Rural Housing Service: Actions Needed to Strengthen Management of the Single Family Mortgage Guarantee Program
Published: 2016-03-31T00:00:00

Fast Facts:

Highlights:
section_title: Why GAO Did This Study
paragraphs: In recent years, RHS's single-family mortgage guarantee program has grown significantly, and RHS currently manages a guaranteed portfolio of more than $100 billion. RHS helps low- and moderate-income rural residents purchase homes by guaranteeing mortgages made by private lenders.
GAO was asked to examine the program's cost estimation methodology and risk-management structure. This report discusses (1) recent trends in the credit subsidy costs of RHS's guarantee program and the process for estimating those costs and (2) the extent to which RHS's policies and procedures for the program are consistent with federal standards for managing credit programs. GAO analyzed RHS budget data for fiscal years 2004 through 2014, examined RHS policies and procedures, reviewed OMB standards, and interviewed RHS officials.
section_title: What GAO Found
paragraphs: The estimated credit subsidy costs (expected net lifetime costs) of single-family mortgages guaranteed by the Department of Agriculture's (USDA) Rural Housing Service (RHS) substantially increased in recent years, partly due to high losses from the 2007 through 2011 housing crisis. For example, the fiscal year 2013 and 2014 reestimates (which federal agencies must do annually) indicated higher expected costs of $804 million and $615 million, respectively, compared with the prior reestimates (see fig.). To improve the current estimation method (which relies on average historical losses), RHS hired a contractor to develop statistical models that will predict losses based on loan, borrower, and economic variables.
RHS's policies and procedures are not fully consistent with all Office of Management and Budget (OMB) standards for managing credit programs (OMB Circular A-129). RHS's policies and procedures are consistent with the OMB standards in most areas, including loan documentation, collateral requirements, and aspects of applicant screening and lender oversight. However, RHS
has not established and published all required lender eligibility standards such as principal officer qualifications (e.g., experience level) and financial standards (e.g., minimum net worth);
lacks written policies and procedures for a committee responsible for analyzing and addressing the credit quality (default risk) of guaranteed loans;
has not established a position independent of program management to help manage the risks of its guaranteed portfolio;
has not established risk thresholds (for example, maximum portfolio- or loan-level loss tolerances) and uses certain loan performance benchmarks that have limited value for risk management; and
has not incorporated a discussion of areas needing increased management focus into its “dashboard” reports.
These and other inconsistencies occurred in part because RHS has not completed an ongoing assessment of its policies and procedures against Circular A-129. Furthermore, the Office of Rural Development (which oversees RHS) has not established procedures for prioritizing Circular A-129 reviews of its credit programs based on risk. More fully adhering to Circular A-129 standards would enhance RHS's effectiveness in managing the risks of its guarantee program.
section_title: What GAO Recommends
paragraphs: GAO is making 11 recommendations to USDA to help ensure that RHS's policies and procedures are consistent with OMB standards and to strengthen management of the guarantee program and other credit programs. Areas on which the recommendations focus include overseeing lenders, formalizing or establishing key risk management functions, and assessing and reporting on portfolio risk and performance. RHS agreed with or said it was acting on five of the recommendations. RHS neither agreed nor disagreed with the rest but said it generally recognized the underlying risk implications. GAO maintains that the recommendations are valid, as discussed in the report.

section_title: Letter
paragraphs: The Department of Agriculture’s (USDA) Rural Housing Service (RHS)  has helped more than 1 million families residing in rural communities  finance homes through its Single Family Mortgage Guarantee Program  (guarantee program). The program insures private lenders against  losses on loans that finance the purchase of properties in areas statutorily  designated as rural or that refinance existing RHS mortgages. RHS has  experienced a substantial increase in its business volume due, in part, to  contraction of other mortgage market segments stemming from the 2007  through 2011 housing crisis. From 2007 through 2014, the amount of  outstanding RHS guarantees grew from less than $20 billion to more than  $100 billion. At the same time, the estimated long-term costs of the  guarantee program—known as credit subsidy costs—have risen. Similar  to other federal credit agencies, USDA is required to estimate and  annually reestimate the budgetary costs of each guaranteed loan cohort  in accordance with the Federal Credit Reform Act of 1990 (FCRA). For  the past several fiscal years, USDA has submitted upward credit subsidy  reestimates for the guarantee program, reflecting an increase in the  program’s expected cost.
In light of these developments, you requested that we assess the cost  estimation methodology and risk-management structure for RHS’s  guarantee program. This report discusses (1) recent trends in the credit  subsidy costs of RHS’s guarantee program and the process for estimating  and reestimating 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.
To examine recent trends in the guarantee program’s credit subsidy costs  and the process for estimating those costs, we analyzed credit subsidy  estimates and reestimates from the President’s budgets for fiscal years  2006–2016 (which include the final reestimates for fiscal years 2004  through 2014). We reviewed relevant requirements and guidance,  including FCRA, OMB Circular A-11, and federal financial accounting  guidance. We examined documentation on the processes and tools RHS  uses to determine subsidy costs, including the cash flow model  maintained by Rural Development (RD), the USDA component that  oversees RHS. We also interviewed RD and RHS officials and RD  contractor staff about current credit subsidy estimation processes and  planned changes. 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 from fiscal years 2004  through fiscal year 2014. We also analyzed RD data on loss amounts for  the fiscal year 2000 through 2013 cohorts as of September 30, 2014. We  assessed the reliability of these data by reviewing related documentation,  interviewing knowledgeable agency officials, and comparing the data with  other data sources, where possible. We found the data to be sufficiently  reliable for the purposes of describing trends in the guarantee program’s  business activity, portfolio size, and loss experience.
To determine the extent to which RHS’s policies and procedures were  consistent with OMB standards, we reviewed OMB Circular A-129, which  contains a number of standards pertinent to managing the risks of a loan  guarantee program, including standards for extending credit, managing  and overseeing credit programs, and managing guaranteed loan lenders  and servicers. We reviewed RHS’s policies and procedures for the  guarantee program—contained in regulations, handbooks, and other  agency guidance and documentation—and assessed the extent to which  they were consistent with the OMB standards. We did not verify RHS’s  compliance with its own policies and procedures or assess their  effectiveness. However, we reviewed related USDA Office of the  Inspector General reports, which included some compliance testing, and  determined the status of the Inspector General’s audit recommendations.  Additionally, we interviewed RD and RHS officials with responsibilities for  managing the guarantee program and OMB staff knowledgeable of the  2013 update of Circular A-129.
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. Appendix I contains additional information on our objectives,  scope, and methodology.
subsections: section_title: Background
subsections: section_title: RHS Guarantee Program
paragraphs: 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.
subsections: section_title: Lenders and Servicers
paragraphs: 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.
section_title: National, State, and Local Offices
paragraphs: 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.
section_title: Requirements for Estimating Credit Subsidy Costs
paragraphs: 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.
section_title: OMB Circular A-129
paragraphs: 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.
section_title: Estimated Costs of Guarantee Program Have Risen, and Rural Development Has Enhanced Its Cost Estimation Process
paragraphs: 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.
subsections: section_title: Losses from the Housing Crisis Contributed to an Increase in Credit Subsidy Reestimates
paragraphs: 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.
section_title: Rural Development Has Been Developing Econometric Models to Address Limitations of Its Cost Estimation Method
subsections: section_title: Current Process for Estimating Credit Subsidy Costs Is Based on Historical Averages
paragraphs: 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.
section_title: RD Adjusted Its Reestimation Method to Account for Effects of the Housing Crisis on Loan Performance
paragraphs: 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.
section_title: RD Has Been Developing Econometric Models to Address Limitations in Its Estimation Method
paragraphs: 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.
section_title: RHS Has Not Fully Aligned Its Policies and Procedures with OMB Guidance
paragraphs: 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.
subsections: section_title: RHS Policies Were Generally Consistent with OMB Standards for Extending Credit, but Did Not Fully Meet One Standard for Screening Applicants
paragraphs: RHS’s policies and procedures were consistent with Circular A-129  standards for extending credit, with the exception of one standard  concerning applicant screening.
subsections: section_title: Applicant Screening
paragraphs: 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.
section_title: Loan Documentation and Collateral
paragraphs: 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.
section_title: RHS’s Program Eligibility Policies Did Not Fully Align with Certain OMB Standards for Managing Lenders and Servicers
paragraphs: 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.
section_title: RHS Has Not Established Risk-Related Metrics and Responsibilities Fully Consistent with All OMB Standards for Credit Program Management
paragraphs: 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.
section_title: Conclusions
paragraphs: 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.
section_title: Recommendations for Executive Action
paragraphs: 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.
section_title: Agency Comments and Our Evaluation
paragraphs: 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.
As agreed with your offices, unless you publicly announce the contents of  this report earlier, we plan no further distribution until 30 days from the  report date. At that time, we will send copies to the appropriate  congressional committees, the Secretary of Agriculture, the Director of  the Office of Management and Budget, and other interested parties. In  addition, the 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 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.
section_title: Appendix I: Objectives, Scope, and Methodology
paragraphs: 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.
subsections: section_title: Credit Subsidy Costs and Estimation Process
paragraphs: 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.
section_title: Consistency with OMB Standards for Managing Credit Programs
paragraphs: 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.
section_title: Appendix II: GAO Contact and Staff Acknowledgments
subsections: section_title: GAO Contact
section_title: Staff Acknowledgments
paragraphs: 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.