experience rehabilitating properties—that would make the loans more profitable to them compared to other bidders. FHA officials stated that they encourage higher, outlier bids by structuring pools to attract different types of bidders. We found differences in the extent to which loan-pool characteristics were associated with bidder participation for FHA’s and the enterprises’ defaulted loan sales. Our multiple variable regression analyses of how loan-pool characteristics predict the number of bidders showed the following: Pools with a higher percentage of occupied properties were associated with an increase in the number of bidders in FHA pools but a decrease in the number of bidders in enterprise pools. Average LTV ratio was not associated with the number of bidders for FHA or the enterprises. National pools were associated with more bidders for FHA. This result may be due to fewer FHA postsale requirements for national pools. For FHA pools, more servicers was associated with fewer bidders, possibly due to higher transaction costs. Although 86 percent of FHA pools had fewer than five servicers, the number of servicers for FHA pools ranged from one to 21. In contrast, all enterprise pools were single-servicer pools, except for four out of 101 pools (about 4 percent) that each had two servicers. See appendix I for a detailed description of these analyses. Setting aside pools for nonprofit organizations has not significantly expanded bidder participation in FHA loan sales. FHA performs market outreach to educate potential purchasers about the DASP process, but barriers to entry exist in terms of qualifications and the underlying capital required. In its 2015 sale, FHA began offering nonprofit-only pools. In 2016, FHA established a goal of selling 10 percent of assets to nonprofits and local governments. In 2015–2016, FHA offered nine pools exclusively to nonprofits, of which five (about 56 percent) received bids at or above FHA’s reserve price and were traded. Each pool received between one and three bids. Despite heavy marketing, all traded pools were awarded to two organizations, including one first-time purchaser. In comparison, from 2010–2016, FHA offered 191 national and NSO pools, and 185 (about 97 percent) received bids at or above FHA’s reserve price and were traded. Several stakeholders told us that most nonprofit organizations do not have the capacity to service delinquent loans, but they may be able to participate in the program in a different capacity. For example, two purchasers partnered with nonprofit organizations to perform outreach to borrowers. Since 2002, FHA has used loan sales intermittently to reduce its backlog of defaulted mortgages and preserve the financial health of the MMI Fund. In addition, some homeowners have received additional opportunities to modify their loans and retain their homes through the program. Yet, our review found several areas where FHA can improve its management of DASP through more formalized procedures and analyses, as follows. Improving controls. By evaluating eligibility at various points throughout the 3-month period prior to the sales, including after the servicer update, FHA could better prevent the sale of ineligible loans. Additionally, as FHA finalizes its comprehensive procedures, it can better ensure that it is considering the effects of previous changes on the program by including procedures for reviewing and documenting program changes in a timely manner. Using performance data. FHA has not developed key performance measures for DASP. Without measurable targets related to clear program objectives, FHA is not well-positioned to assess the effectiveness of DASP—which is still considered a pilot program—in achieving its objectives. Furthermore, by using performance data to determine the optimal timing of DASP sales, FHA could help the program achieve higher recoveries. Evaluating outcomes. FHA has not conducted an analysis that compares the extent to which sold loans help avoid foreclosure, as compared to similar, unsold loans. Such an analysis would help assess DASP’s effectiveness in meeting a program objective. Monitoring and evaluating purchasers’ modifications. FHA does not monitor purchasers of defaulted loans to ensure they are complying with FHA’s requirement to offer payment-lowering modifications to eligible borrowers. Additionally, FHA may not collect the data it needs to evaluate whether modifications offered by purchasers remain sustainable. With better monitoring, FHA could determine whether individual purchasers are meeting these requirements. Maximizing benefits of loan sales. FHA has opportunities to make changes in how loan sales are held and structured that could enhance bidder participation and better meet the DASP objective of maximizing recoveries to the MMI Fund—which are two characteristics of successful auctions. Providing better advance notice to prospective bidders, setting reserve prices based on realistic expectations, and setting loan eligibility requirements that encourage more bidding could improve the results of DASP sales and thereby reduce losses to the MMI Fund. We are making the following nine recommendations to FHA: The Commissioner of FHA should ensure that its eligibility checks are conducted throughout the DASP sale process, such as by establishing a schedule to check for eligibility at certain milestones. (Recommendation 1) In formalizing procedures for DASP, the Commissioner of FHA should document processes for timely consideration and review of program changes. (Recommendation 2) The Commissioner of FHA should clearly define DASP objectives and develop measurable targets for all program objectives. (Recommendation 3) The Commissioner of FHA should use performance data to develop criteria for when to hold DASP sales. (Recommendation 4) The Commissioner of FHA should evaluate loan outcomes under DASP compared to outcomes for similar, unsold loans. (Recommendation 5) The Commissioner of FHA should monitor individual purchasers’ compliance with FHA’s modification requirements and ensure the purchasers submit the data needed to evaluate the sustainability of modifications. (Recommendation 6) The Commissioner of FHA should communicate long-range notice to prospective bidders of upcoming DASP sales. (Recommendation 7) The Commissioner of FHA should develop a methodology to assess the range of possible outcomes for loans when setting DASP reserve prices. (Recommendation 8) The Commissioner of FHA should analyze FHA’s loan portfolio and market information before setting loan eligibility criteria. (Recommendation 9) We provided a draft of this report for review and comment to HUD and FHFA. HUD provided written comments, which have been reproduced in appendix VIII, that communicate FHA’s response to the report. Both HUD and FHFA provided technical comments, which we have incorporated, as appropriate. In its written response, FHA’s management generally agreed that opportunities exist for improvement to single-family loans through more formalized procedures and analyses, as the defaulted loan disposition option transitions to a permanent disposition alternative. FHA generally agreed with seven recommendations and did not explicitly agree or disagree with two recommendations. FHA neither agreed nor disagreed with our recommendation that FHA should ensure that its eligibility checks are conducted throughout the DASP sale process, such as by establishing a schedule to check for eligibility at certain milestones. FHA stated that it works with the servicers and relies on them to determine eligibility throughout the DASP sale process. FHA also stated that its management agrees to include a schedule of eligibility checks in its procedures. We acknowledge that servicers check loan eligibility throughout the process, as stated in the report. However, we maintain that FHA and its contractors should also space their own checks throughout the process, specifically scheduling some closer to the bid date, and not rely exclusively on the servicers for this function at the end of the sale process. FHA neither agreed nor disagreed with our recommendation that FHA should clearly define DASP objectives and develop measurable targets for all program objectives. FHA management stated that it believes it already has clear objectives and performance management in place for its DASP objective to maximize recoveries to the MMI Fund and that it measures whether it is meeting this objective. We acknowledge that FHA’s objective to maximize recoveries to the MMI Fund is clear and that it has a measureable target. However, as stated in the report, agency documents and program changes reflect additional program objectives related to preserving homeownership, helping to stabilize neighborhoods, and offering borrowers a second chance at avoiding foreclosure that do not have measurable targets. We maintain that FHA should clarify its program’s objectives in agency documents, whether that be one objective or several, and ensure that each objective has a measurable target. FHA also took issue with aspects of our comparison of sold and unsold loans in its written response and technical comments. In its written response, FHA noted that the unsold loans in our analysis are invalid for comparison to sold loans because these unsold loans had not been deemed by servicers as having completed all applicable loss mitigation activities prior to being included in the analysis the way sold loans had. We attempted to minimize differences between the sold and unsold loans by matching loans across several variables that could affect the likelihood of foreclosure or foreclosure avoidance. We found a high rate of similarity between the two groups and indirectly controlled for any differences in the extent of loss mitigation by including length of delinquency as one of the matching variables. According to the FHA servicing handbook, servicers are generally required to either use a loss mitigation option for which a borrower qualifies or initiate foreclosure within 6 months of the default date. In its technical comments, FHA also noted that our matching of comparison loans omitted important variables. In particular, FHA noted that the analysis did not hold constant several factors related to the risk of foreclosure, including default risk as measured by FICO scores, debt-to-income ratios, home price appreciation, and loan amount and term. However, we indirectly controlled for loan term and home prices by matching loans by origination years and indirectly controlled for loan amount and home prices by matching on categories of LTV ratios. We did not control for debt-to-income ratios or FICO scores, but FHA’s data systems did not contain them for unsold loans and FHA does not include them as criteria for DASP eligibility. Further, these variables may not be substantially different between the sold and unsold loans because the loans in both groups are severely delinquent. We revised the report to clarify that we estimated the LTV ratio at the time of the DASP sale. We calculated the LTV ratio using the outstanding loan amount and estimating current property values by adjusting the original sale values for regional changes in home prices over time. In addition, FHA stated in technical comments that our comparison group is invalid because 100 percent of loans in DASP sales would end in foreclosure if they were not included in a sale. FHA stated that the only loans eligible for sale are those for which the only alternative remaining to the borrower is foreclosure. However, we disagree that all sold loans would have ended in foreclosure had they not been sold. As discussed in the report, unsold loans with characteristics similar to sold loans experience a range of outcomes, including up to 34 percent experiencing outcomes other than foreclosure following sales. In addition, the status of delinquent loans can be very fluid throughout the sale process, even after purchasers place bids on them, and borrowers who previously did not qualify for a loss mitigation option could become eligible to be evaluated again (and their loan could become ineligible for sale) if their circumstances change. For example, our analysis of FHA data found that from 2010 through 2016 about 23 percent of loans were removed from sales between the bid and claims dates due to, among other things, loans entering into loss mitigation. Furthermore, we found that for five individual loan pools, more than half of the loans were removed from the sales between the bid and claims dates. These results argue against the validity of FHA’s presumption that all loans selected for sales would have ended in foreclosure. Although our matching process does not capture all potential foreclosure risk characteristics and our results should be interpreted accordingly, our analysis supports our assumption that the pools of sold and unsold loans are generally comparable and describes relationships between DASP participation and loan outcomes. We maintain that our approach is reasonable using the available data and forms a sound basis for the findings and recommendations in the report. As FHA considers actions in response to our recommendations about evaluating loan outcomes and assessing its methodology for setting reserve prices, we encourage it to further enhance the robustness of these analytical methods. . As agreed with your office, 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 to the appropriate congressional committees, the Secretary of HUD, the Director of FHFA, and other interested parties. In addition, this report will be 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 garciadiazd@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. Key contributors to this report are listed in appendix IX. The objectives of our report were to examine (1) the changes the Federal Housing Administration (FHA) has made to the Distressed Asset Stabilization Program (DASP) over time; (2) certain DASP procedures, including those associated with loan eligibility, and documentation; (3) FHA’s evaluation of the identified outcomes for loans that have been sold through DASP and how these compare with similar, unsold loans; and (4) the potential effects that changes to DASP might have on the Mutual Mortgage Insurance Fund (MMI Fund). To conduct the data analyses discussed in the sections below, we used the FHA data sets listed in table 2. (We discuss the use and reliability of these data sets in the sections that follow this table.) To address all the objectives, we reviewed relevant laws, agency documents, and agreements. We reviewed the National Housing Act, Department of Housing and Urban Development (HUD) program evaluation policy and sale notices in the Federal Register, and Office of Management and Budget (OMB) Circular A-11. We reviewed HUD’s contractual agreements with servicers and purchasers for each DASP sale from 2010 to 2016, which are called, respectively, Participating Servicer Agreements (servicer agreements) and Conveyance, Assignment, and Assumption Agreements (purchaser agreements). We also reviewed other agency documents, including HUD’s Fiscal Year 2017 Annual Performance Report, FHA’s DASP sale results, FHA’s Actuarial Reports, HUD’s Reports to the Commissioner on Post Sale Reporting, and the Federal Housing Finance Agency’s (FHFA) Enterprise Non-performing Loan Sales Reports. We also reviewed prior GAO work on related topics. We interviewed officials from multiple offices within HUD, including the Offices of Asset Sales, Single Family Asset Management, Risk Management and Assessment, Finance and Budget, and the National Servicing Center. We also interviewed HUD’s three primary contractors for DASP at the time of our review—transaction specialist: Verdi Consulting; compliance analytics: SP Group; and program financial adviser: NOVAD Management Consulting. We interviewed officials from FHFA and the government-sponsored enterprises (enterprises)—Freddie Mac and Fannie Mae—as they also auction defaulted loans. We interviewed and reviewed reports from selected consumer advocacy organizations and industry stakeholders that included five servicers, seven purchasers, and two loan-sale advisory firms. In interviews, we generally discussed with participants the following topics: changes to DASP over time; what works well and what could be improved in DASP; foreclosure avoidance options that purchasers offer; the effectiveness of FHA’s 2015 and 2016 DASP reforms; communication to borrowers whose loans are selected for a DASP sale; and the auction process and effect of alternative auction structures on the MMI Fund. To select servicers and purchasers to interview, we analyzed the bid day pool-level data and postsale data, respectively. We selected and interviewed five servicers from a universe of 56 servicers based on high and low participation in terms of number of sales, loans sold, and the unpaid balance of the loans and type of institution (bank and nonbank). We selected and interviewed seven purchasers from a universe of 29 purchasers based on participation, postsale foreclosure rate, and type of institution (for-profit and nonprofit). The views and practices of the servicers and purchasers we selected may not represent those of the servicers or purchasers not selected. To identify a complete list of the loans sold through DASP (sold loans), as described in the background section of the report and used in analyses throughout, we obtained and analyzed postsale reporting data. Per the purchaser agreements, purchasers are required to report the outcome status of sold loans on a quarterly basis for 4 years following the transfer of loan servicing responsibilities. The quarterly postsale reports did not always include data for every purchased loan. We therefore compared the number of loans included in each quarterly postsale report for each pool and used the quarterly reports with the highest loan count to develop a complete list of the loans sold through DASP. To develop the map showing the concentration of sold loans by state, we used data from the Single Family Default Monitoring System (default monitoring system) to calculate the ratio of loans sold through DASP to FHA-insured, defaulted loans with six or more missed payments in July of each year. We then categorized states into five ratio categories based on the distribution of ratios across states. We limited our review of participants and characteristics to the loans included in our comparison analysis of outcomes to provide descriptive context for this analysis. To assess the reliability of the data sources above, we interviewed FHA officials about how the data were collected, processed, and accessed. We also identified the sold loans that were not reported in the default monitoring system at the time servicers submitted the loans to FHA for sale. We found that less than 0.1 percent of the sold loans in our scope were not reported as delinquent by servicers and determined that, due to their small percentage, excluding these loans would not bias our results. Based on our interviews and review of unreported loans, we concluded that servicers generally reported sold loans in the default monitoring system, and we found the data to be sufficiently reliable for the purpose of identifying and describing sold loans. To describe the DASP process and changes to the program over time, we reviewed FHA documentation, legislation, and other reports. To describe how DASP currently works, we analyzed the 2016 servicer and purchaser agreements and interviewed FHA officials and servicers. To describe how the program changed over time and the type of changes that FHA made, we reviewed HUD’s authorizing legislation to accept assignment and sell loans, program requirements under OMB Circular No. A-11, and HUD press releases that announced the program’s initiation and changes. To identify changes in servicer agreements and purchaser agreements since 2010, we performed a content analysis identifying differences from sale- to-sale (one servicer agreement and one purchaser agreement for each sale between 2010 and 2016). One analyst performed the review, and a second analyst verified the selected content. To gather additional background information on the program and the changes over time, we reviewed reports issued by the HUD Office of Inspector General (OIG) and consumer advocacy and other research organizations such as the National Consumer Law Center, Center for American Progress, and Urban Institute. To corroborate our information on the program and changes, we asked FHA to provide us a list of changes to the program between 2010 and 2016, and we interviewed FHA officials in HUD headquarters and at the National Servicing Center. We further corroborated our understanding of DASP through interviews with the servicers and purchasers. To identify FHA’s procedures for monitoring loan eligibility, we examined procedures identified in the servicer agreements and contracts and statements of work for entities assisting in oversight of DASP sales. We assessed the extent to which these procedures existed and were working effectively by reviewing status codes from FHA’s default monitoring system and examining relevant findings from HUD OIG audit reports. We found limited information in agency documentation on steps conducted to verify loan eligibility and had to rely on discussions with FHA staff and contractors on monitoring processes. We also interviewed servicers on their process for selecting loans and certifying loan eligibility for DASP. We further corroborated this information by providing a combined list of steps to FHA officials to verify accuracy. To assess whether FHA’s procedures for assessing loan eligibility were working, we determined the extent to which FHA’s sold loans appeared to be ineligible in its 2016 sales. To identify the ineligible loans, we compared the eligibility criteria listed in the 2016 servicer agreements to the data in the default monitoring system. We obtained the default information for sold loans for the period 2 months prior to the bid date— the period when servicers generally submit loans for sale—and at the bid date. We limited our analysis to loans sold in 2016 because FHA’s loan eligibility criteria changed from sale to sale and 2016 was the most recent year a sale occurred. We selected a nongeneralizable sample of 10 loans with ineligible default codes in the default monitoring system as of the bid date. To determine why FHA sold loans that appeared to be ineligible, we provided list of sold loans with ineligible codes to FHA staff for them to research and provide their explanations. We followed up in interviews with officials from FHA’s Office of Asset Sales to further clarify their responses. We also interviewed FHA officials regarding data reliability and to ensure that our understanding of the default codes and their corresponding eligibility or ineligibility for sale was accurate. We also performed electronic checks for consistency and validity and found the data to be sufficiently reliable for the purpose of determining default status, length of delinquency, and the extent to which loans that FHA sold in 2016 appeared to be ineligible. To assess whether DASP purchasers offered borrowers payment- lowering modifications, we evaluated the loan modifications offered by individual purchasers by comparing borrowers’ monthly mortgage payments prior to being modified to their monthly payments after being modified. We obtained postmodification payment data from the postsale reports and premodification payment data from the submitted loan database. Using the most recent postsale record for each modified loan, we calculated the change in payment resulting from the modifications offered by DASP purchasers. To confirm that we used the appropriate data sources and variables for our analysis, we contacted FHA’s Program Financial Advisor, who collects postsale reporting data and reports some information on modifications. Our analysis included all loans sold in DASP sales that occurred between 2013 and 2016, with some exceptions, in line with the scope of our comparison analysis of outcomes. We selected this scope because it represented the period for which FHA was generally able to provide consistent postsale quarterly reports. In addition, to assess the sustainability of the modifications offered by DASP purchasers, we used data on modification type from the postsale reports to calculate the number of modifications that included a deferment. We identified loan modification characteristics from prior GAO work. We also reviewed the purchaser agreements and postsale reports to examine the information available on modified interest rates. Our analysis was limited to modifications that were reported using the more expansive list of characteristic codes introduced in 2016, which accounted for about 95 percent of the modifications in our scope. To assess the reliability of the modification data, we checked for missing or invalid data entries across different modification fields, including modification date, modification type, and monthly payment before and after a modification. We found that purchasers generally reported consistent information on modifications for loans sold in DASP sales that occurred between 2013 and 2016 and determined the data to be sufficiently reliable for the purpose of calculating payment change and assessing the sustainability of modifications. We used multiple FHA data sources to match sold loans to similar unsold loans and compare outcomes across the groups. We used data from FHA’s default monitoring system and integrated database to obtain information on loan-level characteristics for both sold and unsold loans, such as length of delinquency. However, FHA data did not contain loans’ current property value or current loan-to-value (LTV) ratio. To calculate the current property value, we generated property values for sold and unsold loans based on data in the integrated database, including property value at origination, date of origination, and location information. We then aged the property values to the matching month and year using FHFA’s House Price Index data, which considers geography. We calculated the LTV ratio for sold and unsold loans by dividing the current unpaid principal balance obtained from the default monitoring system by the calculated current property value. To identify the loans sold through DASP and to determine their outcomes, we used postsale reporting data reported by DASP purchasers. To determine monthly outcome statuses for unsold loans, we used FHA’s default monitoring system and integrated database. Our analysis generally included loans sold in DASP sales that occurred between 2013 and 2016, but we excluded some sales and pools for various reasons. We excluded loans sold in the DASP sales that occurred from 2010 through 2012 because FHA could not provide semiannual or quarterly postsale reports for these loans. We excluded loans sold in Neighborhood Stabilization Outcome (NSO) pools in the first sale in 2013 because FHA had not yet implemented reporting requirements for more detailed information on loan status for NSO pools. We excluded Direct Sales, through which FHA directly transfers loans to government entities, as well as Aged Delinquent Portfolio Loan Sales, because these sales do not follow normal DASP procedures. Lastly, we excluded loans in pools that were offered for sale but not traded and loans that dropped out before transfer and were never sold. FHA was generally able to provide quarterly reports for the remaining sales and pools within the required reporting time frame. We took a number of steps to prepare and ensure the reliability of the data used to match sold loans to similar, unsold loans and compare outcomes. We generated seven datasets corresponding to the seven DASP sales in our scope. Each dataset was made up of the records in the default monitoring system 2 months prior to the bid date for the corresponding DASP sale—the time servicers submit eligible loans for sale to FHA, according to FHA officials. We eliminated duplicate case numbers as well as erroneous submissions, and we added sale and pool variables to identify sold loans based on the master list of sold loans. We also excluded unsold loans that were ineligible for sale at the time of matching. Specifically, we reviewed FHA’s servicer agreements and developed criteria for excluding unsold loans from matching based on sale eligibility requirements outlined in these agreements. We interviewed FHA officials to ensure that our understanding of the default status codes and their corresponding ineligibility for sale was accurate. We then used this information to identify and exclude ineligible loans. We performed a variety of electronic checks to test the completeness, consistency, and logic of outcome statuses for sold and unsold loans as reported by servicers. We excluded or corrected, where possible, a small percentage of sold and unsold loans (2 percent excluded and about 11 percent corrected) that had invalid or illogical reported statuses. We also excluded loans with invalid case numbers, loans erroneously reported as sold by purchasers, and other problem records. These exclusions accounted for less than 1 percent of the sold loans in our scope. We found that three pools were missing more than half of the expected number of postsale reports. Because these pools accounted for less than 2 percent of the sold loans in our scope, we decided to keep these pools in our analysis as they provided additional data points for estimating outcome probabilities, and including them would not significantly bias our results. Finally, when assessing data reliability, we consulted relevant documentation on the default monitoring system, integrated database, and postsale reporting systems and the specific fields used from these systems. We also interviewed officials knowledgeable about how data from these systems were collected, maintained, and accessed. Based on these steps, we determined that the data were sufficiently reliable for the purpose of matching sold loans to similar, unsold loans and comparing outcomes. We used statistical matching methods to identify a comparison group of unsold loans that closely resembled sold loans on loan characteristics that could affect the likelihood of foreclosure. Unsold loans were matched to sold loans for each sale, resulting in seven groups of unsold loans corresponding to loans sold in the seven DASP sales that occurred in 2013–2016. We matched unsold to sold loans 2 months prior to the bid date across the following characteristics: Length of delinquency. Number of missed payments at matching. Occupancy status. Whether property was occupied or vacant at matching. Location. Location of the property, based on latitude and longitude. Servicer. FHA-approved, mortgage servicer. Loan-to-Value (LTV) ratio category. Value of the property relative to the outstanding unpaid balance on the loan at matching. Loan origination. Year of the loan’s origination. We excluded modification status from the matching criteria. While there is some indication that loans that have been modified once are more likely to redefault in the future, this is largely dependent on the quality of the modification. However, modification quality could not be determined based on the FHA data we received. Our analysis did not seek to conduct a definitive evaluation of the causal effects on outcomes of being sold through DASP. Instead we sought to improve on simple comparisons of outcomes between sold and unsold loans by constructing a comparison group of unsold loans that were similar to sold loans on loan-level characteristics known to affect the likelihood of foreclosure. For example, matching sold and unsold loans by location minimized variation in neighborhood characteristics and local housing markets that could be associated with a higher or lower likelihood of foreclosure. We selected these factors based on our previous work on foreclosure mitigation and on consultations with subject-matter experts within GAO. See appendix V for more information on our statistical matching analysis. To compare outcomes for sold and unsold loans, we identified outcomes using postsale reporting data dictionaries in FHA’s purchaser agreements as well as FHA’s status codes used in its default monitoring system and integrated database data dictionaries. We grouped the outcomes into six outcome categories. To assign sold loans to a category, we used FHA’s postsale reporting data, and to assign unsold loans to a category, we used FHA’s default monitoring system and integrated database data. The outcome categories were as follows: Foreclosure. Loans terminated with foreclosure. Reperforming. Loans restored to performing status either under the original mortgage terms or through a permanent modification. In this outcome, the borrower retains ownership of the home. Temporary Action. Loans with temporary action that allow the borrower to retain ownership of the home—for example, an agreement for paying the loan balance or restoring it to performing status has been reached but has not met FHA’s time requirement to meet FHA’s definition of performing. This category may also include other interventions that have the intent of keeping the borrower in the home, such as forbearance. Short sale/deed-in-lieu of foreclosure. Loans that avoid foreclosure through short sales and deeds-in-lieu of foreclosure. In this outcome the borrower loses ownership of the home. Unresolved. Loans remaining in default status and whose outcomes were unresolved. Other. Loans whose outcomes do not fit into these other categories. A number of sold loans were reported by purchasers as resold, with no further outcome updates, and we decided to categorize these separately. Purchasers had the option of reporting on loans as resold until 2015, when FHA introduced a reporting requirement that purchasers continue reporting the outcome status of loans even after selling them to new buyers. For the loans in our scope, the percentage of postsale reports that included a status of resold ranged from 7 to 35 percent for the 2013 and 2014 sales, before dropping to less than 1 percent beginning with the 2015 sale. Purchasers may have returned resold loans to performing status before selling them because performing loans are more profitable, and, by categorizing these loans separately, we may have undercounted performing loans for the earlier DASP sales. While we considered classifying loans reported as resold as performing, our review of status sequences for loans with at least one resold status showed that purchasers reported a range of nonperforming outcomes before and after the resold status, indicating that not all resold loans were performing. We therefore determined that categorizing resold loans separately would result in more reliable estimates for sold loans. Using data from the default monitoring system to classify outcomes for the matched, unsold loans in our analysis required us to make some assumptions that may have resulted in overcounting performing, unsold loans. Because the default monitoring system only contains data on delinquent loans and does not include status information on performing loans, our classification of performing, unsold loans was based on whether or not a servicer reported the loan in the default monitoring system in a given month. As a result, we assumed that unreported loans were performing. However, a missing report could also be the result of a reporting omission by the servicer, rather than an indication of a performing status. To mitigate the risk of overcounting performing, unsold loans, we used a variable indicating the length of a loan’s current default episode to help us distinguish between performing loans and servicer omissions. Specifically, we counted unsold loans as performing only if the default episode length in the most recent default monitoring system report was less than the reported episode length in the default monitoring system report preceding the period of no reporting. We assumed that a lower default episode length in the most recent default monitoring system report meant that the borrower was making payments during the period of no reporting. Otherwise, we classified periods of no reporting as missing. We compared monthly outcomes for sold loans and unsold loans after servicing transferred to the purchaser. We set the origin of the observation period to the latest servicing transfer date in each pool of sold loans and their associated matched unsold loans. Because the latest servicing transfer date varied across these groups, the number of observations and the associated dates varied across pools and sales. We measured outcomes for up to a maximum of 48 months, from January 2013 through December 2017, the most recent full quarter of postsale reporting data available at the time of our review. The follow-up periods ranged from the full, 4-year reporting period required by FHA for loans sold in the 2013 sales to 1 year for loans sold in the second sale in 2016. See appendix V for more information on our statistical analysis of outcomes for sold loans and unsold loans. To examine the extent to which loan-pool characteristics were associated with bidder participation for FHA loan sales and the enterprises’ nonperforming loan sales, we built regression models. We identified from interviews key characteristics (independent variables) that may make loan pools attractive to certain bidders, such as having a single servicer or low vacancy. We obtained bid-day data from FHA and the enterprises that included the number of bidders (dependent variable) and the winning bid amounts, as well as the timing of the sale. We generated FHA pool characteristics from the loan level data in FHA’s submitted loan database and supplemented it with FHA default status data (see table 2 above for further information about FHA’s data sets). For the enterprises, we obtained pool characteristics from a published FHFA report. This report provided a range of characteristics to compare to those of FHA’s pools. See table 3 for our regression estimates of the relationship between pool characteristics and the number of bidders in FHA’s DASP sales and the enterprises’ sales. The associated p-values are presented in parentheses, and *, **, and *** denote significance at 10 percent, 5 percent, and 1 percent or better, respectively. In the report body we use the 95 percent confidence level as indicating significance of the regression estimates. To assess the reliability of the FHA data, we performed reasonableness checks that resulted in the removal of FHA’s 2010 sale due to a large number of invalid case numbers and two additional pools from later sales, we also removed pools based on missing or invalid date—in total 4 percent of FHA’s pools. We did not independently verify the data in the FHFA reports, but we interviewed the FHFA staff that generated the report about the reliability of the data. Some limitations stem from the differences between FHA’s and the enterprises’ pools and the underlying loans as well as the data available on the pools. For example, we use data from FHA sales from 2011–2016 and from sales in 2015–2017 for the enterprises. We use the time variables to control for housing market differences as well as the defaulted loan sale market. Additionally, we included FHA’s nontraded pools but not the enterprises’ nontraded pools because the FHFA reports did not present data on these pools. We showed the differences and similarities across the entities in figure 14 in the report. We determined that data for the remaining pools were sufficiently reliable for examining the association of pool characteristics with bidder participation and for comparison between the enterprises’ and FHA’s sales. To calculate pool reserve prices, we obtained FHA data on quarterly loss severity by disposition method for 2013–2016. Using our results from the outcomes comparison analysis, we calculated pool-level reserve prices and compared them to winning pool-level bids. To assess the effect that changing FHA’s auction design could have on the MMI Fund and to identify elements of a successful auction structure, we reviewed economic literature on auction structures and auction descriptions in business and commercial literature. To compare the DASP auction structure with the enterprises as well as mortgage auctions in the private market, we analyzed agency and enterprise documents and interviewed market participants. We developed a detailed description of FHA’s and the enterprises’ current auction structures, including information about the nature of the loan pools being auctioned; about sellers, purchasers, and other auction stakeholders; and about the benefits and drawbacks of the auction design. In interviews, we received suggestions about aspects of FHA auctions that, if changed, may increase bidder participation. To examine these aspects, we interviewed purchasers on their potential interest in these changes and examined FHA sale data following an instance of a single purchaser winning all the pools in a sale. To assess the DASP auction structure, we compared it to selected characteristics of successful auctions and determined the extent to which the characteristics were used by FHA. We conducted this performance audit from January 2017 to July 2019 in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives. This appendix includes descriptive information about the Federal Housing Administration’s (FHA) Distressed Asset Stabilization Program (DASP) servicers, purchasers, and sold loans. The information presented is generally based on loans sold in DASP sales that occurred between 2013 and 2016. Thirty-two servicers participated in DASP sales between fiscal years 2013 and 2016, with the largest participating servicer offering 48 percent (more than 44,000) of the loans sold. As seen in figure 15, the number of servicers increased from nine in the first sale in 2013 to 22 in the second sale in 2016. During this same period, 26 purchasers participated in the DASP sales, with the largest participating purchaser buying 27 percent (about 25,000) of the loans sold. The share of loans offered by individual servicers also varied over time and by sale. One or two servicers offered the majority of sold loans in earlier sales, but more servicers offered a greater share of the loans sold in later sales (see fig. 16). For example, one servicer offered 89 percent of the loans sold in the first sale in 2013, about 51 percent of the loans sold in the second sale in 2014, and about 8 percent of the loans sold in the second sale in 2016. During this time, new servicers began offering loans for sale, and servicers that had offered a smaller share of the loans sold in earlier sales began offering a larger share of loans for sale. Occupancy status. The majority of properties sold through DASP were occupied by the borrower, with a smaller portion having been vacated (see fig. 17). DASP purchasers told us that their ability to contact and engage borrowers is one determinant in whether they are able to offer loss mitigation options to avoid foreclosure. One purchaser noted that in cases where it is unable to contact the borrower, which may indicate that the property is vacant, it tries to foreclose as quickly as possible. Delinquency. The majority of loans sold through DASP had missed 12 or more payments (see fig. 18). As discussed earlier, a loan becomes delinquent after a borrower misses a single payment, and goes into default after it is two payments past due. Generally, servicers must utilize a loss-mitigation option or initiate foreclosure within 6 months of default. As we previously reported, serious delinquency is among the factors associated with an increased likelihood of foreclosure. Loan-to-Value (LTV) ratio. About 18 percent of sold loans had an LTV ratio of 110 or greater (see fig. 19). The LTV ratio represents the unpaid principal balance of a loan as a percentage of the current property value. As we previously reported, negative equity or a high LTV ratio is among the factors associated with an increased likelihood of foreclosure. Origination. As figure 20 shows, sold loans were more likely to have originated at the peak of the housing crisis in 2008 and 2009. FHA officials told us that they used DASP to reduce the significant backlog of defaulted loans they were faced with following the housing crisis. In this appendix, we describe the documents the Federal Housing Administration (FHA) uses to guide the Distressed Asset Stabilization Program. The documents listed in table 4 represent the current written procedures and guidance that FHA planned, as of May 2018, to incorporate into a single document—the Asset Sales Handbook—to centralize the information for internal and external stakeholders. We examined the different types of actions purchasers have used to modify loans they purchased through the Distressed Asset Stabilization Program (DASP) and the expected effect of each type of action on borrowers’ payments. Table 5 summarizes our findings on postsale modification actions. Our analysis was limited to modifications reported using reporting codes introduced in the purchaser agreement for the first sale in 2016, and included loans sold between fiscal years 2013 and 2016. We found that the Federal Housing Administration (FHA) may not have the data it needs to determine whether payment-lowering modifications offered by purchasers were sustainable—for example, a modification in which a low payment was later adjusted to higher than what it was prior to modification. Therefore, we could not determine the long-term effect on payment for many modifications offered by purchasers, as noted by “unclear” in the last column of table 5. This appendix provides additional methodological details on our analysis to compare outcomes between loans sold through the Distressed Asset Stabilization Program (DASP) and a comparison group of similar unsold loans. The analysis consisted of two parts: (1) applying statistical methods for constructing matched comparison groups and (2) estimating a statistical model of loan outcomes using the matched sample of loans. We matched one unsold loan to each sold loan, using exact and Mahalanobis distance matching methods. We matched exactly on occupancy status, state, and loan servicer, and we matched the distributions of loan delinquency period, loan-to-value ratio (divided into five categories), geographic coordinate, and origination year. Unsold loans could be matched multiple times in order to maximize the degree of similarity between the sold and unsold loans, given constrained sample sizes of potential comparison loans. (That is, we used one-to-one matching with replacement.) Matching occurred separately for each loan sale in order to measure the matching variables 2 months before each sale occurred. We assessed the quality of candidate matched samples by consulting univariate empirical-QQ plots, descriptive statistics, and multivariate Kolmogorov-Smirnov tests of equal distributions for each of the matching variables, as implemented in the “Matching” package for the statistical software, R, version 3.5.1. We attempted to match exactly within the smallest geographical area that sample sizes allowed. Location is important for the outcomes of Federal Housing Administration (FHA) loans and is potentially correlated with many unobserved variables, such as local housing market conditions. After experimenting with multiple geographic areas, such as the census tract and county, we chose a strategy of matching exactly on state and matching in distribution on latitude, longitude, and product. This ensured that the comparison loans were in the same states as the sold loans, which held constant differences in foreclosure processes and other political and legal differences. Although the matched loans were potentially in different counties or municipalities than the sold loans, generally they were still close to each other, as measured by the geographic coordinates. We obtained a similar matched sample of comparison loans for each loan sale, as summarized in table 6 and figures 21 and 22. Although we conducted the matching separately for each sale (exactly matched), we combined the sales and their matched comparison loans for the purpose of summarizing their similarity across the matching variables. We used statistical modeling methods designed for longitudinal time-to- event or “duration” data to compare outcomes for sold and matched unsold loans. Conventional duration methods, such as “competing risks” models, would estimate the probability that a loan experienced one or more terminal outcomes by a certain follow-up time. These methods assume that event times are observed exactly, and that no outcome can occur more than once. These assumptions were not realistic for our analysis. Loans could transition among several nonterminal outcomes over time, such as reperforming or temporary action, before experiencing a terminal outcome, such as foreclosure. Our data sources measured the status of unsold loans monthly and sold loans quarterly. However, events could occur on any date, in continuous time, so the status of each loan was unknown between pairs of reporting times (or interval-censored). We used Multi-State Markov models to account for these features of the data. Our models assumed a directed graphical structure for how loans could transition among events between observed follow-up times, as described in figure 23. We developed our model of possible transitions based on FHA’s typical process for managing unsold delinquent loans and DASP program rules for managing sold delinquent loans. To simplify the model, we did not allow paths for transitions that were infrequently observed, illogical, or inconsistent with prior knowledge about loan management. These unusual transitions in the data may reflect misclassified outcomes or transitions through unobserved outcomes between observation times. Table 7 gives the sample counts of the transitions in the matched sample of loan-month observations. The graphical version of our model implied a matrix of modeled transitions among outcomes, with transition probabilities set to 0 for paths between outcomes not shown in the graph. Specifically, we defined the loan outcomes at time t, Y, as a stochastic process, taking values according to an underlying model of transition probabilities from time 0 to t: where r and s denoted two outcomes from the set of outcomes above in table 7, such as unresolved and reperforming. Consistent with existing literature, we assumed that the outcome process was a time- homogenous Markov chain. This assumption made the model mathematically tractable, but required the transition probability at any follow-up time to be independent of prior outcomes and constant over the observation period. (We estimated versions of the model that relaxed this assumption, as described below.) Under this assumption, we modeled the transition hazard rate from outcome r to s as: where x and βrs were vectors of covariates and transition-specific parameters (excluding an intercept) and qrs was an unspecified proportional baseline hazard. All covariates were time-invariant characteristics of the loans measured at baseline, 2 months prior to the loan’s bid date, used to create the matched sample. We estimated βrs using maximum likelihood estimation methods, as implemented by the “msm” package in R 3.5.1. The body of this report provides estimated transition probabilities for various groups of loans, including loans that were sold or unsold. We estimated the probability of a loan’s transitioning from unresolved at t = 0 to some other outcome at t using the estimated parameters and the matrix exponential P(t) = exp(tQ), where P and Q are the matrices of transition probabilities and hazards, respectively, for all outcomes r and s. We used Monte Carlo simulation from the fitted multivariate normal distribution of the parameters to estimate 95 percent confidence intervals for the transition probabilities, using 1,000 draws. In appendix VI, we provide more detailed estimates of these transition probabilities and their confidence intervals for key findings discussed in the body of this report. Our models estimated the difference in transition probabilities between sold and unsold loans in the matched sample by including an indicator for sold status in x. We estimated transition probabilities for certain subpopulations of loans, like specific purchasers or loan sales, by estimating separate models for each subpopulation. This approach allowed the models to be fully stratified and reduced computational burdens associated with estimating many parameters using a sample of 1 million or more observed transitions, as a fully interactive specification between sold status and the subpopulation variables would have required. However, this approach prevented us from estimating the partial interactions between sold loan status and the subpopulation variables. We conducted several validation and robustness checks of the analyses reported in the body of this report. These included the following: Predictive fit. We did not design our models to predict future outcomes but rather to make inferences about the difference in transition probabilities between sold and matched unsold loans. However, to identify substantial problems with model fit, we compared the observed prevalence of each outcome to the estimated prevalence expected under our models. Figure 24 shows the predictive fit for models with a covariate in x for sold status and a piecewise-constant indicator for the period after month 12. The estimated and observed prevalence are generally close for most outcomes before month 40. After that month, the model underestimates the prevalence of foreclosure and overestimates the prevalence of unresolved. This lack of fit late in the observation period may reflect the substantial effect of sales cohort, which we modeled through separate models stratified by sale rather than as a covariate. In any case, the model fit was acceptable, given our nonpredictive use of the model and the limitations of using observed outcome prevalence rates to validate predictions of a process with interval censoring. Time-inhomogenous models. We relaxed our assumption that the transition intensities were constant throughout the observation period by including indicators in x for whether the observation fell before or after 12 months. FHA changed DASP rules before the 2015 sales to extend the moratorium on foreclosures from 6 months to 12 months. Outcome transition estimates from a model including these time indicators plus a sold indicator appear in table 8, along with our base estimates from a time-homogenous model with only the sold indicator. Although Akaike Information Criterion values showed that the piecewise model improved the fit, the estimated transition probabilities generally supported the same substantive conclusions. The piecewise model estimated that sold loans were somewhat more likely to transition to a short sale or deed-in-lieu outcome, and somewhat less likely to transition to reperforming, but the direction of the association was the same as in the time-homogenous model. We used the time- homogenous model to provide results in the body of this report and in appendix VI, due to the considerable computing time required to estimate models with piecewise-constant covariates. In this appendix, we provide data for selected borrower outcome figures presented in this report. We also provide additional outcome figures and data, as well as outcome data for sold loans and unsold loans by some loan-level characteristics. These figures and data are based on the statistical matching and modeling analysis of loans sold through the Distressed Asset Stabilization Program (DASP) and similar, unsold loans described in appendix I and appendix V of this report. Tables 9–12 present data for selected outcome figures shown in the report. Table 9 presents estimates of foreclosure and foreclosure avoidance outcome rates for sold loans and similar, unsold loans, based on statistical models (fig. 7). Table 10 presents these estimates for out-of- home and in-home outcomes (fig. 8). Figure 9 in the body of this report shows the foreclosure and foreclosure avoidance outcomes by DASP sale, and tables 11 and 12 present these estimates for all outcomes by DASP sale, 12 and 24 months following the servicing transfer date, respectively. As discussed in appendix I, to compare foreclosure and foreclosure avoidance outcomes for sold and unsold loans, we assigned loans to one of six outcome categories. Figure 25 and table 13 present the outcome figures and associated data for sold and unsold loans across all six categories. Figures 26–29 compare specific outcomes for sold and unsold loans across different loan characteristics. We selected characteristics and outcomes that showed clear patterns or differences between sold and unsold loans. Our analysis showed that the loan-to-value (LTV) ratio was less strongly associated with reperforming rates for sold loans compared to similar, unsold loans (see fig. 26). For example, while the probability of reperforming varied across different LTV ratio categories for unsold loans, the probability varied less for sold loans. Our analysis of outcomes by different delinquency categories showed that length of delinquency was less strongly associated with reperforming rates for sold loans compared to similar, unsold loans (see fig. 27). For example, while the probability of reperforming 12 months after the servicing transfer date ranged from 8 to 29 percent across different delinquency lengths for unsold loans, this range was smaller for sold loans—about 9 to about 16 percent. Our analysis of outcomes by year of loan origination showed that length of delinquency was less strongly associated with reperforming rates for sold loans compared to similar, unsold loans (see fig. 28). For example, the year of loan origination did not affect the probability of reperforming for sold loans. However, for unsold loans the probability of reperforming was lowest for loans originating in 2007–2008 at the beginning of the housing crisis. Our analysis of outcomes by occupancy showed that, for occupied properties, sold loans were more likely to experience foreclosure compared with similar, unsold loans (see fig. 29). However, for vacant properties, sold loans experience foreclosure at equal or smaller rates compared to similar, unsold loans. The Federal Housing Administration (FHA) uses a pooled, highest-bidder, sealed-bid auction structure to sell its single-family defaulted residential mortgages through the Distressed Asset Stabilization Program (DASP). This auction structure is consistent with industry standards and private market practices for selling these mortgages and includes many characteristics of a successful auction. We identified characteristics of successful auctions by reviewing economics literature on auction structures and auction descriptions in business and commercial literature, and we obtained information about the nature of the loans being auctioned, about sellers, purchasers and other auction stakeholders, and about the benefits and drawbacks to each of various details of the auction design. Table 14 shows some auction characteristics and an evaluation of FHA’s DASP design. In addition to the contact named above, Jill Naamane (Assistant Director), Rhonda Rose (Analyst in Charge), Abigail Brown, Stephen Brown, Karen Jarzynka-Hernandez, John Karikari, May Lee, Ned Malone, Paulina Maqueda-Escamilla, John McGrail, Samuel Portnow, Tovah Rom, Jena Sinkfield, Anne Stevens, Jeff Tessin, Jim Vitarello, Sarah Wilson, and Elisa Yoshiara made key contributions to this report. Also contributing to this report were DuEwa Kumara and Jason Rodriguez.
HUD insures single-family mortgage loans and is authorized to sell defaulted loans under the National Housing Act. In fiscal years 2010–2016, FHA auctioned off approximately 111,000 loans to private purchasers under DASP. DASP helped reduce a backlog of federally insured defaulted loans stemming from the 2007–2011 financial crisis and was intended to protect the MMI Fund by paying insurance claims before the costly foreclosure process. GAO was asked to evaluate DASP. This report examines, among other things, certain DASP procedures, including verifying loan eligibility criteria, and documentation; FHA's evaluation of the identified outcomes of sold loans and how these compare with similar, unsold loans; and the potential effects that changes to DASP might have on the MMI Fund. GAO reviewed FHA policies, contracts, and reports, and interviewed FHA officials, selected servicers and purchasers based on sales participation, and other stakeholders. GAO also conducted a statistical analysis comparing outcome data for sold loans and similar loans that remained FHA-insured and analyzed the effect of loan pool characteristics on bidder participation. The Department of Housing and Urban Development's (HUD) Federal Housing Administration (FHA) uses multiple entities to check loan eligibility for the Distressed Asset Stabilization Program (DASP)—in which FHA accepts assignment of eligible, defaulted single-family loans from servicers in exchange for claim payments and sells the loans in competitive auctions. After servicers submit loans for sale, FHA and its contractors concurrently check loan data for completeness, validity, and eligibility. FHA relies on servicers to check eligibility a few weeks before and again after the bid date. The status of delinquent loans can be fluid, and a change in eligibility status close to this date may not be detected. GAO's analysis of fiscal year 2016 default data indicates about 2.67 percent of loans that FHA sold were ineligible based on length of delinquency or loss mitigation status. Without checking loan eligibility closer to bidding, FHA risks selling ineligible loans, and borrowers could lose access to benefits. FHA does not evaluate outcomes for sold loans against similar unsold loans. GAO found that, in aggregate, sold defaulted loans were more likely to experience foreclosure than comparable unsold defaulted loans (see figure). However, GAO's analysis identified varying outcomes by purchasers and sales. For example, some purchasers' loans had higher probabilities of avoiding foreclosure, with borrowers making regular payments again by 24 months after the transfer of loans. Also, loans sold in 2016 sales were less likely to experience foreclosure compared to unsold loans. HUD policy states that the agency's evaluations isolate program effects from other influences. Evaluating outcomes for sold loans against similar unsold loans could help FHA determine whether DASP is meeting its objective of maximizing recoveries to the Mutual Mortgage Insurance Fund (MMI Fund) and understand the extent to which DASP helps borrowers. Changing some of FHA's auction processes may help the MMI Fund. FHA could increase participation and MMI Fund recoveries in its auctions by communicating upcoming sales earlier. One purchaser said that additional notice would allow it time to plan for the capital needed to bid. Also, FHA set reserve prices (minimum acceptable price) based on the amount it expected to recover after loans completed foreclosure—yet GAO estimates that some of these loans will avoid foreclosure (see figure). As a result, FHA risks recovering less for the MMI Fund in loan sales than if the loans had not been sold. GAO is making nine recommendations to FHA, including establishing specific time frames to check loan eligibility, evaluating loan outcome data, and changing auction processes to help protect the MMI Fund. FHA generally agreed with seven recommendations, and neither agreed nor disagreed with two. GAO maintains that all the recommendations are valid.