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.

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 322,100 properties, which was about 34,900 fewer than in 2023. Despite the decrease, 2024 saw one of the lowest foreclosure rates on record.

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

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 Q4 2024 about 30 days +, FR Y-14M, large, balance, mortgage, consumer, banks, depository institutions, rate, and USA.

Data provides current information regarding single family homes and ranches for sale by the U.S. Federal Government. These previously owned properties are for sale by public auction or other method depending on the property.

This service provides data on Federal Housing Administration (FHA) single family, Real Estate Owned (REO) properties that are up for sale. The U.S. Department of Housing and Urban Development's Real Estate Owned (REO) properties are the result of the Federal Housing Administration (FHA) paying a claim to a lending institution on a foreclosed property which was financed with an FHA Insured Mortgage, and the lender has transferred ownership of the property of to HUD. Typically, title to the property is not transferred (or the claim paid) until the previous owner is evicted from the property. Normally, after the home is transferred to HUD, the property will go up for auction on the HUD Home store website.

Federal Housing Administration Single-Family – Properties for SaleThis National Geospatial Data Asset (NGDA) dataset, shared as a Federal Housing Administration feature layer, displays single-family real estate owned (REO) properties that are up for sale in the United States. Per Housing and Urban Development (HUD), "The U.S. Department of Housing and Urban Development's Real Estate Owned (REO) properties are a result of the Federal Housing Administration (FHA) paying a claim to a lending institution on a foreclosed property which was financed with an FHA Insured Mortgage and the lender transferring ownership of the property to HUD. Typically, title to the property is not transferred (or the claim paid) until the previous owner is evicted from the property. Normally, after the home is transferred to HUD, the property will go up for auction on the HUD Home store website."FHA Single Family Property, Case Number:137-427167Data currency: current federal service (FHA Single Family REO Properties For Sale)NGDAID: 128 (FHA Single Family REO Properties for Sale - National Geospatial Data Asset (NGDA))For more information: The Federal Housing Administration (FHA); FHA Single Family HousingFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Real Property Theme Community. Per the Federal Geospatial Data Committee (FGDC), Real Property is defined as "the spatial representation (location) of real property entities, typically consisting of one or more of the following: unimproved land, a building, a structure, site improvements and the underlying land. Complex real property entities (that is "facilities") are used for a broad spectrum of functions or missions. This theme focuses on spatial representation of real property assets only and does not seek to describe special purpose functions of real property such as those found in the Cultural Resources, Transportation, or Utilities themes."For other NGDA Content: Esri Federal Datasets

The U.S. Department of Housing and Urban Development's Real Estate Owned (REO) properties are the result of the Federal Housing Administration (FHA) paying a claim to a lending institution on a foreclosed property which was financed with an FHA Insured Mortgage, and the lender has transferred ownership of the property of to HUD. Typically, title to the property is not transferred (or the claim paid) until the previous owner is evicted from the property. Normally, after the home is transferred to HUD, the property will go up for auction on the HUD Home store website.Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. Note that these data only include latitude and longitude coordinates and associated attributes for those addresses that can be geocoded to an interpolated point along a street segment, or to a ZIP+4 centroid location. While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD.To learn more about HUD Real Estate Owned Properties visit: https://www.hud.gov/program_offices/housing/sfh/reo, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD FHA REO Properties for SaleDate of Coverage: 03/2025 SnapshotLast Updated: 03/2025

Thailand BAC: Assets: Properties Foreclosed: Net data was reported at 0.000 THB th in Jun 2018. This stayed constant from the previous number of 0.000 THB th for May 2018. Thailand BAC: Assets: Properties Foreclosed: Net data is updated monthly, averaging 0.000 THB th from Jan 2011 (Median) to Jun 2018, with 90 observations. Thailand BAC: Assets: Properties Foreclosed: Net data remains active status in CEIC and is reported by Bank of Thailand. The data is categorized under Global Database’s Thailand – Table TH.KB058: Balance Sheet: Foreign Bank: Bank of America.

VITAL SIGNS INDICATOR
Home Prices (EC7)

FULL MEASURE NAME
Home Prices

LAST UPDATED
December 2022

DESCRIPTION
Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE
Zillow: Zillow Home Value Index (ZHVI) - http://www.zillow.com/research/data/
2000-2021

California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/
2000-2021

US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
2000-2021

Bureau of Labor Statistics: Consumer Price Index - http://data.bls.gov
2000-2021

US Census ZIP Code Tabulation Areas (ZCTAs) - https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
2020 Census Blocks

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Housing price estimates at the regional-, county-, city- and zip code-level come from analysis of individual home sales by Zillow based upon transaction records. Zillow Home Value Index (ZHVI) is a smoothed, seasonally adjusted measure of the typical home value and market changes across a given region and housing type. It reflects the typical value for homes in the 35th to 65th percentile range. ZHVI is computed from public record transaction data as reported by counties. All standard real estate transactions are included in this metric, including REO sales and auctions. Zillow makes a substantial effort to remove transactions not typically considered a standard sale. Examples of these include bank takeovers of foreclosed properties, title transfers after a death or divorce and non arms-length transactions. Zillow defines all homes as single-family residential, condominium and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that can be owned in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums in that the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Data is adjusted for inflation using Bureau of Labor Statistics metropolitan statistical area (MSA)-specific series. Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index (CPI) does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of the CPI itself.

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.

VITAL SIGNS INDICATOR
Home Prices (EC7)

FULL MEASURE NAME
Home Prices

LAST UPDATED
December 2022

DESCRIPTION
Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE
Zillow: Zillow Home Value Index (ZHVI) - http://www.zillow.com/research/data/
2000-2021

California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/
2000-2021

US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
2000-2021

Bureau of Labor Statistics: Consumer Price Index - http://data.bls.gov
2000-2021

US Census ZIP Code Tabulation Areas (ZCTAs) - https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
2020 Census Blocks

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Housing price estimates at the regional-, county-, city- and zip code-level come from analysis of individual home sales by Zillow based upon transaction records. Zillow Home Value Index (ZHVI) is a smoothed, seasonally adjusted measure of the typical home value and market changes across a given region and housing type. It reflects the typical value for homes in the 35th to 65th percentile range. ZHVI is computed from public record transaction data as reported by counties. All standard real estate transactions are included in this metric, including REO sales and auctions. Zillow makes a substantial effort to remove transactions not typically considered a standard sale. Examples of these include bank takeovers of foreclosed properties, title transfers after a death or divorce and non arms-length transactions. Zillow defines all homes as single-family residential, condominium and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that can be owned in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums in that the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Data is adjusted for inflation using Bureau of Labor Statistics metropolitan statistical area (MSA)-specific series. Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index (CPI) does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of the CPI itself.

The Community Development Block Grant (CDBG), and HOME Investments Partnership Program (HOME) are federal block grants distributed (via formula) to states and local governments. Recipients use the grant funds to carry out housing, economic development, and public improvement efforts that serve low, and moderate-income communities. This dataset denotes the primary locations, and relevant information of HOME program activities, and which HUD classifies using one of the following categories: Asset Acquisition - activity related to acquisition, including disposition, clearance and demolition, and clean-up of contaminated Sites/brownfields.Economic Development - activity related to economic development, including commercial or industrial rehab, commercial or industrial land acquisition, commercial or industrial construction, commercial or industrial infrastructure development, direct assistance to businesses, and micro-enterprise assistance.Housing - activity related to housing, including multifamily rehab, housing services, code enforcement, operation and repair of foreclosed property and public housing modernization.Public Improvements - activity related to public improvements, including senior centers, youth centers, parks, street improvements, water/sewer improvements, child care centers, fire stations, health centers, non-residential historic preservation, etc.Public Services - activity related to public services, including senior services, legal services, youth services, employment training, health services, homebuyer counseling, food banks, etc.Other - activity related to urban renewal completion, non-profit organization capacity building, and assistance to institutions of higher education.HOME Activity (point) - All HOME activities. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. Note that these data only include latitude and longitude coordinates and associated attributes for those addresses that can be geocoded to an interpolated point along a street segment, or to a ZIP+4 centroid location. While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. To learn more about the CDBG program visit: https://www.hud.gov/hudprograms/home-program, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_HOME Program Activity Date of Coverage: Up to 03/2025 Last Updated: 03/2025

Provides grantee information for the first round of Neighborhood Stabilization Program (NSP) formula funding (referred to as NSP1) allowed under Title III of the Housing and Economic Recovery Act (HERA) of 2008.The Neighborhood Stabilization Program (NSP) provides emergency assistance to state and local governments for the acquisition and redevelopment of foreclosed properties that might otherwise become sources of abandonment and blight within their communities.The Housing and Economic Recovery Act (HERA) of 2008, under Title III, provided a first round of formula funding to States and units of general local government (UGLG), and is referred to as NSP1. For the first round of funding HUD awarded grants to a total of 309 grantees including the 55 states, territories, and selected local governments to stabilize communities hardest hit by foreclosures and delinquencies. To learn more about the Neighborhood Stabilization Program (NSP) visit: https://www.hudexchange.info/programs/nsp/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_NSP1 Grantee Target AreasDate of Coverage: 12/2014

This dataset provides grantee information for the second round of Neighborhood Stabilization Program (NSP) formula funding (referred to as NSP2) authorized under the American Recovery and Reinvestment Act (ARRA). The NSP provides emergency assistance to state and local governments for the acquisition and redevelopment of foreclosed properties that might otherwise become sources of abandonment and blight within their communities. The ARRA provided a second round of funds in 2009. NSP2 provides grants to states, local governments, nonprofits and a consortium of nonprofit entities on a competitive basis. The Recovery Act also authorized HUD to establish NSP-TA (Technical Assistance), a $50 million allocation made available to national and local technical assistance providers to support NSP grantees. NSP2 grantee areas are comprised of the 2010 U.S. Census Tract boundaries.

Provides grantee information for the third round of Neighborhood Stabilization Program (NSP) formula funding (referred to as NSP3) authorized under Section 1497 of the Wall Street Reform and Consumer Protection Act of 2010.The Neighborhood Stabilization Program (NSP) provides emergency assistance to state and local governments for the acquisition and redevelopment of foreclosed properties that might otherwise become sources of abandonment and blight within their communities.Section 1497 of the Wall Street Reform and Consumer Protection Act of 2010, also known as the Dodd-Frank Act, provided a third round of funding in 2010. NSP3 provides grants to states, local governments, nonprofits and a consortium of nonprofit entities on a competitive basis.Grantee target area data provided through this service was created from user generated areas drawn by grantees using the NSP3 online map tool at available at https://www.huduser.org/NSP/NSP3.html. . To learn more about the Neighborhood Stabilization Program (NSP) visit: https://www.hudexchange.info/programs/nsp/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_NSP3 Grantee Target AreasDate of Coverage: 12/2014

This dataset consists of sixteen related feature classes. Each feature class represents a single year from 2007 to 2023. The feature classes contain points representing Sheriff's Office Foreclosure Sales in Dakota County. The Dakota County Sheriff's Office serves only as the auctioneer for foreclosed property sales in the County. The Sheriff's Office does not provide a list of upcoming sales.

Congress established the Neighborhood Stabilization Program (NSP) to allow for the purchase and redevelopment of foreclosed and neglected residential properties in an effort to stabilize communities suffering from foreclosures and abandonment. This service aggregates NSP activity at the 2010 tract-level geography of the U.S. Census.Please note that the data offered in this service is derived from an extract of HUD’s Office of Community Planning and Development (CPD) Disaster Recovery Grants Reporting (DRGR) System. Each observation in the raw DRGR extract is an address at which an NSP activity took place. If multiple activities took place at one address, that address would be in the database multiple times and would over-count NSP activity. This is likely to be the case if a grantee reports the same property under an acquisition activity and a rehab activity.Steps have been taken to mitigate the occurrences of over-counting through the standardization of addresses, the prioritization of activity types for those addresses where more than one activity took place, and then the removal of duplicate addresses. For example, if a grantee reported an acquisition and rehab activity at the same address, the rehab activity will be prioritized over the acquisition, and the acquisition will be removed.Likewise, the data will also over-count NSP activity if grantees enter an activity at a single address in multiple quarterly performance reports; much of this double counting will also be mitigated through the standardization and duplicate removal process. Conversely, if multiple units were assisted at a single address, that address would under-represent NSP activity. This is likely to be the case if a grantee reports a single address that represents a group of properties or a property with multiple units. To learn more about the Neighborhood Stabilization Program (NSP) visit: https://www.hudexchange.info/programs/nsp/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_NSP Activity by TractData Updated: 03/2020