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: 30 or More Days Past Due: Including Foreclosures Rates: Balances Based (RCMFLBBALDPDPCT30P) from Q3 2012 to Q1 2025 about 30 days +, FR Y-14M, large, balance, mortgage, consumer, banks, depository institutions, rate, and USA.

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.

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.

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.

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 first 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.

Our foreclosure data offering provides an extensive suite of real-time real estate data, available through both API integration and bulk data delivery. This rich dataset is designed to meet the needs of a variety of users, from real estate investors to foreclosure prevention services and market analysts. With over 31 data points available, this dataset covers multiple aspects of foreclosure processes, including auction details, loan information, foreclosure status, and trustee data. Below is a detailed description of the data points and their potential use cases.

Data Points Overview for Foreclosure Data:

1. Auction Data (9+ Data Points) Auction Location, Auction Time, Case Number, Bid Parameters

2. Loans/Lender Data (9+ Data Points) Lender Name, Original Loan Details, Unpaid Balances, Pre-Foreclosure Flags, Related Documents

3. Foreclosure Status Data (7+ Data Points) Recording Date, Release Date, Status Indicators and Codes

4. Trustee Data (6+ Data Points) Trustee Name, Trustee Address, Trustee Phone Number, Sale Number

Top Use Cases

1. Surface Investment Opportunities Websites and Applications: Integrate our foreclosure data into real estate platforms to provide users with up-to-date information on potential investment properties. This can enhance search functionality and deliver greater value by identifying promising foreclosure opportunities.

2. Foreclosure Prevention Services Sales and Marketing: Leverage foreclosure data to target homeowners in distress with tailored marketing efforts. By identifying properties in pre-foreclosure status, you can focus your outreach to offer services designed to prevent foreclosure, such as financial counseling or loan modification programs.

3. Market Analysis and Predictive Analytics Data-Driven Insights: Utilize the comprehensive dataset to perform in-depth market analysis and develop predictive models. This can help forecast foreclosure trends, assess market conditions, and make informed decisions based on historical and current foreclosure activity.

Access and Delivery

Our foreclosure data is accessible through two primary methods: - API Integration: Seamlessly integrate the data into your applications or platforms with our robust API, offering real-time access and automated updates. - Bulk Data Delivery: Obtain large datasets for offline analysis or integration into internal systems through bulk delivery options, providing flexibility in how you utilize the information.

This comprehensive data listing is designed to empower users with detailed and actionable foreclosure data, facilitating a range of applications from investment analysis to foreclosure prevention and market forecasting.

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, commercial, residential, domestic, banks, depository institutions, rate, and USA.

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.

The mortgage delinquency rate for Federal Housing Administration (FHA) loans in the United States declined since 2020, when it peaked at ***** percent. In the second quarter of 2024, **** percent of FHA loans were delinquent. Historically, FHA mortgages have the highest delinquency rate of all mortgage types.

Federal Housing Administration (FHA) loans had the highest delinquency rate in the United States in 2025. As of the second quarter of the year, ***** percent of the outstanding one-to-four family housing mortgage loans were ** days or more delinquent. This percentage was lower for conventional loans and Veterans Administration loans. Despite a slight increase, the delinquency rate for all mortgages was one of the lowest on record.

As a result of the coronavirus (COVID-19) crisis, many people worldwide faced job insecurity and loss of income. For mortgage borrowers in the United States, this means increased default and foreclosure risk. Forbearance is a type of borrower assistance which allows the lender to negotiate a temporary postponement of a mortgage repayment. It allows a payment period relief in lieu of the creditor foreclosing on any property that was used as collateral for the loan.

As of March 2022, New York was one of the states in the United States with highest forbearance rate for Freddie Mac single-family housing loans with approximately **** percent of current loans in forbearance.

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.

As of March 2025, the 30-day delinquency rate for commercial mortgage-backed securities (CMBS) varied per property type. The share of late payments for office CMBS was the highest at over **** percent, about ***** percentage points higher than the average for all asset classes. A 30-day delinquency refers to payments that are one month late, regardless of how many days the month has. Commercial mortgage-backed securities are fixed-income investment products which are backed by mortgages on commercial property.

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

%3C!-- --%3E

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.