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.

Foreclosure types considered for this analysis include lender owned and third-party owned foreclosures as well as foreclosed properties ready for auction. Contra Costa and Solano counties showed the highest foreclosure rates in the San Francisco Bay Region during the first half of 2009 with up to 170 foreclosures per tract.

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.

Between 2015 and 2017, Memphis, Tennessee had the highest eviction rate at *** percent. The metropolitan areas with the next highest eviction rates were Phoenix (Arizona), Atlanta (Georgia), Indianapolis (Indiana) and Dallas (Texas) in that period.

Why do evictions occur? Eviction rate refers to the share of renters who are legally removed from a rental property by their landlord, because rent is overdue, the tenant has breached a condition of the rental agreement or for other legally permitted reasons.

Higher rates in the South and Midwest Eviction rates tend to be higher in the South and Midwest of the country, because median incomes are low and foreclosure rates are high. Vacancy rates are consistently higher in the South and Midwest than in the Northeast and West, which means that landlords cannot afford to be as picky when choosing a tenant in the South and Midwest. Tenants who struggle to pay their rent have a much lower chance of being chosen as tenant in the more competitive rental markets, which also keeps the eviction rates lower in those areas.

This hosted feature layer has been published in RI State Plane Feet NAD 83.The RI Neighborhood Stabilization Program (NSP) Mapping analysis was performed to assist the Office of Housing and Community Development in identifying target areas with both a Foreclosure Rate (Block Group Level) >=6.5% and a Subprime Loan percentage rate >= 1.4% (Zip Code Level). Based on these criteria the following communities were identified as containing such target areas: Central Falls, Cranston, Cumberland, East Providence, Johnston, North Providence, Pawtucket, Providence, Warwick, West Warwick, and Woonsocket. Federal funding, under the Housing and Economic Recovery Act of 2008 (HERA), Neighborhood Stabilization Program (NSP), totaling $19.6 will be expended in these NSP Target Areas to assist in the rehabilitation and redevelopment of abandoned and foreclosed homes, stabilizing communities.The State of Rhode Island distributes funds allocated, giving priority emphasis and consideration to those areas with the greatest need, including those areas with - 1) Highest percentage of home foreclosures; 2) Highest percentage of homes financed by subprime mortgage loans; and 3) Anticipated increases in rate of foreclosure. The RI Office of Housing and Community Development, with the assistance of Rhode Island Housing, utilized the following sources to meet the above requirements. 1) U.S. Department of Housing & Urban Development (HUD) developed foreclosure data to assist grantees in identification of Target Areas. The State utilized HUD's predictive foreclosure rates to identify those areas which are likely to face a significant rise in the rate of home foreclosures. HUD's methodology factored in Home Mortgage Disclosure Act, income, unemployment, and other information in its calculation. The results were analyzed and revealed a high level of consistency with other needs data available. 2) The State obtained subprime mortgage loan information from the Federal Reserve Bank of Boston. Though the data does not include all mortgages, and was only available at the zip code level rather than Census Tract, findings were generally consistent with other need categories. This data was joined to the Foreclosure dataset in order to select areas with both a Foreclosure Rate >=6.5% and a Subprime Loan Rate >=1.4%. 3) The State also obtained, from the Warren Group, actual local foreclosure transaction records. The Warren Group is a source for real estate and banking news and transaction data throughout New England. This entity has analyzed local deed records in assembling information presented. The data set was normalized due to potential limitations. An analysis revealed a high level of consistency with HUD-predictive foreclosure rates.

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.

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.

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.

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.

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.

We use nationwide deed-level records on home foreclosures to examine the effects of economic distress on electoral outcomes and individual voter turnout. County-level difference-in-differences estimates show that counties that suffered larger increases in foreclosures did not punish or reward members of the incumbent president’s party more than less affected counties. Linking the Ohio voter file to individual foreclosures, difference-in-differences estimates show that individuals whose homes were foreclosed on were less likely to turn out, rather than being mobilized. However, in 2016 counties more exposed to foreclosures supported Trump at substantially higher rates. Taken together, the evidence suggests that the effect of local economic distress on incumbent performance is generally close to zero and only becomes substantial in unusual circumstances.

Between 2005-2009 and 2009-2013, homeownership rates in the nine-county San Francisco Bay Region decreased by about 2.8% overall. However, the rates vary significantly across the region.The region's lower-income neighborhoods and its outer suburbs were most impacted by the foreclosure crisis and therefore experienced the sharpest drop in homeownership rates. These communities include, Oakland, Hayward, and San Ramon. On average, in 2013, the region had fewer homeowners than in 2005. These households will likely not benefit as much from the recent recovery compared to households that were able to retain ownership of their homes during the Great Recession.

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.

Demand for employee relocation services is highly linked to economic activity and the housing market. Since these indicators shift often, revenue is often volatile for providers. COVID-19 caused governments to shut down businesses and enforce quarantines, severely reducing economic activity. Corporations had less money to spend on employee relocation services, so the industry took a big hit. The pandemic recovery resulted in a surge in consumer spending, boosting corporate profit and aiding revenue growth in 2021 and 2022. Increased business formation and employment raised the supply of potential customers for the industry, so this trend also boosted companies’ performance. Recent years brought challenges: rising interest rates constrained homebuying and moving, while recessionary fears prompted companies to pull back, muting revenue growth in 2023 and 2024. The easing of rates in late 2024 offered some relief, helping the housing market, and demand for relocations partially rebounded. Higher purchase expenses and miscellaneous expenses have put downward pressure on profit since 2020. Meanwhile, remote work trends have increased short-term assignments, decreasing large relocations and shifting providers' focus toward digital services. The growing preference for renting over homeownership means that rental assistance has become pivotal in relocation firm offerings, while flexible housing options and urban multifamily markets are increasingly important for corporate moves. Overall, revenue for employee relocation services businesses has expanded at a CAGR of 2.2% over the past five years, reaching $35.6 billion in 2025. This includes a 1.3% rise in revenue in that year. Servicers will face opportunities and challenges moving forward. Major tariffs imposed in 2025 are expected to dampen consumer spending and potentially trigger a recession, lowering disposable income and corporate profit, which could slow downstream demand for employee relocation services. All service segments—including real estate and moving assistance—are at risk of declining revenue if business activity drops. However, long-term GDP growth is projected to remain solid. Demographic changes, personalized solutions, globalization and technological innovations are expected to sustain modest revenue growth and help relocation firms adapt to evolving market challenges in the near future. Overall, revenue for employee relocation services providers is forecast to rise at a CAGR of 1.9% in the next five years, reaching $39.2 billion in 2030.

Greece, Cyprus, and Hungary were the countries with the highest share of non-performing mortgage loans in the second quarter of 2023. In Greece, *** percent of the gross carrying amount of mortgage loans to households was considered non-performing. In Spain, which was the country with the highest value of non-performing mortgages, this share was *** percent.