September 27, 2022

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Mortgage Lending: Use of Alternative Data Is Limited but Has Potential Benefits

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<div>What 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.</div>

What 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.

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