The Federal National Mortgage Association, commonly known as Fannie Mae, was created by the U.S. congress in 1938, in order to maintain liquidity and stability in the domestic mortgage market. The company is a government-sponsored enterprise (GSE), meaning that while it was a publicly traded company for most of its history, it was still supported by the federal government. While there is no legally binding guarantee of shares in GSEs or their securities, it is generally acknowledged that the U.S. government is highly unlikely to let these enterprises fail. Due to these implicit guarantees, GSEs are able to access financing at a reduced cost of interest. Fannie Mae's main activity is the purchasing of mortgage loans from their originators (banks, mortgage brokers etc.) and packaging them into mortgage-backed securities (MBS) in order to ease the access of U.S. homebuyers to housing credit. The early 2000s U.S. mortgage finance boom During the early 2000s, Fannie Mae was swept up in the U.S. housing boom which eventually led to the financial crisis of 2007-2008. The association's stated goal of increasing access of lower income families to housing finance coalesced with the interests of private mortgage lenders and Wall Street investment banks, who had become heavily reliant on the housing market to drive profits. Private lenders had begun to offer riskier mortgage loans in the early 2000s due to low interest rates in the wake of the "Dot Com" crash and their need to maintain profits through increasing the volume of loans on their books. The securitized products created by these private lenders did not maintain the standards which had traditionally been upheld by GSEs. Due to their market share being eaten into by private firms, however, the GSEs involved in the mortgage markets began to also lower their standards, resulting in a 'race to the bottom'. The fall of Fannie Mae The lowering of lending standards was a key factor in creating the housing bubble, as mortgages were now being offered to borrowers with little or no ability to repay the loans. Combined with fraudulent practices from credit ratings agencies, who rated the junk securities created from these mortgage loans as being of the highest standard, this led directly to the financial panic that erupted on Wall Street beginning in 2007. As the U.S. economy slowed down in 2006, mortgage delinquency rates began to spike. Fannie Mae's losses in the mortgage security market in 2006 and 2007, along with the losses of the related GSE 'Freddie Mac', had caused its share value to plummet, stoking fears that it may collapse. On September 7th 2008, Fannie Mae was taken into government conservatorship along with Freddie Mac, with their stocks being delisted from stock exchanges in 2010. This act was seen as an unprecedented direct intervention into the economy by the U.S. government, and a symbol of how far the U.S. housing market had fallen.

Graph and download economic data for 15-Year Fixed Rate Mortgage Average in the United States (MORTGAGE15US) from 1991-08-30 to 2025-11-26 about 15-year, mortgage, fixed, interest rate, interest, rate, and USA.

View weekly updates and historical trends for 30 Year Mortgage Rate. from United States. Source: Freddie Mac. Track economic data with YCharts analytics.

Graph and download economic data for Government-Sponsored Enterprises; Securitized Multifamily Residential Mortgages Held by Fannie Mae; Asset, Transactions (BOGZ1FA403065463Q) from Q4 1946 to Q2 2025 about fannie mae, GSE, multifamily, securitized, transactions, mortgage, family, residential, assets, and USA.

United States Fannie Mae: Year to Date: Risk Management Derivatives: Net Contractual Interest Expense on Interest-Rate Swaps data was reported at -218.000 USD mn in Mar 2025. This records an increase from the previous number of -964.000 USD mn for Dec 2024. United States Fannie Mae: Year to Date: Risk Management Derivatives: Net Contractual Interest Expense on Interest-Rate Swaps data is updated quarterly, averaging -450.000 USD mn from Dec 2011 (Median) to Mar 2025, with 51 observations. The data reached an all-time high of 16.000 USD mn in Dec 2021 and a record low of -2.187 USD bn in Dec 2011. United States Fannie Mae: Year to Date: Risk Management Derivatives: Net Contractual Interest Expense on Interest-Rate Swaps data remains active status in CEIC and is reported by Federal National Mortgage Association. The data is categorized under Global Database’s United States – Table US.EB121: Derivatives Fair Value Gains or Losses: Federal National Mortgage Association, Fannie Mae.

Graph and download economic data for Agency-and GSE-Backed Mortgage Pools; Total Mortgages Held in a Fannie Mae Pool; Asset, Transactions (BOGZ1FA413065045A) from 1946 to 2024 about GSE-Backed, fannie mae, mortgage, transactions, assets, and USA.

Fannie Mae and Freddie Mac Loan-Level Dataset

Borrower Demographics, Loan-to-Value Ratios, and Census Tract Location

By Natarajan Krishnaswami [source]

About this dataset

The FHFA Public Use Databases provide an unprecedented look into the flow of mortgage credit and capital in America's communities. With detailed information about the income, race, gender and census tract location of borrowers, this database can help lenders, planners, researchers and housing advocates better understand how mortgages are acquired by Fannie Mae and Freddie Mac.

This data set includes 2009-2016 single-family property loan information from the Enterprises in combination with corresponding census tract information from the 2010 decennial census. It allows for greater granularity in examining mortgage acquisition patterns within each MSA or county by combining borrower/property characteristics, such as borrower's race/ethnicity; co-borrower demographics; occupancy type; Federal guarantee program (conventional/other versus FHA-insured); age of borrowers; loan purpose (purchase, refinance or home improvement); lien status; rate spread between annual percentage rate (APR) and average prime offer rate (APOR); HOEPA status; area median family income and more.

In addition to demographic data on borrowers and properties, this dataset also provides insight into affordability metrics such as median family incomes at both the MSA/county level as well as functional owner occupied bankrupt tracts using 2010 Census based geography while taking into account American Community Survey estimates available at January 1st 2016. This allows us to calculate metrics that are important for assessing inequality such as tract income ratios which measure what portion of an area’s median family income is made up by a single borrows earnings or the ratio between borrows annual income compared to an area’s average median family iincome for those year’s reporting period. Finally each record contains Enterprise Flags associated with whether loans were purchased my Fannie Mae or Freddie Mac indicating further insights regarding who is financing policies affecting undocumented immigrant labor access as well affordable housing legislation targeted towards first time home buyers

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How to use the dataset

This guide will provide you with all the information needed to use the Fannie Mae and Freddie Mac Loan-Level Dataset for 2016. The dataset contains loan-level data for both Fannie Mae and Freddie Mac, including loans acquired in 2016. It includes details such as homeowner demographics, loan-to-value ratio, census tract location, and affordability of mortgage.

The first step to using this dataset is understanding how it is organized. There are 38 fields that make up the loan level data set, making it easy to understand what is being looked at. For each field there is a description of what the field represents and potential values it can take on (i.e., if it’s an integer or float). Having an understanding of the different fields will help when querying certain data points or comparing/contrasting.

Once you understand what type of information is available in this dataset you can start to create queries or visualizations that compare trends across Fannie Mae & Freddie Mac loans made in 2016. Depending on your interest areas such as homeownership rates or income disparities certain statistics may be pulled from the dataset such as borrower’s Annual Income Ratio per area median family income by state code or a comparison between Race & Ethnicity breakdown between borrowers and co-borrowers from various states respective MSAs, among other possibilities based on your inquiries . Visualizations should then be created so that clear comparisons and contrasts could be seen more easily by other users who may look into this same dataset for additional insights as well .

After creating queries/visualization , you can dive deeper into research about corresponding trends & any biases seen within these datasets related within particular racial groupings compared against US Postal & MSA codes used within the 2010 Census Tract locations throughout the US respectively by further utilizing publicly available research material that looks at these subjects with regards housing policies implemented through out years one could further draw conclusions depending on their current inquiries

Research Ideas

• Use the dataset to analyze borrowing patterns based on race, nationality and gender, to better understand the links between minority groups and access to credit...

Market DataResidential Mortgage Debt Outstanding—Enterprise Share, 1990 – 2010Total mortgages held or securitized by Fannie Mae and Freddie Mac as a Percentage of Residential Mortgage Debt Outstanding, 1990 – 2010. Note: Currently, FHFA does not have any plans to update this dataset through more recent periods.Single-Family Mortgages Originated and Outstanding, 1990 – 2011 Q2Statistics for conventional and government-insured or -guaranteed loans and, within each of those sectors, for fixed-rate and adjustable-rate mortgages. Conventional loans are also divided into jumbo and non-jumbo loans. Note: Currently, FHFA does not have any plans to update this dataset through more recent periods.​ Treasury and Federal Reserve Purchase Programs for GSE and Mortgage-Related Securities Data on activities by the Department of the Treasury and the Federal Reserve System to support mortgage markets through purchases of securities issued by Fannie Mae, Freddie Mac, and the Federal Home Loan Banks and by Ginnie Mae, a federal agency that guarantees securities backed by mortgages insured or guaranteed by the Federal Housing Administration, the Department of Veterans Affairs, and other federal agencies. More details are available on the Treasury and Federal Reserve Purchase Programs for GSE and Mortgage-Related Securities page. ​Note: Currently, FHFA does not have any plans to update this dataset through more recent periods.

CLTV Range 0% to 30 30.01% to 60 60.01% to 70 70.01% to 75 75.01% to 80 80.01% to 85 85.01% to 90 90.01% to 95 95.01% to 97 97.01% to 100 100.01% and up Credit Score Range 0% to 30 30.01% to 60 60.01% to 70 70.01% to 75 75.01% to 80 80.01% to 85 85.01% to 90 90.01% to 95 95.01% to 97 97.01% to 100 100.01% and up Total 639 and lower 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 1% 640 to < 660 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 1% 660 to < 680 0% 0% 0% 0% 1% 0% 0% 1% 0% 0% 0% 3% 680 to < 700 0% 0% 0% 0% 1% 0% 1% 1% 0% 0% 0% 4% 700 to < 720 0% 1% 0% 0% 1% 0% 1% 2% 1% 0% 0% 7% 720 to < 740 0% 1% 1% 1% 2% 0% 1% 3% 1% 0% 0% 10% 740 to < 760 0% 1% 1% 1% 3% 1% 2% 3% 1% 0% 0% 14% 760 to < 780 0% 2% 2% 2% 5% 1% 2% 4% 1% 0% 0% 19% 780 and greater 1% 7% 4% 4% 11% 2% 4% 6% 1% 0% 0% 41% Total 2% 13% 9% 9% 25% 4% 12% 20% 5% 0% 0% 100.0%

Graph and download economic data for Agency-and GSE-Backed Mortgage Pools; Total Mortgages Held in a Fannie Mae Pool; Asset, Transactions (BOGZ1FA413065045Q) from Q4 1946 to Q2 2025 about GSE-Backed, fannie mae, mortgage, transactions, assets, and USA.

During the Global Financial Crisis of 2007-2008, a number of systemically important financial institutions in the United States declared bankruptcy, sought takeovers to prevent financial failure, or turned to the U.S. government for bailouts. Two of these institutions, Fannie Mae and Freddie Mac, were government-sponsored enterprises (GSEs), meaning that they were set up by the federal government in order to steer credit towards lower income homebuyers through interventions in the secondary mortgage market. While both were chartered by the government, they were also publicly traded companies, with a majority of shares owned by private investors. The fall of Fannie Mae and Freddie Mac These GSEs' business model was based on buying mortgages from their originators (banks, mortgage brokers, etc.) and then packaging groups of these mortgages together as mortgage-backed securities (MBS), before selling these on again to private investors. While this allowed the expansion of mortgage credit, meaning that many Americans were able to buy houses who would not have in other cases, this also contributed to the growing speculation in the housing market and related financial derivatives, such as MBS. The lowering of mortgage lending standards by originators in the early 2000s, as well as the need for GSEs to compete with their private sector rivals, meant that Fannie Mae and Freddie Mac became caught up in the financial mania associated with the early 2000s U.S. housing bubble. As their losses mounted due to the bursting of the bubble in 2007, both companies came under increasing financial stress, finally being brought into government conservatorship in September 2008. Fannie Mae and Freddie Mac were eventually unlisted from stock exchanges in 2010.

Loan Channel CO Refinance Share Retail 71.2% Correspondent 18.2% Broker 10.6% Loan Channel Purchase Loan Channel Share Retail 49.2% Correspondent 35.0% Broker 15.8%

Graph and download economic data for Government-Sponsored Enterprises; Securitized Multifamily Residential Mortgages Held by Fannie Mae; Asset, Transactions (BOGZ1FA403065463A) from 1946 to 2024 about fannie mae, GSE, multifamily, securitized, transactions, mortgage, family, residential, assets, and USA.

The Federal Housing Finance Agency (FHFA) is an independent regulatory agency that is not part of the Department of Housing and Urban Development (HUD). The FHFA was established by the Housing and Economic Recovery Act of 2008 (HERA) and is responsible for the effective supervision, regulation, and housing mission oversight of Fannie Mae, Freddie Mac (the Enterprises), Common Securitization Solutions, LLC (CSS), ​ and the Federal Home Loan Bank System, which includes the 11 Federal Home Loan Banks (FHLBanks) and the Office of Finance. Since 2008, FHFA has also served as conservator of Fannie Mae and Freddie Mac. Conforming Loan Limits are mortgage limits set annually (as required by HERA) by the FHFA. In order for a mortgage loan to be eligible to be insured by Freddie Mac or Fannie Mae, the loan amount must be less than the loan limit. Mortgage exceeding the Conforming Loan Limit are referred to as "non-conforming loans" or "jumbo loans." While most counties use a single set of Conforming Loan Limits based on the number of units, high cost of living counties use higher Conforming Loan Limits. The FHFA analyzes year-over-year change in average home prices in October of each year using the Monthly Interest Rate Survey (MIRS) to adjust the Conforming Loan Limits for the upcoming year.Geospatial data in this feature service uses the Census 2010 County geographies.To learn more about about the FHFA, please visit: https://www.fhfa.gov/AboutUs For more information about FHFA Conforming Loan Limits, please visit: https://www.fhfa.gov/DataTools/Downloads/Pages/Conforming-Loan-Limits.aspxDate of Coverage: 2022 Date Updated: Annually Data Dictionary: DD_FHFA Conforming Loan Limits

The minimum equity required for rate and term conventional refinance

The size of the Mortgage Lending Market was valued at USD 1.58 Billion in 2023 and is projected to reach USD 2.89 Billion by 2032, with an expected CAGR of 9.00% during the forecast period. Key drivers for this market are: Digital platforms and AI-driven credit assessments have simplified the application process, improving accessibility and borrower experience. Potential restraints include: Fluctuations in interest rates significantly impact borrowing costs, affecting loan demand and affordability. Notable trends are: The adoption of online portals and mobile apps is transforming the mortgage process with faster approvals and greater transparency.

Counties and areas designated as high-cost for 2025 mortgage loan limits

The FHFA House Price Index (HPI) is a broad measure of the movement of single-family house prices. The HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. This information is obtained by reviewing repeat mortgage transactions on single-family properties whose mortgages have been purchased or securitized by Fannie Mae or Freddie Mac since January 1975.

Agency MBS Market Outlook

According to our latest research, the global Agency MBS market size reached USD 9.8 trillion in 2024, with a robust compound annual growth rate (CAGR) of 5.1% observed over the past year. The market is expected to grow steadily, reaching an estimated USD 15.7 trillion by 2033, driven by factors such as heightened investor demand for stable fixed-income instruments, evolving regulatory frameworks, and ongoing innovation in mortgage-backed securities structuring. As per our latest research, the Agency MBS market is witnessing significant momentum due to its perceived safety, liquidity, and the continued support from government-sponsored enterprises (GSEs).

One of the primary growth factors for the Agency MBS market is the persistent demand for yield in a low-interest-rate environment. Institutional investors, including pension funds, insurance companies, and asset managers, are increasingly allocating capital to Agency MBS due to their attractive risk-adjusted returns and implicit government backing. The market’s resilience during periods of economic uncertainty further enhances its appeal, with investors seeking the safety net provided by Ginnie Mae, Fannie Mae, and Freddie Mac. Additionally, the ongoing expansion of the global middle class and rising homeownership rates, particularly in North America and Asia Pacific, are fueling the origination of underlying mortgages, thereby expanding the pool of eligible assets for securitization.

Technological advancements and digitalization are also playing a pivotal role in the Agency MBS market’s growth trajectory. Enhanced data analytics, automated underwriting processes, and blockchain-based securitization platforms are improving transparency, efficiency, and risk assessment in the mortgage origination and securitization value chain. These innovations are not only reducing operational costs but also enabling more granular risk segmentation and tailored product offerings. Moreover, regulatory reforms aimed at increasing market stability—such as stricter capital requirements and enhanced disclosure standards—are fostering greater investor confidence and participation, particularly among global institutional investors seeking diversification.

Another key driver is the evolving regulatory and macroeconomic landscape. The proactive involvement of central banks, especially the U.S. Federal Reserve, in purchasing Agency MBS as part of quantitative easing programs has provided a significant liquidity buffer and compressed spreads, making these securities even more attractive. Furthermore, the gradual normalization of monetary policy is expected to create new opportunities for active portfolio management and trading strategies within the Agency MBS space. The combination of strong government support, robust investor demand, and continuous product innovation is positioning the Agency MBS market for sustained growth over the forecast period.

Regionally, North America continues to dominate the Agency MBS market, accounting for over 70% of global issuance in 2024, driven by the deep and liquid U.S. secondary mortgage market, strong regulatory oversight, and the presence of major GSEs. Europe and Asia Pacific are emerging as growth frontiers, with increasing adoption of securitization frameworks and rising cross-border investment flows. While Latin America and the Middle East & Africa currently represent smaller shares, ongoing financial sector reforms and efforts to deepen local capital markets are expected to provide new growth avenues in these regions. Overall, the global Agency MBS market is characterized by a dynamic interplay of macroeconomic, regulatory, and technological factors, underpinning its long-term growth outlook.

Product Type Analysis

The Agency MBS market is broadly segmented by product type into Pass-Throughs, Collateralized Mortgage Obligations (CMOs), Stripped MBS, and Others. Pass-Through securities remain the dominant product type, accounting for appr