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Mortgage Application in the United States decreased by 3.80 percent in the week ending July 25 of 2025 over the previous week. This dataset provides - United States MBA Mortgage Applications - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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Mortgage Originations in the United States decreased to 425.63 Billion USD in the first quarter of 2025 from 465.35 Billion USD in the fourth quarter of 2024. This dataset includes a chart with historical data for the United States Mortgage Originations.
Mortgage Assignment & Release Data refers to information related to the assignment and release of mortgage loans. It provides valuable insights into the transfer of mortgage ownership from one party to another and the subsequent release of the mortgage lien. This data can be essential for various industries, including banking, real estate, legal services, and mortgage lending, enabling them to make informed decisions and mitigate risks associated with mortgage transactions.
What is Assignment and Release Data?
Assignment Data – Assignment data pertains to the transfer of ownership rights of a mortgage loan from one entity to another. This transfer typically occurs when a lender sells or transfers a mortgage loan to another financial institution, such as a bank, credit union, or mortgage-backed security issuer. Assignment data includes information such as the parties involved, the effective date of the assignment, and any relevant terms or conditions.
Release Data – Release data involves the release or satisfaction of a mortgage lien on a property. When a mortgage loan is fully paid off or otherwise satisfied, the lender releases the mortgage lien, allowing the property owner to have clear title. Release data provides details about the release, including the date of release, the parties involved, and any legal documentation associated with the release.
Assignment & Release Property Details:
Our Home Ownership Mortgage Database is rebuilt from every two months and contains information on over 50+ million US Homeowners. The data is collected from county recorder and assessor offices.
The file is processed via National Change of Address (NCOA) to ensure deliverability. Additionally, the data is passed against suppression files to eliminate consumers or telephone numbers as appropriate such as Decease File, State Attorney General (SAG) data, the Direct Marketing Association's (DMA) do-not-mail and do-not-call lists, and the national FTC do-not-call file.
Selections include mortgage loan and property attributes along with household, individual and neighborhood demographics.
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30 Year Mortgage Rate in the United States decreased to 6.72 percent in July 31 from 6.74 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.
Our US Home Ownership Data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.
Our comprehensive data enrichment solution includes various data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences. 1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc. 2. Demographics - Gender, Age Group, Marital Status, Language etc. 3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc 4. Persona - Consumer type, Communication preferences, Family type, etc 5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc. 6. Household - Number of Children, Number of Adults, IP Address, etc. 7. Behaviours - Brand Affinity, App Usage, Web Browsing etc. 8. Firmographics - Industry, Company, Occupation, Revenue, etc 9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc. 10. Auto - Car Make, Model, Type, Year, etc. 11. Housing - Home type, Home value, Renter/Owner, Year Built etc.
Consumer Graph Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:
Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).
Consumer Graph Use Cases: 360-Degree Customer View: Get a comprehensive image of customers by the means of internal and external data aggregation. Data Enrichment: Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity. Advertising & Marketing: Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.
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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 Q1 2025 about domestic offices, delinquencies, 1-unit structures, mortgage, family, residential, commercial, domestic, banks, depository institutions, rate, 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 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.
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Fixed 30-year mortgage rates in the United States averaged 6.83 percent in the week ending July 25 of 2025. This dataset provides the latest reported value for - United States MBA 30-Yr Mortgage Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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Average Mortgage Size in the United States decreased to 376.08 Thousand USD in June 30 from 379.21 Thousand USD in the previous week. This dataset includes a chart with historical data for the United States Average Mortgage Size.
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Graph and download economic data for Federal Government; Total Mortgages Held by FHA; Asset, Level (BOGZ1FL313065035Q) from Q4 1945 to Q1 2025 about FHA, mortgage, federal, assets, government, and USA.
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United States Employment: NF: FA: Mortgages & Non Mortgage Loan Broker data was reported at 91.300 Person th in May 2018. This records a decrease from the previous number of 91.900 Person th for Apr 2018. United States Employment: NF: FA: Mortgages & Non Mortgage Loan Broker data is updated monthly, averaging 69.400 Person th from Jan 1990 (Median) to May 2018, with 341 observations. The data reached an all-time high of 148.200 Person th in Apr 2006 and a record low of 28.700 Person th in Feb 1991. United States Employment: NF: FA: Mortgages & Non Mortgage Loan Broker data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G024: Current Employment Statistics Survey: Employment: Non Farm.
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MBA Mortgage Market Index in the United States decreased to 245.70 points in July 25 from 255.50 points in the previous week. This dataset includes a chart with historical data for the United States MBA Mortgage Market Index.
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This data collection is part of the American Housing Metropolitan Survey (AHS-MS, or "metro") which is conducted in odd-numbered years. It cycles through a set of 21 metropolitan areas, surveying each one about once every six years. The metro survey, like the national survey, is longitudinal. This particular survey provides information on the characteristics of a New Orleans metropolitan sample of housing units, including apartments, single-family homes, mobile homes, and vacant housing units in 2009. The data are presented in eight separate parts: Part 1, Home Improvement Record, Part 2, Journey to Work Record, Part 3, Mortgages Recorded, Part 4, Housing Unit Record (Main Record), Recodes (One Record per Housing Unit), and Weights, Part 5, Manager and Owner of Rental Units Record, Part 6, Person Record, Part 7, High Burden Unit Record, and Part 8, Recent Mover Groups Record. Part 1 data include questions about upgrades and remodeling, cost of alterations and repairs, as well as the household member who performed the alteration/repair. Part 2 data include journey to work or commuting information, such as method of transportation to work, length of trip, and miles traveled to work. Additional information collected covers number of hours worked at home, number of days worked at home, average time respondent leaves for work in the morning or evening, whether respondent drives to work alone or with others, and a few other questions pertaining to self-employment and work schedule. Part 3 data include mortgage information, such as type of mortgage obtained by respondent, amount and term of mortgages, as well as years needed to pay them off. Other items asked include monthly payment amount, reason mortgage was taken out, and who provided the mortgage. Part 4 data include household-level information, including demographic information, such as age, sex, race, marital status, income, and relationship to householder. The following topics are also included: data recodes, unit characteristics, and weighting information. Part 5 data include information pertaining to owners of rental properties and whether the owner/resident manager lives on-site. Part 6 data include individual person level information, in which respondents were queried on basic demographic information (i.e. age, sex, race, marital status, income, and relationship to householder), as well as if they worked at all last week, month and year moved into residence, and their ability to perform everyday tasks and whether they have difficulty hearing, seeing, and concentrating or remembering things. Part 7 data include verification of income to cost when the ratio of income to cost is outside of certain tolerances. Respondents were asked whether they receive help or assistance with grocery bills, clothing and transportation expenses, child care payments, medical and utility bills, as well as with rent payments. Part 8 data include recent mover information, such as how many people were living in last unit before move, whether last residence was a condo or a co-op, as well as whether this residence was outside of the United States.
U.S. National Deed and Mortgage Data is made up of millions of data points sourced from public records containing information about property ownership, mortgages, and loan originations.
Deed & Mortgage Data includes:
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Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2018-2022 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Beginning in data year 2020, categories were added to Mortgage Status to account for the variety of mortgage arrangements that may exist. See “American Community Survey Subject Definitions” for more information on Mortgage Status..The 2018-2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.
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US Mortgage/Loan Brokers Market Analysis The US mortgage/loan brokers market is substantial, valued at USD XX million in 2025 with a projected CAGR of 5.00% during 2025-2033. This growth is attributed to factors such as rising demand for home ownership, increasing home values, and low interest rates. The market is segmented by component (products, services), enterprise (large, small, medium-sized), application (home loans, commercial loans, etc.), end-user (business, individuals), and region. Prominent players include Quicken Loans, Wells Fargo, and Caliber Home Loans. Market Drivers and Trends The growth of the US mortgage/loan brokers market is driven by several factors, including the increasing demand for residential and commercial construction, government incentives for home ownership, and the availability of various loan options. Additionally, technological advancements, such as online loan applications and mobile banking, are simplifying the loan application process. However, rising interest rates and stricter lending regulations pose potential challenges to the market's growth. Nonetheless, the growing need for mortgages and the increasing complexity of loan processes are expected to drive the market's expansion in the coming years. Recent developments include: November 2022: A digital home equity line of credit was introduced by loanDepot, one of the country's biggest non-bank retail mortgage lenders, against the backdrop of inflation and rising consumer debt., October 2022: Pennymac Financial Services launched POWER+, its next generation broker technology platform. Brokers will now have more speed and control over the mortgage process to deliver an exceptional experience to their customers and referral partners.. Notable trends are: Adoption of the New Technologies Driving the Market.
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United States Mortgage Debt Outstanding: Effective Interest Rate data was reported at 3.799 % in Mar 2020. This records a decrease from the previous number of 3.872 % for Dec 2019. United States Mortgage Debt Outstanding: Effective Interest Rate data is updated quarterly, averaging 7.677 % from Mar 1977 (Median) to Mar 2020, with 173 observations. The data reached an all-time high of 11.449 % in Mar 1985 and a record low of 3.750 % in Dec 2017. United States Mortgage Debt Outstanding: Effective Interest Rate data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s United States – Table US.KB025: Mortgage Interest Paid. [COVID-19-IMPACT]
The FHA Office of Housing last conducted a series of mortgage loan sales under the Single Family Loan Sale (SFLS) Initiative in 2016. The current sales structure consisted of whole loan, competitive auctions, offering for purchase defaulted single family mortgages provided by FHA-approved loan servicers. The loans sold contained specified representations and warranties and may be sold with post-sale restrictions and/or reporting requirements. FHA sold loans in large national pools, as well as loan pools in designated geographical areas that are aimed at a neighborhood stabilization outcome (“NSO pools”).
The Federal Housing Administration's HECM program is the only government-insured reverse mortgage program. The HECM program guarantees that the lender will meet its payment obligations to the homeowner, limits the borrower's loan origination costs, and insures full repayment of the loan balance to the lender up to the maximum claim amount. The loan amount is based on borrower age, home value, and current interest rates. The HECM data files provide loan-level records that will enable interested parties to explore issues regarding downpayment assistance provided to homebuyers utilizing HECM insured mortgage financing.
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Mortgage Application in the United States decreased by 3.80 percent in the week ending July 25 of 2025 over the previous week. This dataset provides - United States MBA Mortgage Applications - actual values, historical data, forecast, chart, statistics, economic calendar and news.