Rural Housing Service: Actions Needed to Strengthen Management of the Single Family Mortgage Guarantee Program
Released: 2016-05-02T00:00:00

Letter

Background

RHS Guarantee Program

RHS, a component of USDA’s RD mission area, is responsible for rural housing and community facilities programs. Under the single-family guarantee program, RHS provides lenders guarantees on residential mortgage loans to households with low to moderate incomes in areas statutorily designated as rural. The guarantees cover 30-year fixed-rate loans made to purchase a home or refinance an existing RHS direct or guaranteed loan. The guarantee program requires no down payment from borrowers and currently charges a 2.75 percent up-front guarantee fee (which borrowers may finance in the approved loan amount) and a 0.5 percent annual guarantee fee. The guarantee provides coverage for eligible losses of up to 90 percent of the original loan balance, including unpaid principal and interest, principal and interest on USDA-approved advances for protection and preservation of the property, and the costs associated with selling a foreclosed property.

Lenders and Servicers

RHS-approved lenders and servicers originate, underwrite, and service the mortgage loans that RHS guarantees. According to RHS, in fiscal year 2014, about 1,700 lenders originated loans guaranteed by RHS. A borrower (home buyer) applies for a guaranteed loan through an RHS- approved lender. Since 2006, RHS has provided an automated underwriting system for lenders to submit loan information and determine borrower eligibility. RHS staff are to review the loan information and, if it meets RHS’s requirements, issue a conditional commitment to guarantee the loan. Upon receiving and satisfying the commitment conditions, the lender closes the loan and submits the closing package to RHS. After reviewing the closing package, RHS issues the loan guarantee. A lender may service its own loans—including collecting monthly mortgage payments, maintaining escrow accounts for property taxes and hazard insurance, and conducting loss mitigation activities—or pay a fee for another organization to service its loans. Servicers also are responsible for liquidating foreclosed properties.

In December 2014, new program regulations went into effect that expanded the pool of lenders eligible to participate in the guarantee program. With the regulation change, any lender supervised and regulated by the Federal Deposit Insurance Corporation, the National Credit Union Administration, the Office of the Comptroller of the Currency, the Federal Reserve System, or the Federal Housing Finance Board was eligible. According to RHS, the regulation enables many small community banks and credit unions that were ineligible prior to the change in regulations to participate in the guarantee program.

National, State, and Local Offices

RD offices at the national, state, and local levels play important roles in the guarantee program. The Single Family Housing Guaranteed Loan Division in Washington, D.C., is responsible for developing, implementing, and monitoring program policy and procedures. The division’s functions include legislative and budget planning; management reporting; issuance of regulatory and policy directives; portfolio monitoring; and approval, training, and review of nationwide lenders and servicers. RD state and local offices conduct program operations within their geographic jurisdictions. Their responsibilities include approving lenders that operate in a single state to participate in the program and monitoring the lenders’ underwriting and servicing of guaranteed loans. In addition, staff in state and local offices are responsible for reviewing loan applications and closing documentation and issuing conditional and final loan guarantee commitments. They also are to provide loan servicing guidance to lenders and servicers and train lenders on program requirements.

Other offices play key roles in administering and overseeing the guarantee program including, but not limited to, the following:

RHS’s Centralized Servicing Center (CSC) in St. Louis, Missouri, reviews and approves lender loss-mitigation efforts and lender claims, among other functions.

RD’s Office of the Chief Financial Officer calculates credit subsidy estimates and reestimates; oversees periodic management control reviews and state internal reviews of RD programs, including the guarantee program; and reviews documentation related to implementation of USDA Office of the Inspector General audit recommendations and forwards it to USDA’s Office of the Chief Financial Officer, which determines whether the recommendation can be closed.

Requirements for Estimating Credit Subsidy Costs

Under FCRA, USDA and other federal agencies must estimate the credit subsidy costs of their direct loan and loan guarantee programs and include the costs to the government in their annual budgets. Agencies annually estimate credit subsidy costs for each program by cohort—the loans agencies commit to insure or guarantee in a given fiscal year. The credit subsidy cost is equal to the net present value of estimated lifetime cash flows to and from the government, excluding administrative costs. For a mortgage guarantee program, cash inflows consist primarily of premiums received from borrowers and cash outflows consist mostly of claim payments to lenders. Credit programs have a positive subsidy cost when the present value of estimated payments by the government exceeds the present value of estimated premiums and other funds received by the government (collections). When credit programs have a positive subsidy cost, they require appropriations. Conversely, negative subsidy programs are those in which the present value of estimated collections is expected to exceed the present value of estimated payments.

FCRA requires that agencies have budget authority to cover credit subsidy costs before entering into credit transactions. To estimate their subsidy costs for annual appropriation requests, credit agencies estimate the future performance of direct loans and loan guarantees. Agencies are responsible for accumulating relevant, sufficient, and reliable data on which to base these estimates. To estimate future credit performance, agencies generally have models that include assumptions about defaults, prepayments, recoveries, and the timing of these events and are based on the nature of their credit programs. As needed, agencies also incorporate economic assumptions provided by the President into credit subsidy calculations. Further, OMB requires agencies to discount cash flows using projected Treasury interest rates that are consistent with the economic assumptions underlying the President’s budget. The discount rates are used to derive the present value of future cash flows that, in turn, indicate the credit subsidy costs. The costs can be expressed as a rate. For example, if an agency commits to guarantee loans totaling $1 million and has estimated that the present value of cash outflows will exceed the present value of cash inflows by $15,000, the estimated credit subsidy rate is 1.5 percent.

Under FCRA, agencies generally must produce annual updates of their credit subsidy estimates—known as reestimates—of each cohort based on information about the actual performance and estimated changes in future credit performance. This requirement reflects the fact that estimates of credit subsidy costs can change over time. Beyond changes in estimation methodology, each additional year provides more historical data on credit performance that may influence estimates of the amount and timing of future cash flows. Economic assumptions also can change from one year to the next, including assumptions on interest rates. When reestimated credit subsidy costs exceed agencies’ original cost estimates—resulting in an upward reestimate—the additional subsidy costs are not covered by new discretionary appropriations but rather are funded from permanent, indefinite budget authority.

OMB Circular A-129

In January 2013, OMB reissued its Circular A-129, which provides guidance to federal agencies on managing credit programs. The guidance addresses key aspects of managing a loan guarantee program, including assessing the eligibility and creditworthiness of borrowers, overseeing guaranteed loan lenders and servicers, developing performance indicators and risk thresholds, and analyzing and reporting on portfolio risks. The circular also provides guidance on management structures, including the need for risk-management functions that are independent from credit program administration. According to OMB staff, the 2013 update to the circular incorporated best practices for risk management. RD’s Office of the Chief Financial Officer has primary responsibility for ensuring the guarantee program’s compliance with the circular.

Estimated Costs of Guarantee Program Have Risen, and Rural Development Has Enhanced Its Cost Estimation Process

In part due to the recent housing crisis, the estimated credit subsidy costs of RHS’s guarantee program rose in recent years. RD uses information on historical average performance to develop its cost estimates, although it adjusted its method in recent years to account for the effects of the housing crisis. Furthermore, RD has been developing econometric (statistical) models to estimate future credit subsidy costs that should help address the limitations of its current method, such as reduced reliability when economic conditions vary from those in the past.

Losses from the Housing Crisis Contributed to an Increase in Credit Subsidy Reestimates

RHS estimated the initial subsidy rates of its most recent single-family mortgage guarantee cohorts to be around zero. As required by FCRA, RD annually estimates the credit subsidy cost of the loans it plans to guarantee in the upcoming fiscal year and reestimates credit subsidy costs for prior loan cohorts. According to RHS officials, since 2010 RHS has had the goal of making each new loan guarantee cohort “subsidy neutral”—that is, initially, the present value of lifetime estimated cash inflows equals the present value of lifetime estimated cash outflows. Accordingly, the initial credit subsidy rate estimates for the 2011 through 2014 cohorts were close to zero (ranging from -0.04 percent to -0.25 percent). However, the current reestimated rates for the 2011 and 2012 cohorts are slightly positive (1.39 percent and 0.86 percent, respectively). The current reestimated rates for the 2013 and 2014 cohorts—the most recent cohorts to be reestimated—are slightly negative, each at -0.31 percent.

The reestimated costs of the RHS guarantee portfolio as a whole substantially increased in recent years. In part, the larger reestimates reflected growth in the size of RHS’s loan cohorts. RHS has submitted net upward credit subsidy reestimates—expectations that the guaranteed portfolio as a whole will cost more or produce less revenue than previously estimated—in 8 of the last 11 years (see fig. 1). The upward reestimates for fiscal years 2012 through 2014 were significantly larger than those of prior years. For example, the reestimates for 2012, 2013, and 2014 were $364 million, $804 million, and $615 million, respectively, compared with $42 million for 2010. A change in the estimated subsidy rate (even a small one) will result in larger reestimated amounts in dollar terms for relatively larger loan cohorts because the change would apply to a higher dollar volume of loans. RHS guaranteed fewer than 40,000 loans annually from 1992 (the first year RHS made guarantees nationwide) through 2007, but volume grew significantly from 2008, when RHS guaranteed about 62,000 loans, through 2014 when RHS guaranteed about 140,000 loans. The total amount of guarantees outstanding increased from less than $22 billion in 2008 to more than $100 billion in 2014.

According to RD management, the large upward credit subsidy reestimates for fiscal years 2013 and 2014 also were due to higher-than- expected loss amounts (claims paid to lenders after defaults) and to changes in the estimation methodology RD used those years (discussed later in this report). RD’s financial statement auditor for federal credit subsidy issues (credit subsidy auditor) agreed with RD management’s explanation. Cumulative loss rates (total losses divided by the dollar volume of loans guaranteed) were especially high for cohorts guaranteed directly before and during the early years of the 2007 through 2011 housing crisis. (In a loan cohort, losses are expected, and any losses are offset in part or in whole by guarantee fees.) As of the end of fiscal year 2014, the 2007 cohort had the highest cumulative loss rate of any cohort since 2000, followed by cohorts from 2006, 2005, and 2008, respectively (see fig. 2). For example, the 2007 cohort had a cumulative loss rate of almost 10 percent. In contrast, the 2003 cohort had a cumulative loss rate under 3 percent at the comparable point in its life cycle (8 years) and a cumulative loss rate of 4.7 percent at the end of 2014. The higher losses for these cohorts may have stemmed from homeowners’ inability to build equity before housing prices declined. Borrowers who owe more on their mortgages than their homes are worth may be more likely to default because (1) they may not be able to sell or refinance their homes to relieve unsustainable mortgage payments and (2) they may choose to stop making mortgage payments to minimize losses. Furthermore, when lenders foreclose on the borrowers, the lower home values reduce the amount that lenders recover through sale of the properties, resulting in higher losses for RHS.

As shown in figure 2, cohorts guaranteed since 2010 had lower loss rates in each year of their life cycle after the first year than all other cohorts since 2000. For example, the 2011 cohort had a 0.3 percent cumulative loss rate at the end of fiscal year 2014, whereas the 2000 cohort had a 1.6 percent rate at the comparable point (after 4 years). Improved economic conditions as well as other factors contributed to the improved performance of recent cohorts. For example, a report from USDA’s Office of the Inspector General on RD’s fiscal year 2014 financial statements noted that losses that year were lower than expected for the 2012 through 2014 cohorts as a result of stricter credit requirements RHS had implemented in response to the housing crisis. For instance, in 2009, RHS began requiring lenders to provide additional documentation to waive RHS underwriting guidelines for maximum borrower debt ratios and adverse credit histories. Also, according to an RHS official, some lenders may have tightened credit standards more than required by RHS as a result of the housing crisis and the risks associated with managing defaulted loans.

Rural Development Has Been Developing Econometric Models to Address Limitations of Its Cost Estimation Method

Current Process for Estimating Credit Subsidy Costs Is Based on Historical Averages

RD—the USDA division that estimates the credit subsidy costs of RHS’s guarantee program—averages historical information on loan performance to estimate certain expected cash outflows and inflows for loan cohorts. As previously noted, cash outflows consist primarily of losses (claims paid to lenders after defaults) and inflows primarily of fees from borrowers and recoveries. In turn, the expected cash flows are inputs in the calculations that produce estimates of credit subsidy costs. Federal guidance states that the historical averages method is an acceptable approach for estimating credit subsidy costs.

Beginning with the credit subsidy cost estimate for the 2013 cohort, RD has calculated average loss and recovery rates using the total dollar amounts of losses and recoveries for all prior loans. Previously, RD calculated the rates by averaging the average loss and recovery rates for all prior loan cohorts. By using total dollar amounts instead of an average of individual loss and recovery rates, RD’s method of projecting losses and recoveries for new loans accounts for variations in the size of loan cohorts. That is, the method gives more weight to the performance of large cohorts than smaller ones.

To project losses and recoveries for a new cohort, RD averages historical information on loan performance (from 1992 through the last complete fiscal year). To illustrate, RD calculates the expected first-year loss rate for a new cohort as the total losses experienced by all prior cohorts during their first year divided by the total dollar amount of guarantees for loans aged at least 1 year. RHS then performs the calculations for the second-year loss rates and so on. RD calculates expected recovery rates—total recoveries divided by the total dollar amount of losses—in a similar manner.

RD also projects cash inflows from annual and up-front guarantee fees. To project the annual guarantee fees for a new cohort, RD first estimates what portion of loans will prepay using a historical average method similar to the one used to estimate losses and recoveries. RD calculates an expected prepayment rate for each year of the new cohort’s life using data on the prepayment experience of prior cohorts in corresponding years. RD then uses the expectations for prepayments and loan terminations (for example, defaulted loans resulting in loss claims) to estimate the total outstanding loan balance expected at the end of each year of the cohort’s life. More specifically, RD reduces the amount of the estimated outstanding loan balance by the amount of prepayments and terminations expected each year. RD calculates the annual fee revenue using the estimated outstanding loan balance and the annual fee rates in effect at the time the guarantees were made. Finally, RD bases its estimate of cash flows from up-front guarantee fees on the dollar value of loans expected to be guaranteed in the given budget year and the guarantee fee percentage in effect.

Then, to estimate the credit subsidy rate for a new cohort, RD runs its cash flow projections for losses, recoveries, and fees through OMB’s credit subsidy calculator. This tool produces the net present value of the cash flows, which is the credit subsidy cost estimate for that cohort, and an associated credit subsidy rate.

RD Adjusted Its Reestimation Method to Account for Effects of the Housing Crisis on Loan Performance

The methodology RD currently uses to calculate reestimates includes certain adjustments made in 2012, 2013 and 2014 intended to more accurately predict cash flows by accounting for the effects of the housing crisis. To calculate reestimates, RD generally uses the same historical averages methodology that it uses to calculate the original credit subsidy estimates for new cohorts. However, according to RD officials, for the 2013 and 2014 reestimates, RD made adjustments to this method, as follows: Increased loss expectations for cohorts most affected by the housing crisis (2005 through 2008 cohorts). RD’s credit subsidy auditor found that during the housing crisis, the historical averages method underpredicted losses for certain cohorts. To more accurately predict losses, the credit subsidy auditor recommended that RD assess whether it should make manual adjustments to the reestimate calculations for cohorts most affected by the crisis. As a result of this assessment, RD increased loss amounts used to calculate the average loss rates for the 2005 through 2008 cohorts. RD increased the losses by a percentage equivalent to the difference between the defaults predicted when using the historical averages approach for each cohort and the actual defaults experienced by each cohort in the most recent fiscal year.

Decreased losses for cohorts made with higher credit standards (2009 through 2014 cohorts). In a 2012 report, RD’s credit subsidy auditor also found that the historical averages method was likely overpredicting losses for the 2009 through 2012 cohorts. Similarly, an RD analysis in 2014 (that did not include the 2014 cohort) showed that this method overpredicted losses for the 2009 through 2013 cohorts. According to RD, the overprediction of losses was due to the historical averages method incorporating the unusually high defaults of the 2005 through 2008 cohorts into the default projections for the more recent cohorts. In addition, the cohorts guaranteed in 2009 and later were originated using higher borrower credit standards, which lowered their default risk, according to RD. To reduce the overestimation of losses for more recent cohorts, RD removed the default data for the 2005 through 2008 cohorts when calculating historical average loss rates for certain cohorts. For example, for the 2014 reestimate, RD removed these data from the loss rate calculation for the 2009 through 2014 cohorts.

Third parties that reviewed these manual adjustments found them to be acceptable. For example, RD’s credit subsidy auditors found the adjustments to be reasonable, and OMB approved the methodology used to calculate the reestimates. In 2013 and 2014, respectively, a consultant and RD conducted analyses that found that excluding the 2005 through 2008 data when estimating cash flows for cohorts of more recent years improved the accuracy of the estimates. But subsequent analysis illustrated some limitations in making manual adjustments to the historical averages method. During the fiscal year 2014 audit, the credit subsidy auditor found that RD still might have been overprojecting defaults for the more recent cohorts even with the data exclusions. Also, in 2014 RD’s credit subsidy auditor found that the revised methodology continued to underestimate losses for the 2007 and 2008 cohorts.

RD Has Been Developing Econometric Models to Address Limitations in Its Estimation Method

In 2014, RD contracted with a firm to develop econometric models to predict loan performance based on various loan, borrower, and economic variables. Federal guidance states that the historical averages method is an accepted approach for estimating credit subsidy costs, but the method has limitations that may prevent it from reliably predicting cash flows under certain conditions. Specifically, results may be less reliable when economic conditions, program policy, and borrower composition change, as follows:

Economic conditions. When economic conditions vary from those in the past, estimates of future losses based solely on historical averages may not take into account the effects of the changed conditions on future performance. For instance, when interest rates decrease, homeowners may choose to refinance (and therefore prepay) their mortgages to receive lower interest rates. Cost estimates developed using only historical data on loan performance may not account for the increased likelihood of prepayments given the changed economic conditions.

Policy. Policy changes such as changes to underwriting standards may result in new loans having a different default risk than loans made before the change. For instance, changes to loan-to-value ratios or maximum borrower debt ratios allowed by the program may result in borrowers participating in the program who present a different level of risk than previous borrowers.

Composition of borrowers. Even without policy changes, the composition of the borrowers receiving RHS guarantees may change from year to year. For example, the geographic dispersion, average credit scores, or other characteristics of borrowers may shift. These changes may result in changed expectations for the future performance of the loans, which would not be reflected in the loss rates calculated using only historical data.

The firm was contracted to develop the econometric models to estimate the likelihood of claims and prepayments on RHS guaranteed loans—key inputs into estimates of future cash flows used to develop RHS credit subsidy estimates and reestimates. According to the contractor, the models will incorporate RHS’s historical loan performance and borrower data, and economic data that may be predictive of loan performance, such as macroeconomic forecasts and home price forecasts. RD officials indicated that OMB has reviewed and approved the contractor’s models and that RD plans to use the models to develop its initial credit subsidy cost estimate for the 2017 cohort and the 2016 reestimate. Additionally, RD noted that based on its preliminary analysis, the new models will correct for the overestimation of future losses that resulted from using the historical method in recent years. As a result, RHS expects the 2016 reestimate to be a downward reestimate.

According to federal guidance, econometric models have a number of advantages over other methods for estimating credit subsidy costs, such as historical averages and informed opinion. For example, econometric models can identify key relationships between loan performance and economic and other indicators; take into account changes in policy; be easily commented on and reestimated to take comments into be easily transferred between analysts (for instance, if the agency’s knowledgeable staff leave, the model and its key assumptions remain in place).

Certain attributes of econometric models—in particular, the ability to take into account changes in economic conditions or policy—address limitations of the historical averages method that RHS currently uses. To illustrate, RD’s credit subsidy auditor noted that RD’s historical averages method did not produce accurate forecasts when the housing crisis caused losses to deviate from predictable patterns seen in prior years. The auditor reported that the historical averages method may not adequately take into account changes in the composition of borrowers or economic conditions that could materially affect the future performance of the program relative to its historical performance. Furthermore, the auditor said that using an econometric modeling methodology would allow RD to improve the quality of its estimates.

The quality of the credit subsidy cost estimates produced by RD’s econometric models will depend on many factors. In a March 2004 report on another federal guarantee program, we found that the choice of which variables to include in an economic model is based on professional judgement, statistical testing, and economic theory. Excluding key predictive variables can reduce model quality. In addition, model validation is important to help ensure the models continue to be appropriate for the purpose they are intended and are calculating correctly. Further, once the models are developed, regularly updating them is important to help ensure their continued reliability.

In addition to estimating credit subsidy costs, RHS program management may be able to use the econometric models for other risk-management functions. For instance, according to federal guidance, econometric models can be used in policy formulation to estimate how alternative changes to policies would affect future cash flows and thereby the subsidy cost of the guarantees. Econometric models also may allow RHS management to conduct simulations of portfolio performance under different scenarios of future economic conditions. For example, management could stress test the portfolio—a technique that allows managers to measure the vulnerability of the portfolio to unexpected losses. RHS officials told us that they plan to use the econometric models under development to help anticipate and assess potential risk to the program caused by changing conditions such as a future economic downturn.

RHS Has Not Fully Aligned Its Policies and Procedures with OMB Guidance

RHS’s policies and procedures for the guarantee program were consistent with 19 of 26 OMB A-129 standards for managing federal credit programs, but were not fully consistent with the other 7. Specifically, RHS policies and procedures were consistent with 10 of the 11 standards for extending credit, but partially consistent with the remaining standard. The agency’s policies and procedures were consistent with 7 of 9 standards for managing lenders and servicers, but partially consistent with the remaining 2. Finally, the policies and procedures were partially consistent with 4 of 6 standards for credit program management and consistent with the remaining 2.

RHS Policies Were Generally Consistent with OMB Standards for Extending Credit, but Did Not Fully Meet One Standard for Screening Applicants

RHS’s policies and procedures were consistent with Circular A-129 standards for extending credit, with the exception of one standard concerning applicant screening.

Applicant Screening

As shown in table 1, RHS’s policies and procedures were consistent with four of the five A-129 standards for screening applicants and partially consistent with the remaining one. Applicant screening refers to determining an applicant’s eligibility and creditworthiness for a loan.

RHS policies were consistent with the standard for an applicant’s program eligibility and certifications. For example, RHS requires lenders to assess compliance with a number of eligibility requirements—for example, that the applicant’s income is no more than 115 percent of the area median, that the property to be purchased or refinanced is in a designated rural area, and that the applicant is not eligible for “traditional conventional credit.” RHS defines this term as mortgages with 20 percent down payments and other loan and borrower characteristics associated with lower-risk, uninsured private mortgages. Consequently, applicants who may qualify for other types of conventional credit, such as those with private mortgage insurance, or mortgages guaranteed by other federal agencies, such as the Federal Housing Administration (FHA) or Department of Veterans Affairs (VA), also may be eligible for an RHS- guaranteed loan.

However, RHS’s policies and procedures were not fully consistent with the standard that states that the agency must deny an applicant who is subject to an administrative offset to collect delinquent child support payments. An administrative offset is an enforcement remedy that allows for the interception of certain federal payments—for example, tax refunds—to collect past-due child support. RHS policy requires court- ordered payments such as child support to be considered in assessing an applicant’s ability to repay a mortgage. Additionally, RHS officials said that delinquent child support payments should be reflected in an applicant’s credit report and that it was unlikely a lender would approve an applicant with that type of adverse credit history. However, RHS policy does not disqualify applicants solely on the basis of delinquent child support payments and does not address the ineligibility of applicants subject to administrative offsets for past-due child support. Furthermore, RHS has lacked the information needed to identify these ineligible applicants. The Department of the Treasury (Treasury) maintains a database of individuals subject to administrative offset that federal agencies can access through Treasury’s “Do Not Pay” portal. However, RHS officials acknowledged that they had not yet taken the necessary steps to access it because they were not aware of the tool. Consequently, it is possible that applicants subject to administrative offsets for past-due child support may be able to obtain RHS-guaranteed mortgages, contrary to the OMB standard.

Loan Documentation and Collateral

As shown in table 2, RHS’s policies and procedures were consistent with the six standards in Circular A-129 for loan documentation and loan collateral. Loan documentation refers to the maintenance of files containing key information used in loan underwriting. Collateral refers to the assets that secure the loan (for the guarantee program, the mortgaged property).

RHS also has made or has been pursuing process enhancements related to loan documentation and collateral. In March 2015, it implemented a paperless processing system that uses web-based document uploads and electronic signatures to help save the time and expense of sending paper documents between lenders and RHS field offices for every guarantee. In addition, RHS officials told us that they were in discussions with VA, which also administers a loan guarantee program, about an interagency agreement that would allow RHS to use an automated appraisal evaluation tool that VA implemented in June 2015. An RHS official said that the tool would increase the efficiency of the appraisal review process and help identify problematic appraisals, such as those that may overvalue a property.

RHS’s Program Eligibility Policies Did Not Fully Align with Certain OMB Standards for Managing Lenders and Servicers

As shown in table 3, RHS’s policies and procedures for managing entities that originate or service RHS-guaranteed mortgages (lenders and servicers) were consistent with seven of the nine standards in Circular A- 129, but only partially consistent with the remaining two. The circular contains standards for lender and servicer eligibility, monitoring, recertification, and reporting.

The seven standards with which RHS’s policies and procedures were consistent include those concerning on-site reviews of lenders and servicers, review of lender claims, and collection and maintenance of data from lenders and servicers. For example, RHS lenders and servicers are to be subject to periodic compliance reviews conducted either on-site (at lenders’ offices) or off-site (“desk” reviews). RHS’s compliance review guide contains risk factors for prioritizing the reviews. RHS policy also requires reviews of loss claim packages to determine whether lenders fulfilled all program obligations and, if not, whether reduction or denial of the loss claims would be warranted.

However, RHS does not have policies and procedures that address all aspects of two standards for lender and servicer eligibility. First, the circular describes the various lender and servicer eligibility criteria agencies should publish. Although RHS published a Federal Register notice in 2013 containing such criteria, it did not include qualification requirements for principal officers, such as years of experience in the mortgage industry. The notice also does not include financial and capital requirements for lenders not regulated by a federal financial institution regulator (referred to as nonsupervised lenders). RHS officials said they effectively relied on the requirements of other mortgage institutions, such as FHA and VA, because approval by these institutions is generally the means by which nonsupervised lenders become eligible to participate in the guarantee program. They also expressed concern that imposing additional requirements would increase the complexity of the lender approval process. But FHA’s and VA’s requirements differ and may not be well-suited for RHS’s program. For example, FHA calibrates its net worth requirement to the amount of FHA business a lender does. Specifically, FHA requires nonsupervised lenders to have a minimum adjusted net worth of $1 million, plus 1 percent of their total FHA business volume in excess of $25 million, up to a maximum required adjusted net worth of $2.5 million. As such, FHA’s requirement does not take into account any additional risk represented by a lender’s business with RHS. In contrast, VA requires nonsupervised lenders to have a minimum adjusted net worth of $250,000 or have at least $50,000 in working capital, regardless of lending volume. The suitability of VA’s net worth requirement for RHS may be limited, among other things, by VA’s lower loss coverage for lenders—from 25 percent to 50 percent compared with up to 90 percent for RHS. In previously issued work, we discussed the view of some mortgage industry observers that a lower level of loss coverage may provide lenders an incentive to improve underwriting quality, thus reducing the risk of default. By not specifying its own requirements, RHS increases the potential that entities that originate and service RHS-guaranteed mortgages may lack the experience and financial soundness to perform these functions in a manner that protects RHS’s financial interests or lack the ability to cover any liability for violations of RHS requirements.

Second, the circular states that agencies should review and document a lender’s or servicer’s eligibility at least every 2 years. According to RHS officials, the agency’s practice is to biennially assess the eligibility of previously approved lenders and servicers and to maintain documentation of eligibility in paper files. They said that they issue instructions every other year directing staff to complete the eligibility reviews within 180 days of the issuance date. However, RHS has not established standing written policies or guidance requiring eligibility reviews to be completed at least every 2 years. RHS officials said they had not seen the need to disclose the 2-year review cycle to lenders by putting it in the guarantee program handbook. Without explicitly stating the required frequency of eligibility reviews, RHS increases the risk of not complying with the OMB 2-year minimum standard and of guaranteeing loans originated or serviced by ineligible lenders. For example, RHS issued the 2013 instruction more than 2 years and 7 months after the 2011 instruction, which is not consistent with a standard of reviewing eligibility within the minimum 2-year time frame.

While RHS’s policies and procedures did not fully comply with all the Circular A-129 standards for managing lenders and servicers, the agency has been taking steps to improve its lender and servicer oversight. For example, RHS officials told us that they were taking steps to automate the eligibility recertification process, which could facilitate implementation of a more regular and streamlined review of lenders and servicers. In addition, RHS has proposed regulations that would strengthen its authority to require lenders to indemnify (compensate) RHS for loss claims on defaulted loans that were not properly underwritten. Current regulations authorize RHS to seek indemnification within 24 months of loan closing when RHS concludes that the lender did not comply with the agency’s underwriting standards. In March 2015, RHS issued a proposed rule that would increase the indemnification period to 5 years. According to RHS, the comment period has ended, and the agency plans to issue the final rule upon completing its review of the comments. However, the agency did not have a specific time frame for issuing the final rule.

In addition, in December 2015, Congress enacted legislation authorizing the Secretary of Agriculture to grant qualified lenders the authority to determine the eligibility of loans for RHS guarantees without RHS’s prior approval (similar to FHA’s and VA’s single-family mortgage guarantee programs). According to RHS, this change will improve program delivery and increase efficiency, while also requiring RHS to shift additional resources to lender and servicer monitoring. RHS officials said the change will take several years to implement.

RHS Has Not Established Risk-Related Metrics and Responsibilities Fully Consistent with All OMB Standards for Credit Program Management

As shown in table 4, RHS’s policies and procedures were consistent with two of the six standards in Circular A-129 concerning credit program management and partially consistent with the remaining four. OMB added the six standards as part of its revision of the circular in 2013. The standards address various aspects of credit program management, including lines of authority and communication, performance and risk indicators, and reporting mechanisms.

RHS policies and procedures were consistent with two standards (performance data and separation of program functions). For example, RHS produces a monthly Portfolio Performance Report that includes national summary statistics on delinquencies, foreclosures, loss mitigation actions, and loss claims as well as detailed loss claim data organized by state. Senior RHS officials, including the Undersecretary for Rural Development, the RHS Administrator, the RHS Deputy Administrator for Single Family Housing, and the Director of the guarantee program receive these reports. In addition, program operations are structured to separate key functions such as approval of loan guarantees and approval of loss claims. Furthermore, agency contracting policies and procedures incorporate requirements concerning the retention of inherently governmental functions and require progress reporting for advisory and assistance services contracts. Finally, RHS’s handbook for the guarantee program contains policies for how agency staff should communicate with lenders when RHS reviews the lender’s loan guarantee application package.

However, RHS’s policies and procedures did not fully align with the other four standards, as follows:

Defined responsibilities and codified lines of authority and communication. While RD has position descriptions for individuals involved in risk-management functions that specify duties and responsibilities, RHS does not have written procedures for a key part of its risk-management structure and documented lines of communication, as required by OMB’s Circular A-129.

Specifically, since 2009 RHS has had a Credit Policy Committee that, according to RHS officials, meets regularly to detect, discuss, and analyze credit quality issues and address them through policy changes. However, as we testified in May 2015, the committee operated without policies and procedures describing its purpose, scope, membership, or decision-making process. We also testified that RHS had not defined the roles and responsibilities of committee members and did not prepare minutes of meeting discussions and results. RHS officials said they saw no need to formalize the committee’s operations when the committee was created because the staff was small and in frequent communication. But in November 2015, the officials told us they had drafted a charter for the committee in response to our findings. Without written policies and procedures, accountability for and transparency of the credit policy committee’s activities may be limited.

Additionally, RHS has not documented the lines of communication between the agency components that have risk-management functions and responsibilities. RHS’s risk-management structure is decentralized and complex. According to RHS, it involves staff in 47 state offices; the Centralized Servicing Center and National Financial and Accounting Operations Center in St. Louis, Missouri; and USDA headquarters. RHS has basic organizational charts for these components that show lines of authority, but has not codified how and what types of information should flow among the components. Instead, they share information on a less formal basis built on established working relationships. While we found evidence that communication on financial, budget, and operational matters occurs between key staff, not documenting lines of communication increases the risk that information flows will break down in the event that these staff transfer or retire.

Independent oversight and control functions for risk management, including credit and operational risks. RHS’s management structure does not fully align with OMB standards or a congressional directive, which call for an independent risk management function. RHS officials identified various USDA components that perform oversight and control functions and operate independently of guaranteed loan program staff. For example, RD’s Office of the Chief Financial Officer oversees periodic management control reviews of the guarantee program and other programs. These reviews, which occur every 5 years, are designed to assess the effectiveness and efficiency of management controls, inform senior managers of the status of operations and internal controls, and provide solutions to reduce or eliminate any deficiencies. In addition, the Centralized Servicing Center reviews lenders’ loss claims to help ensure that lenders complied with program guidelines before the agency pays the claims. However, neither RHS nor RD has an independent function specifically tasked with identifying the range of credit and operational risks facing the guarantee program. Circular A- 129 states that agencies should strongly consider the formalization of risk-management functions through the creation of a risk- management office led by a Chief Risk Officer. Consistent with this recommendation, the House Committee on Appropriations directed RD in June 2014 to “expeditiously create and fill a position of Chief Risk Officer” whose responsibility would be to manage and mitigate the agency’s financial risk. RD officials told us that in early 2015 they had created a working group to examine how to create the position, including looking at similar efforts at other federal agencies. But as of March 2016, RD had not established the position. RD officials told us they expected to create and fill the position sometime in 2016 but did not have a more detailed timeline. As a result, RD’s efforts to manage and mitigate the risks of the guarantee program may not be as effective as they could be.

Performance indicators and risk thresholds. Although RHS uses a number of indicators to assess the performance of its guaranteed portfolio, two key indicators have limitations that diminish their usefulness and appropriateness. In addition, RHS has not established risk thresholds for the guarantee program.

Circular A-129 states that agencies should establish and periodically review appropriate performance measures for their credit programs. According to RHS officials, since 2004, they have compared the overall delinquency and foreclosure rates for RHS’s portfolio with corresponding rates for FHA’s insured portfolio of 30- year fixed-rate mortgages. RHS officials justified the performance measures based on the similarity of the FHA and RHS mortgage programs. Additionally, they noted that performance data on FHA’s portfolio was readily available from a mortgage industry group. RHS has established performance goals stating that RHS should be within a specified range of FHA’s delinquency and foreclosure rates at the end of each fiscal year. Although RHS generally has met these goals, the performance measures are not fully consistent with certain attributes of successful performance measures—such as objectivity and reliability—that we identified in previously issued work. The weaknesses in the performance measures are two-fold. First, a simple comparison of two portfolios ignores potential differences in their composition—for example, in the age and geographic distribution of loans—that may influence loan performance and make comparisons of the portfolios invalid. FHA maintains data that can be segmented by loan cohort and property location, which could help address some limitations of the industry group data. Second, it implies that FHA has been effectively managing its risk. However, FHA has at times exhibited shortcomings in this area. For example, in a 2006 report, we found that FHA had not developed sufficient standards and controls to manage risks associated with the substantial proportion of FHA- insured loans with down payment assistance. Because of these weaknesses, a performance measure that does not account for such portfolio differences may not provide a useful and appropriate benchmark for RHS risk management.

Circular A-129 also states that agencies should establish risk thresholds for their credit programs. RHS has established a risk appetite—the amount and type of risk an organization is willing to accept in pursuit of its objectives—for the single-family guarantee program. According to RHS officials, the program’s risk appetite is expressed primarily through the goal of making each annual cohort of loan guarantees subsidy-neutral, while keeping guarantee fees at a level affordable to low- and moderate-income households. However, RHS has not established associated risk thresholds—that is, target values above which risks are not tolerated or that trigger application of additional risk controls. For example, RHS has not developed thresholds for the magnitude of expected losses that are acceptable at the portfolio or loan level.

Without established risk thresholds, RHS’s ability to determine when risk levels are too high is diminished.

Reporting of performance information in watch lists and dashboards. RHS’s performance reports were not fully consistent with the OMB standard concerning portfolio dashboards. RHS produces three reports—one specifically called a dashboard and two others with some characteristics of a dashboard—that generally contain the types of quantitative information identified in the OMB guidance. However, these reports do not include a qualitative discussion of areas meriting increased management focus, as specified in Circular A-129. RHS officials said they orally discussed issues warranting greater management attention in briefings and meetings in which the reports are used. However, by not highlighting and documenting issues for management attention in the performance reports, RHS increases the possibility that senior managers will not have the information necessary to address emerging risks in a timely manner.

The inconsistencies we identified between RHS’s policies and procedures and Circular A-129 standards—both for credit program management and the areas discussed previously—occurred, in part, because RD did not compare and align its requirements with all elements of the circular. Circular A-129 requires agencies to periodically conduct program reviews that assess whether credit programs are achieving policy goals while mitigating risk and cost to the taxpayer and minimizing displacement of private credit markets. The reviews also should identify any area where a program is not consistent with the requirements of Circular A-129, evaluate the effects of any deviation, and whether the deviation is still necessary. RD officials told us that RD’s Office of the Chief Financial Officer was primarily responsible for ensuring that policies and procedures for the guarantee program were consistent with the circular. They said that the office began reviewing the compliance of all RD credit programs with the circular in 2014. RD officials said they did not expect to complete the review of the single-family loan guarantee program until 2016. RD officials added that this program review was begun on an ad hoc basis rather than part of a schedule. Furthermore, they noted that because of the large number of credit programs RD operates, they intended to complete the program reviews on a rotating basis, an approach that does not establish priorities based on risk. Federal internal control standards state that agencies should identify risks, including by using qualitative and quantitative ranking activities, and have controls such as policies and procedures to address risks. At present, RD operates 27 loan and loan guarantee programs. Without procedures for prioritizing program reviews based on risk level, RD may not be able to fully realize the intended benefits of the reviews, which include mitigating risk and cost to the taxpayer.

Conclusions

Congress and OMB have established requirements and standards for estimating the costs of and managing federal credit programs, including FCRA and OMB Circular A-129. In the wake of the recent housing crisis, RHS’s guarantee program has expanded dramatically and the estimated costs of the guarantee program have risen, due partly to higher-than- expected losses from mortgages made shortly before or during the housing downturn. Furthermore, RHS has recently been granted the authority to give qualified lenders the ability to determine the eligibility of loans for guarantees without RHS’s prior approval. These developments underscore the importance of complying with requirements and standards intended to improve the reliability of cost estimates and help ensure that risks are prudently managed. RHS has taken a number of steps to enhance its administration of the guarantee program, including development of an econometric model to estimate credit subsidy costs and potentially enhance risk analysis.

However, RHS could further strengthen its policies and procedures for managing the guarantee program by addressing inconsistencies with Circular A-129 standards related to applicant screening, lender oversight, management frameworks, and risk assessment and reporting. By doing so, the agency would help decrease the risk that ineligible borrowers would receive guaranteed loans and that unqualified or ineligible firms would originate or service the loans. RHS also would enhance its capabilities to manage its expanded portfolio and strengthen its ability to identify and mitigate risks in a timely manner. Finally, by not having procedures for risk-based scheduling of the program reviews required by OMB guidance, RD may be limiting its ability to manage its multiple credit programs in the most effective manner.

Recommendations for Executive Action

To improve compliance with OMB Circular A-129 standards and strengthen management and oversight of the guarantee program, we recommend that the Secretary of Agriculture direct the Undersecretary for Rural Development to take the following 11 actions:

To enhance screening of loan guarantee applicants, complete steps to obtain access to Treasury’s Do Not Pay portal and establish policies and procedures to deny loan guarantees to applicants who are subject to administrative offsets for delinquent child support payments.

To strengthen oversight of lenders and servicers, develop and publish in the Federal Register qualification requirements for the principal officers of lenders and servicers seeking initial or continued approval to participate in the guarantee program, develop and publish in the Federal Register capital and financial requirements for guarantee program lenders that are not regulated by a federal financial institution regulatory agency, and establish standing policies and procedures to help ensure that the agency reviews the eligibility of lenders and servicers participating in the guarantee program at least every 2 years.

To enhance and formalize the guarantee program’s risk-management finalize and adopt policies and procedures for the guarantee program’s Credit Policy Committee, document lines of communication between the different components of the risk-management structure for the guarantee program, and complete steps to create and fill a Chief Risk Officer position for RD as soon as practicable.

To strengthen risk assessment and reporting, improve performance measures comparing RHS and FHA loan performance, potentially by making comparisons on a cohort basis and limiting comparisons to loans made in similar geographic areas, develop risk thresholds for the guarantee program, potentially in the form of maximum portfolio- or loan-level loss tolerances, and identify issues for increased management focus in high-level dashboard reports.

To more effectively fulfill the requirements for conducting program reviews described in OMB Circular A-129, develop procedures for selecting RD credit programs for review based on risk and establish a prioritized schedule for conducting the reviews.

Agency Comments and Our Evaluation

We provided a draft of this report to OMB and USDA for their review and comment. OMB staff provided technical comments, which we incorporated into the report. USDA provided comments in an e-mail from the audit liaison officer in RD’s Financial Management Division.

In its comments, RD agreed with or indicated that it was taking steps to address 5 of our 11 recommendations and neither agreed or disagreed with the remaining 6. Concerning our recommendation to enhance screening of loan guarantee applicants using Treasury’s Do Not Pay portal, RD noted that it did not have the resources to manually conduct Do Not Pay searches for all loan guarantee applicants at this time because of the large volume of applicants and the technological limitations of the portal. RD also said that RHS staff had completed the Do Not Pay enrollment process and were working with Treasury to begin accessing the portal as an additional verification resource. Concerning our recommendation to create and fill a Chief Risk Officer position as soon as practicable, RD said it planned to hire someone for the position in fiscal year 2016. RD stated it agreed with our recommendations to establish standing policies and procedures governing the frequency of lender and servicer eligibility reviews, finalize and adopt policies and procedures for the Credit Policy Committee, and document lines of communication among components of the risk-management structure.

For four of the six recommendations with which RD neither agreed nor disagreed, RD said it recognized the underlying risk implications and was continuing to consider the recommendations. The recommendations concern the development of qualification requirements for principal officers of guarantee program lenders and servicers, capital and financial requirements for nonsupervised guarantee program lenders, risk thresholds for the guarantee program, and improved measures for comparing RHS and FHA loan performance. For the first three of these recommendations, RD stated that “existing requirements may currently address concern,” but it did not cite the requirements to which it was referring or otherwise elaborate. We maintain that existing requirements do not address the concerns underlying our recommendations. As our report notes, RHS effectively relies on requirements of other mortgage institutions (such as FHA and VA) for lender and servicer approval, and these requirements may not be well-suited to RHS’s program. For example, FHA’s net worth requirement for nonsupervised lenders is calibrated to the amount of FHA business the lender does, and the suitability of VA’s net worth requirement for RHS is limited by the substantially lower loss coverage of VA’s program compared with RHS’s. Furthermore, while it is possible that detailed analysis of FHA and VA requirements would find them sufficient for RHS’s program, RHS did not provide any evidence that it had conducted such an analysis. Regarding risk thresholds, while our report notes that statutory limits exist on RHS’s annual business volume and the percentage of each mortgage it can guarantee, these limits define RHS’s maximum possible financial exposure rather than loss tolerances established by agency management. OMB Circular A-129 requirements, including the requirement for establishing risk thresholds, outline steps agency officials should take to manage the risks of their credit programs.

For the remaining two recommendations—which concern identifying areas for increased management focus in dashboard reports and prioritizing Circular A-129 program reviews based on risk—RD elaborated on current agency practices but did not indicate whether or how it planned to address the recommendations. RD stated that its dashboard reports provided differing levels of detail, but also acknowledged that they contained no specific issues for increased focus despite the existence of program challenges identified by agency staff. Including a qualitative discussion of areas meriting greater attention in dashboard reports would help ensure that agency managers address emerging risks in a timely manner. Finally, RD described its process for prioritizing programs for Management Control Reviews. As we described in our report, these periodic reviews are a USDA requirement designed to determine whether necessary controls are in place and producing intended results, comply with applicable laws and regulations, and provide solutions to reduce or eliminate any deficiencies. While we acknowledge RHS’s risk-based process for prioritizing programs for Management Control Reviews, our recommendation addressed program reviews required by OMB Circular A-129. Although the two types of reviews may be complementary, the A- 129 program reviews are broader in scope than Management Control Reviews. For example, A-129 program reviews should assess whether programs are achieving policy goals while mitigating risk and cost to the taxpayer and minimizing displacement of private credit markets. In addition, they should identify any area in which a program is not consistent with the requirements of Circular A-129, and evaluate the effects of any deviation and if the deviation is still necessary. USDA and RD instructions for Management Control Reviews do not include these requirements and do not reference A-129. Using a risk-based approach for selecting programs for A-129 program reviews, rather than the rotational process RD previously described and that we discussed in our report, would help RD manage its multiple credit programs in the most effective manner. We added language to the body of our report and to our recommendation to clarify that our focus was on risk-based selection of programs for program reviews conducted in accordance with A-129 requirements.

In addition, in its comments, RD concurred with our characterization of trends in the estimated long-term costs of the guarantee program and RD’s efforts to develop an econometric model to improve the quality of cost estimates. RD also said that, based on its preliminary analysis, the econometric models will correct for the overestimation of future losses that resulted from using the historical method in recent years. As a result, RD said that it expects its 2016 credit subsidy reestimate will be a downward reestimate. RD also provided clarification on the role of RD’s Office of the Chief Financial Officer in reviewing RHS actions to address Office of the Inspector General audit recommendations. We incorporated the information about the potential impact of the econometric models and the role of RD’s Office of the Chief Financial Officer into the final report.

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If you or your staff have any questions about this report, please contact me at (202) 512-8678 or sciremj@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of this report. GAO staff who made key contributions to this report are listed in appendix II.

Appendix I: Objectives, Scope, and Methodology

Our objectives were to examine: (1) recent trends in the credit subsidy costs of the Rural Housing Service’s (RHS) single-family guarantee program (guarantee program) and the process for estimating those costs and (2) the extent to which RHS’s policies and procedures for the guarantee program are consistent with Office of Management and Budget (OMB) standards for managing credit programs.

Credit Subsidy Costs and Estimation Process

To examine recent trends in credit subsidy costs for the guarantee program and the process for estimating these costs, we analyzed credit subsidy cost estimates and reestimates from the President’s budgets for fiscal years 2006 through 2016 (which include the final reestimates for fiscal years 2004 through 2014). We reviewed related requirements and guidance, including the Federal Credit Reform Act of 1990; the Office of Management and Budget (OMB) Circular No. A-11 (Preparation, Submission, and Execution of the Budget); the Federal Accounting Standards Advisory Board’s Federal Financial Accounting and Auditing Technical Release 6 (Preparing Estimates for Direct Loan and Loan Guarantee Subsidies under the Federal Credit Reform Act); and the Government-wide Audited Financial Statement Task Force Subcommittee on Credit Reform Issue Paper 96-CR-7 (Model Credit Program Methods and Documentation for Estimating Subsidy Rates and the Model Information Store). We examined documentation on the processes and tools Rural Development (RD) uses to determine subsidy costs for the guarantee program, including RD’s cash flow model and technical and other guidance associated with the model. We also reviewed documentation of analyses RD’s independent financial statement auditor conducted on the model as part of RD’s fiscal years 2012 through 2014 financial statement audits and associated findings and recommendations. In addition, we reviewed analyses conducted by an independent contractor in 2013 on the model’s ability to predict cash flows and associated recommendations. To obtain information about manual adjustments made to the model for credit subsidy cost reestimates in recent years, we interviewed officials from RD’s Office of the Chief Financial Officer, including staff from the National Financial and Accounting Operations Center. In addition, we reviewed the contract RD awarded for the development of an econometric model for estimating credit subsidy costs for future budgets and interviewed RHS and RD officials and contractor staff on their plans for and progress on developing the model.

To provide context for recent trends in the program’s credit subsidy costs, we analyzed RD data on the number of loans guaranteed annually from fiscal year 1992 (the first year RHS made guarantees nationwide) through fiscal year 2014 and the total dollar amount of outstanding guarantees each year in fiscal years 2004 through 2014. We also analyzed RD data on loss amounts for the fiscal year 2000 through fiscal year 2013 cohorts as of September 30, 2014. Specifically, we calculated cumulative loss rates by cohort and year from origination. The cumulative loss rates represent the total losses at a given point in time divided by the original dollar volume of loans guaranteed. To assess the reliability of these data, we reviewed related documentation, including information about their source systems and how the data were compiled. We also interviewed RD officials knowledgeable about the data and compared them with other data sources, where possible. We concluded that the data elements we used were sufficiently reliable for the purposes of describing trends in the guarantee program’s business activity, portfolio size, and loss experience. Additionally, we obtained extracts of RHS loan-level data, including loan and borrower characteristics and performance information, for guarantees made in fiscal years 2010 through 2014 to confirm that RHS maintained the types of data suitable for credit subsidy cost modeling.

Consistency with OMB Standards for Managing Credit Programs

To determine the extent to which RHS’s policies and procedures were consistent with OMB standards, we reviewed OMB Circular A-129 (Policies for Federal Credit Programs and Non-Tax Receivables). We focused on part III of the guidance, which contains a number of standards pertinent to risk management for a loan guarantee program, including standards for credit extension (applicant screening, loan documentation, and collateral requirements), credit program management (management and oversight and data-driven decision making), and management of guaranteed loan lenders and servicers (lender and servicer eligibility, agreements, reviews, and corrective actions). We reviewed RHS’s policies and procedures for these functions contained in regulations, handbooks, and other guidance and documentation. These included U.S. Department of Agriculture (USDA) and RD policies, Federal Register notices, regulations, and RD and RHS organizational charts and position descriptions. They also included the guarantee program’s technical handbook, lender and servicer compliance review guides, loss mitigation and loss claim guides, Guaranteed Underwriting System guidance, administrative notices, unnumbered letters (a type of internal guidance), annual reports, and portfolio performance reports. We assessed the extent to which they were consistent with the OMB A-129 standards. For several of the OMB standards, we identified related, sound risk management practices cited in documents from other organizations. These included previously issued GAO reports on risk management frameworks, federal internal control standards, and attributes of successful performance measures and publications from the Committee on the Sponsoring Organizations of the Treadway Commission and the International Association of Credit Portfolio Managers.

To supplement our understanding of the OMB guidance and RHS’s policies and procedures, we interviewed OMB staff knowledgeable of the 2013 update of Circular A-129 and various USDA officials. The USDA officials included the RHS Administrator, Deputy Administrator, and Director of the Single Family Housing Guarantee Loan Division, as well as staff from that division, RHS’s Centralized Servicing Center, and RD’s Office of the Chief Financial Officer (which includes the National Finance and Accounting Operations Center). These interviews typically included representatives from an RHS contractor with responsibilities for producing risk analytics and conducting compliance reviews of national lenders and servicers.

To determine what prior audits and evaluations of the guarantee program had found, we met with USDA’s Office of Inspector General and reviewed pertinent Inspector General audit reports. We also reviewed RD’s 2008 and 2013 management control reviews for the guarantee program. For both the Inspector General reports and the management control reviews, we determined the status of recommendations made to address deficiencies in program management and implementation. We also reviewed nationwide summaries of RD state internal reviews, which include the guarantee program in their scope, for fiscal years 2012 through 2014. We did not verify RHS’s compliance with its own policies and procedures or assess their effectiveness. However, the prior audits and evaluations we reviewed included compliance testing and reviews of information documenting RHS actions to address any recommendations.

We conducted this performance audit from May 2014 to March 2016 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.

Appendix II: GAO Contact and Staff Acknowledgments

GAO Contact

Staff Acknowledgments

In addition to the contact named above, Steve Westley (Assistant Director); Alexandra Martin-Arseneau (Analyst-in-Charge); Abiud Amaro Diaz; Stephen Brown; Marcia Carlsen; William R. Chatlos; Melissa Kornblau; John McGrail; Barbara Roesmann; Jena Sinkfield; and Heneng Yu made key contributions to this report.