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.

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.

Graph and download economic data for Large Bank Consumer Mortgage Balances: 90 or More Days Past Due: Including Foreclosures Rates: Balances Based (RCMFLBBALDPDPCT90P) from Q3 2012 to Q1 2025 about 90 days +, FR Y-14M, large, balance, mortgage, consumer, banks, depository institutions, rate, and USA.

Product Overview

You’re a few short steps away from accessing the largest and most comprehensive Pre-Foreclosure and Foreclosure database in the country. Whether you want to conduct property research, data analysis, purchase distressed properties, or market your services, licensing Pre-Foreclosure and Foreclosure Data provides in-depth intelligence on distressed properties across the country that will inform your next move.

What is Foreclosure?

Foreclosure is the legal process of taking possession of a mortgaged property when the borrower fails to keep up with mortgage payments. The foreclosure process varies from state to state, depending on whether the state has a judicial or nonjudicial process. Judicial process requires court action on a foreclosed property, where a nonjudicial process does not.

Foreclosure and Pre-Foreclosure Data Includes:

• 9 Different types of Judicial vs Non-Judicial
• Auctions
• Public Notices
• Lis Pendens
• Releases
• Defendant and Plaintiff Names
• Recording Dates, Published Dates, and Auction Dates
• Original Mortgage Information

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.

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.

Provides monthly totals of Notices of Intent (NOI), Notices of Foreclosure (NOF), and Foreclosure Property Registrations (FPR) for Maryland Counties as reported to the Office of Financial Regulation (OFR). For additional information and definitions, please see the OFR's Foreclosure Data Tracker: https://www.labor.maryland.gov/finance/consumers/frforeclosuredatatracker.shtml. NOTE: The data provided is for informational and research purposes only and is not intended to guide policy or provide specific outreach targets. The data provided is compiled from third-party filings with the Office of Financial Regulation (OFR) pursuant to applicable law. These third-party filings may contain duplicates and other errors and the OFR cannot guarantee the accuracy and quality of the submissions upon which the data is based. The data does not constitute foreclosure case records and may differ from the official foreclosure records contained in the court records of the State of Maryland. OFR makes no express or implied warranties or representations concerning the data contained in this report.

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.

Foreclosure Statistics: Foreclosures on rustic and urban properties begun and registered in Land Registries by province. Annual. Provinces.

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.

This statistic shows the foreclosure filings in the United States as of June 2017, by state. South Dakota had the lowest rate with only *** in every 24,583 housing units being subject to foreclosure.

The foreclosure rate in the United States has experienced significant fluctuations over the past two decades, reaching its peak in 2010 at 2.23 percent following the financial crisis. Since then, the rate has steadily declined, with a notable drop to 0.11 percent in 2021 due to government interventions during the COVID-19 pandemic. In 2024, the rate stood slightly higher at 0.23 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 4.6 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, 52 percent of non-homeowners reported that student loan expenses hindered their ability to save for a down payment.

2024 Foreclosure Properties registered with the LAHD from January 1, 2024 through December 31, 2024.

View quarterly updates and historical trends for Florida Consumers With New Foreclosure. Source: Federal Reserve Bank of New York. Track economic data wit…

Foreclosure Statistics: Dwellings with begun foreclosure according to dwelling status by province. Annual. Provinces.

Monthly foreclosures in Connecticut by county, 2008 through the present. Data updated monthly by the Connecticut Housing Finance Authority and tracked in the following dashboard: https://www.chfa.org/about-us/ct-monthly-housing-market-dashboard/. CHFA has stopped maintaining the dashboard and associated datasets, and this dataset will no longer be updated as of 2022.

Table of INEBase Dwellings with begun foreclosure according to dwelling status. Quarterly. Autonomous Communities and Cities. Foreclosure Statistics

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

Provides the annual total number of Maryland Notices of Intent to Foreclose (NOI) by census tract as reported to the Office of Financial Regulation (OFR). For more information and definitions, please see OFR's Foreclosure Data Tracker: https://www.labor.maryland.gov/finance/consumers/frforeclosuredatatracker.shtml. NOTE: The data provided is for informational and research purposes only and is not intended to guide policy or provide specific outreach targets. The data provided is compiled from third-party filings with the OFR pursuant to applicable law. These third-party filings may contain duplicates and other errors and the OFR cannot guarantee the accuracy and quality of the submissions upon which the data is based. The data does not constitute foreclosure case records and may differ from the official foreclosure records contained in the court records of the State of Maryland. In addition, errors in reported street addresses mean that some NOIs are not able to be matched with a census tract. This may result in a different total number of annual NOIs than the total number in other related reports. OFR makes no express or implied warranties or representations concerning the data contained in this report. Blank values indicate census tracts with fewer than 10 NOIs.

The table Pre-Foreclosure is part of the dataset Cotality Smart Data Platform: Pre-Foreclosure, available at https://stanford.redivis.com/datasets/my00-1hx3kjzzk. It contains 37285932 rows across 91 variables.