Reconsider travel to Qatar due to COVID-19.
Read the Department of State’s COVID-19 page before you plan any international travel.
The Centers for Disease Control and Prevention (CDC) has issued a Level 3 Travel Health Notice for Qatar due to COVID-19.
Qatar has lifted stay at home orders, and resumed some transportation options and business operations. Visit the Embassy’s COVID-19 page for more information on COVID-19 in Qatar.
Read the country information page.
Due to risks to civil aviation operating within the Persian Gulf and the Gulf of Oman region, including Qatar, the Federal Aviation Administration (FAA) has issued an advisory Notice to Airmen (NOTAM) and/or a Special Federal Aviation Regulation (SFAR). For more information U.S. citizens should consult the Federal Aviation Administration’s Prohibitions, Restrictions and Notices.
If you decide to travel to Qatar:
Last Update: Reissued with updates to COVID-19 information.
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- Mortgage Lending: Use of Alternative Data Is Limited but Has Potential BenefitsBy Sam NewsDecember 16, 2021What GAO Found To help determine a borrower's creditworthiness, mortgage lenders can use “alternative data”—consumer information not contained in a traditional credit report, such as a borrower's rent payments. But available data indicate that few mortgage loans have been underwritten with alternative data. In fiscal years 2016–2020, less than 0.1 percent of mortgages purchased by Fannie Mae and Freddie Mac (government-sponsored enterprises that purchase about half of all originated mortgages) were made to borrowers without credit scores, an indication they were underwritten using alternative data. Similarly, very few loans the Federal Housing Administration, Department of Agriculture, and Department of Veterans Affairs insured or guaranteed went to such borrowers (see table). Mortgage Loans Made to Borrowers without Credit Scores, Fiscal Years 2016–2020 Institution Total loans Loans without borrower credit scores Percent of loans without borrower credit scores Fannie Mae 5,447,753 5,023 0.09 Freddie Mac 4,813,075 2,212 0.05 Federal Housing Administration 4,109,309 12,777 0.31 Department of Agriculture 599,864 14,174 2.36 Department of Veterans Affairs 2,833,813 2,739 0.10 Source: GAO analysis of Fannie Mae, Freddie Mac, and federal agency data. | GAO-22-104380 Note: Data for Fannie Mae and Freddie Mac represent loans purchased, and for the federal agencies, loans guaranteed or insured. According to agency officials, loans made to borrowers without credit scores very likely used alternative data for underwriting. Using alternative data in mortgage lending presents benefits and risks. Underwriting with alternative data can increase mortgage access for individuals who have little credit history with the national consumer reporting agencies, including many minority and lower-income consumers, according to literature GAO reviewed and stakeholders GAO interviewed. But the extent to which the use of alternative data could increase access depends on several factors, including whether the data increase credit scores enough to qualify consumers for mortgage loans. Alternative data usage could lead to better pricing for consumers if it improved lenders' ability to predict default risks, but also could present fair lending risks. For example, if alternative data are correlated with characteristics protected under fair lending laws (such as race or gender), borrowers in protected classes may be adversely affected by underwriting models using such data. Use of alternative data also can present privacy concerns if consumers lack knowledge and control of how these data are used. Public and private entities have taken steps to encourage use of alternative data in mortgage lending. For example, in September 2021, Fannie Mae updated its automated underwriting system to allow rental payments (a form of alternative data) to be included. In December 2020, the Consumer Financial Protection Bureau issued rules that may facilitate use of alternative data. For example, one rule changed the general qualified mortgage definition to give lenders additional flexibility—which could include analyzing alternative data such as cash flows—when assessing a consumer's ability to repay. Lenders are protected from certain types of liability for loans meeting the definition. Why GAO Did This Study Roughly 45 million consumers lack a credit score from one of three major consumer reporting agencies, according to the Consumer Financial Protection Bureau, which limits their ability to qualify for a mortgage loan. To address this, an increasing number of lenders have been exploring use of alternative data—information not used in traditional credit scoring—to determine eligibility for mortgage loans. However, some policymakers and regulators have raised questions about potential risks of using such data in mortgage underwriting. GAO was asked to review the use of alternative data in mortgage lending. This report describes (1) the extent to which mortgage loans were originated using alternative data in fiscal years 2016–2020, (2) potential benefits and risks associated with using alternative data in such lending, and (3) efforts to encourage lenders' use of alternative data. GAO analyzed data provided by government-sponsored enterprises and federal agencies for fiscal years 2016–2020; reviewed studies by agencies and other researchers; and interviewed federal financial regulators, agencies with mortgage lending programs, lenders, government-sponsored enterprises, and other industry participants. For more information, contact Michael E. Clements at (202) 512-8678 or ClementsM@gao.gov.[Read More…]
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- Military Training: Observations on the Army’s Implementation of a Metric for Measuring Ground Force TrainingBy Sam NewsAugust 31, 2021What GAO FoundThe full spectrum training mile metric is similar in some ways to the tank mile metric and dissimilar in other ways. Both metrics measure training activity of nondeployed units associated with recommended training events based on the Army's approved training strategy. Specifically, they both calculate the average number of miles a unit is expected to drive its vehicles on an annual basis for training that occurs during the reset and train/ready stages of the Armys Force Generation (ARFORGEN) cycle.However, the full spectrum training mile metric applies to all Army components (active component, Army Reserve, and Army National Guard) while the tank mile metric does not apply to the Army Reserve, because the Army Reserve does not have tanks. The full spectrum training mile metric also is based on multiple vehicles including the M1 Abrams tank, M2/M3 Bradley, Stryker, up-armored high mobility multipurpose wheeled vehicle, medium tactical vehicle, and palletized load system, while the tank mile metric is limited to the M1 Abrams tank. According to Army officials, the full spectrum training mile metricand its incorporation of a wider array of vehiclesis more reflective of the type of vehicles the Army is actually using to train its ground forces for full spectrum operations.The Armys full spectrum training mile metric is based on certain assumptions associated with standards set in the Armys training strategy and force-generation model. Because the metric is a standard for actual training to be measured against, the metrics assumptions are based on desired or expected conditions and may not fully align with actual conditions. For example, the Army made certain assumptions about the length of time units would spend in each stage of the ARFORGEN cycle, assumed that units would have all the vehicles that were included in their modified table of organization and equipment, and assumed units would accomplish all the training in the Armys training strategy. However, prior GAO reports and Army readiness reports have both shown that units do not always have all the equipment, including vehicles included in their modified table of organization and equipment, available when they are conducting training. Army officials have also acknowledged that many units are not currently executing the ARFORGEN training cycle and the Armys training strategy as envisioned. To the extent that units do not have all of their equipment, including vehicles, or complete all recommended training, the units actual miles driven may differ from the Armys full spectrum training mile metric. According to a responsible Army official, the Army tracks historical data on actual miles driven and has, in the past, adjusted assumptions used to develop its tank mile metric to more closely reflect actual conditions. The Army plans to continue this practice now with the new metric in place. For example, when conducting its 2010 training strategy review, the Army reduced its estimated miles per training day and event to more closely reflect actual miles driven.The Army uses the full spectrum training mile metric to measure training activity. Specifically, the Army compares the actual miles its units have driven to conduct ground force training to its full spectrum training mile metric to determine how well it executed its training strategy. However, the Army does not use the full spectrum training mile metric to develop its training cost estimates or related funding needs. The Army uses its Training Resource Model, rather than its full spectrum training mile metric, to develop its training cost estimates and funding needs. While some of the inputs to the full spectrum training mile metric and the Training Resource Model are the same (i.e., the number and duration of training events and the numbers of units and vehicles available for training) the Training Resource Model contains unique inputs, such as cost factors that are not related to the full spectrum training mile metric. Specifically, the cost calculation in the Training Resource Model includes the cost to drive a vehicle, expressed as cost per mile, that are linked to the number of units and vehicles, as well as other indirect nonmileage support costs, such as civilian pay. The Training Resource Model, like the full spectrum training mile metric, assumes, among other things, that all recommended training events will be fully executed. To the extent that all training does not occur or other assumptions do not hold true, requirements could differ from estimates derived from the Training Resource Model. According to an Army official, the Training Resource Model is one of several sources of information the Army considers when developing its funding requests for training. For example, the official stated the Army uses historical data on actual miles driven to adjust its funding requests to more closely reflect actual conditions.Why GAO Did This StudyIn 2008, the Army issued a field manual that identified the need to expand its training focus so units would be trained and ready to operate across a full spectrum of operations including offensive, defensive, stability, and civil support operations. To support operations in Iraq and Afghanistan, for the last several years, the Army has focused its ground force training on preparing units for counterinsurgency operations. With the withdrawal from operations in Iraq, fewer units are engaged in counterinsurgency operations and now have more time to train for full spectrum operations.To reflect the shift in training focus, the Army, in April 2011, updated its training strategy and also established a new metric to measure training activityreferred to as the full spectrum training mile metric. This metric replaced the Armys traditional tank mile metric, which represented the average number of miles the Army expected to drive its tanks while conducting training. In its fiscal year 2012 budget materials, the Army provided background information on its transition to the new metric, and, starting in fiscal year 2012, began using the new metric.House report 112-78 directed GAO to review the Armys transition to the full spectrum training mile metric and report its findings by February 28, 2012. To address this mandate, we determined (1) how the Army's full spectrum training mile metric differs from its traditional tank mile metric; (2) the key assumptions associated with the full spectrum training mile metric and to what extent these assumptions reflect actual conditions; and (3) to what extent the Army uses the full spectrum training mile metric to measure training execution and develop training cost estimates and related funding needs. Additionally, for background purposes, this report includes information on how training is reflected in the Armys operation and maintenance budget-justification materials.For more information, contact Sharon L. Pickup at 202-512-9619 or firstname.lastname@example.org.[Read More…]
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- Real Estate Appraisals: Most Residential Mortgages Received Appraisals, but Waiver Procedures Need to Be Better DefinedBy Sam NewsDecember 27, 2021What GAO Found Although Title XI permits federal regulators to exempt certain mortgages from an appraisal requirement, such exemptions likely have not increased overall risks for regulated lenders (e.g., banks and credit unions) and homebuyers. This is because GAO estimates the lenders obtained appraisals for around 85 percent of the mortgages eligible for an exemption in 2018–2019 (see figure). An appraisal of a home's market value can help lenders mitigate the risk of loss and homebuyers mitigate the risk of overpaying. Regulated lenders obtained appraisals even when not required by Title XI for various reasons. For example, Fannie Mae and Freddie Mac generally require appraisals for mortgages they purchase from lenders, so lenders obtained appraisals in order to sell mortgages to them. In addition, regulated lenders typically obtained appraisals for mortgages of $250,000 or less, although they were permitted to use an evaluation (an estimate of a home's market value not conducted by a state-approved appraiser) in place of an appraisal. Most Residential Mortgages Originated in 2018–2019 That Qualified for a Title XI Appraisal Exemption Still Had an Appraisal The Appraisal Subcommittee (ASC) followed its process in granting a waiver to North Dakota in 2019 but faced challenges in making the determination. ASC may temporarily waive the requirement that only state-approved appraisers perform Title XI appraisals if it determines a scarcity of appraisers led to a significant delay in obtaining appraisals. However, ASC's regulations and guidance for processing temporary waiver requests do not define scarcity and significant delay or establish standards to determine when these conditions exist. For North Dakota's request, the absence of such standards led different stakeholders to use different definitions and data to prove or disprove the conditions existed—creating challenges for ASC in making its determination. Defining the key terms in measurable ways and establishing standards to determine if such conditions exist would better ensure that ASC has a consistent and objective process for reviewing and granting future waiver requests. Why GAO Did This Study Congress enacted Title XI in the Financial Institutions Reform, Recovery, and Enforcement Act of 1989 to require regulated lenders to obtain appraisals for residential mortgages from state-approved appraisers, unless eligible for one of its exemptions. Title XI also created ASC to monitor Title XI-related activities and authorized it to grant waivers related to appraiser credentialing requirements. In late 2019 and early 2020, federal regulators raised the threshold under which lenders can (but do not have to) obtain an evaluation instead of an appraisal for mortgages to $400,000 or less. Also, in 2018, North Dakota requested a temporary waiver, citing delays in appraisals because of a scarcity of appraisers. GAO was asked to review Title XI exemptions. This report examines the extent to which (1) Title XI appraisal exemptions increased risks for federally regulated lenders and homebuyers, and (2) ASC followed its waiver review process or faced challenges when it granted North Dakota a temporary waiver. GAO reviewed and analyzed Title XI and related regulations, most recently available mortgage data, research on appraisals, and ASC records, and interviewed federal agencies and industry stakeholders.[Read More…]
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