The foreclosure rate in the United States has experienced significant fluctuations over the past two decades, reaching its peak in 2010 at **** percent following the financial crisis. Since then, the rate has steadily declined, with a notable drop to **** percent in 2021 due to government interventions during the COVID-19 pandemic. In 2024, the rate stood slightly higher at **** percent but remained well below historical averages, indicating a relatively stable housing market. Impact of economic conditions on foreclosures The foreclosure rate is closely tied to broader economic trends and housing market conditions. During the aftermath of the 2008 financial crisis, the share of non-performing mortgage loans climbed significantly, with loans 90 to 180 days past due reaching *** percent. Since then, the share of seriously delinquent loans has dropped notably, demonstrating a substantial improvement in mortgage performance. Among other things, the improved mortgage performance has to do with changes in the mortgage approval process. Homebuyers are subject to much stricter lending standards, such as higher credit score requirements. These changes ensure that borrowers can meet their payment obligations and are at a lower risk of defaulting and losing their home. Challenges for potential homebuyers Despite the low foreclosure rates, potential homebuyers face significant challenges in the current market. Homebuyer sentiment worsened substantially in 2021 and remained low across all age groups through 2024, with the 45 to 64 age group expressing the most negative outlook. Factors contributing to this sentiment include high housing costs and various financial obligations. For instance, in 2023, ** percent of non-homeowners reported that student loan expenses hindered their ability to save for a down payment.

Graph and download economic data for Large Bank Consumer Mortgage Balances: 60 or More Days Past Due: Including Foreclosures Rates: Accounts Based (RCMFLBACTDPDPCT60P) from Q3 2012 to Q1 2025 about 60 days +, accounts, FR Y-14M, large, balance, mortgage, consumer, banks, depository institutions, rate, and USA.

The number of properties with foreclosure filings in the United States declined in 2024, but remained below the pre-pandemic level. Foreclosure filings were reported on approximately ******* properties, which was about ****** fewer than in 2023. Despite the decrease, 2024 saw one of the lowest foreclosure rates on record.

In the second quarter of 2025, the share of mortgage loans in the foreclosure process in the U.S. decreased slightly to **** percent. Following the outbreak of the coronavirus crisis, the mortgage delinquency rate spiked to the highest levels since the subprime mortgage crisis (2007-2010). To prevent further impact on homeowners, Congress passed the CARES Act, which provides foreclosure protections for borrowers with federally backed mortgage loans. As a result, the foreclosure rate fell to historically low levels.

Active foreclosure properties that are currently on the market (includes Pre-foreclosure Auction and REO properties). This matches the active listings shown on RealtyTrac. Does not include historical foreclosure data.

In the second quarter of 2024, the share one-to-four family residential mortgage loans entering the foreclosure process in the U.S. was **** percent. Following the coronavirus pandemic outbreak in 2020, mortgage delinquency rates surged, followed by a gradual decline. Between the second quarter of 2020 and the first quarter of 2022, foreclosures remained at record low levels due to The Coronavirus Aid, Relief, and Economic Security Act (CARES Act).

View quarterly updates and historical trends for US Consumers with New Foreclosure. from United States. Source: Federal Reserve Bank of New York. Track ec…

Graph and download economic data for Nonfarm Real Estate Foreclosures for United States (M09075USM476NNBR) from Jan 1934 to Mar 1963 about real estate, nonfarm, and USA.

Following the drastic increase directly after the COVID-19 pandemic, the delinquency rate started to gradually decline, falling below *** percent in the second quarter of 2023. In the second half of 2023, the delinquency rate picked up but remained stable throughout 2024. In the second quarter of 2025, **** percent of mortgage loans were delinquent. That was significantly lower than the **** percent during the onset of the COVID-19 pandemic in 2020 or the peak of *** percent during the subprime mortgage crisis of 2007-2010. What does the mortgage delinquency rate tell us? The mortgage delinquency rate is the share of the total number of mortgaged home loans in the U.S. where payment is overdue by 30 days or more. Many borrowers eventually manage to service their loan, though, as indicated by the markedly lower foreclosure rates. Total home mortgage debt in the U.S. stood at almost ** trillion U.S. dollars in 2024. Not all mortgage loans are made equal ‘Subprime’ loans, being targeted at high-risk borrowers and generally coupled with higher interest rates to compensate for the risk. These loans have far higher delinquency rates than conventional loans. Defaulting on such loans was one of the triggers for the 2007-2010 financial crisis, with subprime delinquency rates reaching almost ** percent around this time. These higher delinquency rates translate into higher foreclosure rates, which peaked at just under ** percent of all subprime mortgages in 2011.

United States - Delinquency Rate on Loans Secured by Real Estate, Banks Ranked 1st to 100th Largest in Size by Assets was 1.94% in January of 2025, according to the United States Federal Reserve. Historically, United States - Delinquency Rate on Loans Secured by Real Estate, Banks Ranked 1st to 100th Largest in Size by Assets reached a record high of 11.49 in January of 2010 and a record low of 1.31 in October of 2004. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Delinquency Rate on Loans Secured by Real Estate, Banks Ranked 1st to 100th Largest in Size by Assets - last updated from the United States Federal Reserve on August of 2025.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The study integrated neighborhood-level data on robbery and burglary gathered from local police agencies across the United States, foreclosure data from RealtyTrac (a real estate information company), and a wide variety of social, economic, and demographic control variables from multiple sources. Using census tracts to approximate neighborhoods, the study regressed 2009 neighborhood robbery and burglary rates on foreclosure rates measured for 2007-2008 (a period during which foreclosure spiked dramatically in the nation), while accounting for 2007 robbery and burglary rates and other control variables that captured differences in social, economic, and demographic context across American neighborhoods and cities for this period. The analysis was based on more than 7,200 census tracts in over 60 large cities spread across 29 states. Core research questions were addressed with a series of multivariate multilevel and single-level regression models that accounted for the skewed nature of neighborhood crime patterns and the well-documented spatial dependence of crime. The study contains one data file with 8,198 cases and 99 variables.

About ***** percent of U.S. homeowners with a mortgage who were behind on mortgage payments in ************ were very likely to face eviction in the next two months due to a foreclosure. Additionally, ** percent of the respondents were somewhat likely to be evicted. In 2022, the foreclosure rate in the U.S. picked up, after a long period of steady decline after the subprime mortgage crisis.

Residential mortgage arrears and foreclosure rates in Canada and the U.S. from 2002 to today. This table lets housing professionals compare data by type of mortgage in the U.S. and by region in Canada.

Snapshot img { margin: 10px !important; } About Housing Mortgage Mortgage is a debt instrument that the borrower is obliged to pay back with a fixed set of payments and is secured by the collateral of a specified real estate property. Mortgages enable individuals and businesses to make large real estate purchases without paying the entire value of the purchase in one go. Borrowers repay the loan along with interest over a period of many years until they eventually own the property free and clear. However, if borrowers stop paying the mortgage, the lender can foreclose and may evict the property’s owner and sell it, using the income from the sale to clear the mortgage debt. In a fixed-rate mortgage system, borrowers pay the same interest rate for the life of the loan. Most fixed-rate mortgages have a 15 or 30-year term. There is no influence on borrowers’ payment if market interest rates rise. However, if market interest rates decline significantly, borrowers may be able to secure that lower rate by means of refinancing the mortgage. TechNavio's analysts forecast the Housing Mortgage market in the US to grow at a CAGR of 1.75 percent over the period 2013-2018.Covered in this Report This report covers the present scenario and the growth prospects of the Housing Mortgage market in the US for the period 2014-2018. To calculate the market size, the report considers the loan volume of primary housing mortgage banks, credit unions, and financial institutions. It takes into consideration the various product segments such as Home Purchase, Home Improvement, and Refinancing. The report mentions the role played by Federal Government by the way of government-sponsored enterprises operating in the system. TechNavio's report, the Housing Mortgage Market in the US 2014-2018, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the US; it also covers the landscape of the Housing Mortgage market in the US and its growth prospects in the coming years. The report also includes a discussion of the key vendors operating in this market.Key Regions • USKey Vendors • Bank of America • Citigroup • JPMorgan Chase • U.S. Bancorp • Wells FargoOther Prominent Vendors • Ally Financial • Capital One Financial • Fifth Third Bancorp • Flagstar Bank, FSB • SunTrust Banks • Quicken Loans • Regions FinancialMarket Driver • Improved Demand for Home Loans • For a full, detailed list, view our reportMarket Challenge • Shrinking Lending Capacity • For a full, detailed list, view our reportMarket Trend • Less Incidence of Foreclosures • For a full, detailed list, view our reportKey Questions Answered in this Report • What will the market size be in 2018 and what will the growth rate be? • What are the key market trends? • What is driving this market? • What are the challenges to market growth? • Who are the key vendors in this market space? • What are the market opportunities and threats faced by the key vendors? • What are the strengths and weaknesses of the key vendors?

Graph and download economic data for Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, All Commercial Banks (DRSFRMACBS) from Q1 1991 to Q2 2025 about domestic offices, delinquencies, 1-unit structures, mortgage, family, residential, commercial, domestic, banks, depository institutions, rate, and USA.

Annual residential mortgage arrears and foreclosure rates in Canada and the U.S. from 1990 to 2013. This table is archived for reference, research and record-keeping purposes only. It is not subject to Government of Canada Web Standards and has not been altered or updated since it was archived.

Graph and download economic data for Delinquency Rate on Commercial Real Estate Loans (Excluding Farmland), Booked in Domestic Offices, All Commercial Banks (DRCRELEXFACBS) from Q1 1991 to Q2 2025 about farmland, domestic offices, delinquencies, real estate, commercial, domestic, loans, banks, depository institutions, rate, and USA.

Abstract

Title: Cotality Smart Data Platform (SDP): Owner Transfer and Mortgage

The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in June 2024, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C.

Formerly known as CoreLogic Smart Data Platform: Owner Transfer & Mortgage.

Methodology

In the United States, parcel data is public record information that describes a division of land (also referred to as "property" or "real estate"). Each parcel is given a unique identifier called an Assessor’s Parcel Number or APN. The two principal types of records maintained by county government agencies for each parcel of land are deed and property tax records. When a real estate transaction takes place (e.g. a change in ownership), a property deed must be signed by both the buyer and seller. The deed will then be filed with the County Recorder’s offices, sometimes called the County Clerk-Recorder or other similar title. Property tax records are maintained by County Tax Assessor’s offices; they show the amount of taxes assessed on a parcel and include a detailed description of any structures or buildings on the parcel, including year built, square footages, building type, amenities like a pool, etc. There is not a uniform format for storing parcel data across the thousands of counties and county equivalents in the U.S.; laws and regulations governing real estate/property sales vary by state. Counties and county equivalents also have inconsistent approaches to archiving historical parcel data.

To fill researchers’ needs for uniform parcel data, Cotality collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. Cotality augments this data with information gathered from other public and non-public sources (e.g., loan issuers, real estate agents, landlords, etc.). The Stanford Libraries has purchased bulk extracts from Cotality's parcel data, including mortgage, owner transfer, pre-foreclosure, and historical and contemporary tax assessment data. Data is bundled into pipe-delimited text files, which are uploaded to Data Farm (Redivis) for preview, extraction and analysis.

For more information about how the data was prepared for Redivis, please see Cotality 2024 GitLab.

Usage

The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in June 2024, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C. The Owner Transfer data provides historical information about property sales and ownership-related transactions, including full, nominal, and quitclaim transactions (involving a change in title/ownership). It contains comprehensive property and transaction information, such as property characteristics, current ownership, transaction history, title company, cash purchase/foreclosure/resale/short sale indicators, and buyer information.

The Mortgage data provides historical information at the mortgage level, including purchase, refinance, equity, as well as details associated with each transaction, such as lender, loan amount, loan date, interest rate, etc. Mortgage details include mortgage amount, type of loan (conventional, FHA, VHA), mortgage rate type, mortgage purpose (cash out first, consolidation, standalone subordinate), mortgage ARM features, and mortgage indicators such as fixed-rate, conforming loan, construction loan, and private party. The Mortgage data also includes subordinate mortgage types, rate details, and lender details (NMLS ID, Loan Company, Loan Officers).

The Property, Mortgage, Owner Transfer, Historical Property and Pre-Foreclosure data can be linked on the CLIP, a unique identification number assigned to each property.

Mortgage records can be linked to a transaction using the MORTGAGE_COMPOSITE_TRANSACTION_ID.

For more information about included variables, please see:

• cotality_sdp_owner_transfer_data_dictionary_2024.txt
• cotality_sdp_mortgage_data_dictionary_2024.txt
• Mortgage_v3.xlsx
• Owner Transfer_v3.xlsx

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For a count of records per FIPS code, please see cotality_sdp_owner_transfer_counts_2024.txt and cotality_sdp_mortgage_counts_2024.txt.

For more information about how the Cotality Smart Data Platform: Owner Transfer and Mortgage data compares to legacy data, please see 2025_Legacy_Content_Mapping.pdf.

Bulk Data Access

Data access is required to view this section.

Abstract

The Owner Transfer data provides historical information about property sales and ownership-related transactions, including full, nominal, and quitclaim transactions (involving a change in title/ownership). The Owner Transfer data contains comprehensive property and transaction information, such as property characteristics, current ownership, transaction history, title company, cash purchase/foreclosure/resale/short sale indicators, and buyer information.

The Mortgage data provides historical information at the mortgage level, including purchase, refinance, equity, as well as details associated with each transaction, such as lender, loan amount, loan date, interest rate, etc. Mortgage details include mortgage amount, type of loan (conventional, FHA, VHA), mortgage rate type, mortgage purpose (cash out first, consolidation, standalone subordinate), mortgage ARM features, and mortgage indicators such as fixed-rate, conforming loan, construction loan, and private party. The Mortgage data also includes subordinate mortgage types, rate details, and lender details (NMLS ID, Loan Company, Loan Officers).

The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in August 2022, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C.

The CoreLogic Smart Data Platform (SDP) Owner Transfer and Mortgage data was formerly known as the CoreLogic Deed data. The CoreLogic Deed data contained both owner transfer and mortgage information. In the CoreLogic Smart Data Platform (SDP), this data was separated into two tables: Owner Transfer and Mortgage. Between the two tables, the CoreLogic Smart Data Platform (SDP) Owner Transfer and Mortgage data contains almost all of the variables that were included in the CoreLogic Deed data. Further, each CoreLogic Smart Data Platform (SDP) table is augmented with additional owner transfer and mortgage characteristics.

Methodology

In the United States, parcel data is public record information that describes a division of land (also referred to as "property" or "real estate"). Each parcel is given a unique identifier called an Assessor’s Parcel Number or APN. The two principal types of records maintained by county government agencies for each parcel of land are deed and property tax records. When a real estate transaction takes place (e.g. a change in ownership), a property deed must be signed by both the buyer and seller. The deed will then be filed with the County Recorder’s offices, sometimes called the County Clerk-Recorder or other similar title. Property tax records are maintained by County Tax Assessor’s offices; they show the amount of taxes assessed on a parcel and include a detailed description of any structures or buildings on the parcel, including year built, square footages, building type, amenities like a pool, etc. There is not a uniform format for storing parcel data across the 3,006 counties in the U.S.; laws and regulations governing real estate/property sales vary by state. Counties also have inconsistent approaches to archiving historical parcel data.

To fill researchers’ needs for uniform parcel data, CoreLogic collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. CoreLogic augments this data with information gathered from other public and non-public sources (e.g., loan issuers, real estate agents, landlords, etc.). The Stanford Libraries have purchased bulk extracts from CoreLogic’s public records data, including mortgage, owner transfer, pre-foreclosure, and historical and contemporary tax assessment data. Data is bundled into pipe-delimited text files, which we upload to Redivis for preview, extraction and light analysis.

Usage

The Property, Mortgage, Owner Transfer, Historical Property and Pre-Foreclosure data can be linked on the CLIP, a unique identification number assigned to each property.

Mortgage records can be linked to a transaction using the Mortgage Composite Transaction ID.

For more information about included variables, please see Core_Logic_SDP_Owner_Transfer_Codebook.xlsx and Core_Logic_SDP_Mortgage_Codebook.xlsx (under** Supporting files**).

For a count of records per FIPS code, please see owner_transfer_counts.txt and mortgage_counts.txt (under Supporting files).

For more information about how the CoreLogic Smart Data Platform: Owner Transfer and Mortgage data compares to legacy data, please see ***Legacy_Content_Mapping.pdf ***(under Supporting files).

Bulk Data Access

Data access is required to view this section.

The real estate sales and brokerage industry is navigating a complex landscape with high mortgage rates and dropping home sales. The Federal Reserve's decision to raise the benchmark interest rate 11 times across 2022 and 2023 to combat inflation led to a significant climb in mortgage rates, dampening buyer demand and affordability. This gain has deterred homeowners from selling, leading to low housing inventory. Despite the rate cuts that came in 2024, mortgage rates remain high, with the typical 30-year fixed mortgage staying above 6.5%. Existing home sales also hit a near 30-year low in 2024, mainly because of high home prices and tight supply. Amid these challenges, the real estate market has seen a surge in home values, propelling industry growth. This growth greatly benefits real estate agents and brokerages, who often base their commissions on the house's selling price. Despite the high vacancy rates, the office market also shows signs of picking up, primarily because of demand for high-quality assets such as Class A office spaces and modern buildings. Increased competitive pressure necessitates more aggressive marketing tactics to secure listings and attract sellers. Nonetheless, because of the industry's robust performance from 2020 to 2021, revenue has climbed at a CAGR of 0.8% over the past five years, reaching $241.3 billion in 2025. 2025 revenue will climb an estimated 1.0% as home price appreciation and a rebound in commercial sales volume will fuel tepid growth. The higher-for-longer interest rate environment is expected to slow the industry's growth. The high mortgage rates and escalating home prices will likely price out many potential home buyers from the market, forcing customers to rent or live in multifamily complexes. The limited new office construction will stimulate office building sales and intensify brokerage activity. The housing stock situation is expected to remain tight, with homeowners staying in their homes for longer and contributing to home price appreciation. Amid these conditions, a likely shift toward new construction and build-to-rent properties for agents and brokers is anticipated. Increased competition in the form of market saturation and disruption from online platforms will inhibit profit growth. Overall, industry revenue will gain at a CAGR of 2.3% to reach $270.8 billion in 2030.