44 datasets found
  1. Mortgage delinquency rate in the U.S. 2000-2025, by quarter

    • statista.com
    • tokrwards.com
    Updated Sep 8, 2025
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    Statista (2025). Mortgage delinquency rate in the U.S. 2000-2025, by quarter [Dataset]. https://www.statista.com/statistics/205959/us-mortage-delinquency-rates-since-1990/
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    Dataset updated
    Sep 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  2. Mortgage Rates Across Surprise, Butler County, Nebraska

    • ownwell.com
    Updated Mar 1, 2025
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    Ownwell (2025). Mortgage Rates Across Surprise, Butler County, Nebraska [Dataset]. https://www.ownwell.com/trends/nebraska/butler-county/surprise
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    Dataset updated
    Mar 1, 2025
    Dataset authored and provided by
    Ownwell
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    Butler County, Nebraska, Surprise
    Description

    The table below showcases the 10th, 25th, 50th, 75th, and 90th percentiles of mortgage rates for each zip code in Surprise, Nebraska. It's important to understand that mortgage rates can vary greatly and can change yearly.

  3. Mortgage delinquency rate for subprime conventional loans in the U.S....

    • statista.com
    Updated Dec 7, 2024
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    Statista (2024). Mortgage delinquency rate for subprime conventional loans in the U.S. 2000-2016 [Dataset]. https://www.statista.com/statistics/205970/delinquency-rates-on-us-subprime-conventional-loans-since-2000/
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    Dataset updated
    Dec 7, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic presents the mortgage delinquency rates for subprime conventional loans in the United States from 2000 to 2016. The mortgage delinquency rate for subprime conventional loans in the United States amounted to 14.9 percent in 2016.

  4. F

    Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic...

    • fred.stlouisfed.org
    json
    Updated Aug 18, 2025
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    (2025). Delinquency Rate on Single-Family Residential Mortgages, Booked in Domestic Offices, All Commercial Banks [Dataset]. https://fred.stlouisfed.org/series/DRSFRMACBS
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    jsonAvailable download formats
    Dataset updated
    Aug 18, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    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.

  5. T

    United States 30-Year Mortgage Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 2, 2025
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    TRADING ECONOMICS (2025). United States 30-Year Mortgage Rate [Dataset]. https://tradingeconomics.com/united-states/30-year-mortgage-rate
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Oct 2, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Apr 1, 1971 - Oct 2, 2025
    Area covered
    United States
    Description

    30 Year Mortgage Rate in the United States increased to 6.34 percent in October 2 from 6.30 percent in the previous week. This dataset includes a chart with historical data for the United States 30 Year Mortgage Rate.

  6. Foreclosure rates on subprime conventional loans in the U.S. 2000-2016

    • statista.com
    • tokrwards.com
    Updated Jul 22, 2025
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    Statista (2025). Foreclosure rates on subprime conventional loans in the U.S. 2000-2016 [Dataset]. https://www.statista.com/statistics/206014/us-foreclosure-rates-on-subprime-conventional-loans-since-2000/
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    Dataset updated
    Jul 22, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic shows the foreclosure rates of subprime conventional loans in the United States from 2000 to 2016. In 2016, 7.2 percent of subprime conventional loans were in foreclosure.

  7. Real Estate Loans & Collateralized Debt in the US - Market Research Report...

    • ibisworld.com
    Updated Sep 25, 2025
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    IBISWorld (2025). Real Estate Loans & Collateralized Debt in the US - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/united-states/market-research-reports/real-estate-loans-collateralized-debt-industry/
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    Dataset updated
    Sep 25, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2015 - 2030
    Area covered
    United States
    Description

    The industry is composed of non-depository institutions that conduct primary and secondary market lending. Operators in this industry include government agencies in addition to non-agency issuers of mortgage-related securities. Through 2025, rising per capita disposable income and low levels of unemployment helped fuel the increase in primary and secondary market sales of collateralized debt. Nonetheless, due to the sharp contraction in economic activity at the onset of the period, revenue gains were limited, but climbed in the latter part of the period as the economy has normalized. Interest rates climbed significantly to tackle significant inflationary pressures, which increased borrowing costs, hindering loan volumes but increasing interest income for each loan. However, the Fed cut interest rates in 2024 and is anticipated to cut rates in the latter part of the current year, reducing borrowing costs and providing a boost to loan volumes. Overall, these trends, along with volatility in the real estate market, have caused revenue to slump at a CAGR of 1.3% to $488.9 billion over the past five years, including an expected decline of 0.1% in 2025 alone. The high interest rate environment has hindered real estate loan demand but increased interest income, boosting profit to 15.6% of revenue in the current year. Higher access to credit and higher disposable income have fueled primary market lending over much of the period, increasing the variety and volume of loans to be securitized and sold in secondary markets. An additional boon for institutions has been an increase in interest rates, which raised interest income as the spread between short- and long-term interest rates increased. These macroeconomic factors, combined with changing risk appetite and regulation in the secondary markets, have resurrected collateralized debt trading since the middle of the period. Although institutions are poised to benefit from strong economic growth, inflationary pressures easing and the decline in the 30-year conventional mortgage rate, the rate of homeownership is still expected to fall but at a slower pace compared to the current period. Shaky demand from commercial banking and uncertainty surrounding inflationary pressures will influence institutions' decisions on whether or not to sell mortgage-backed securities and commercial loans to secondary markets. These trends are expected to cause revenue to decline at a CAGR of 1.0% to $465.4 billion over the five years to 2030.

  8. Great Recession: delinquency rate by loan type in the U.S. 2007-2010

    • statista.com
    • tokrwards.com
    • +1more
    Updated Sep 2, 2024
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    Statista (2024). Great Recession: delinquency rate by loan type in the U.S. 2007-2010 [Dataset]. https://www.statista.com/statistics/1342448/global-financial-crisis-us-economic-indicators/
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    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2007 - 2012
    Area covered
    United States
    Description

    The Global Financial Crisis of 2008-09 was a period of severe macroeconomic instability for the United States and the global economy more generally. The crisis was precipitated by the collapse of a number of financial institutions who were deeply involved in the U.S. mortgage market and associated credit markets. Beginning in the Summer of 2007, a number of banks began to report issues with increasing mortgage delinquencies and the problem of not being able to accurately price derivatives contracts which were based on bundles of these U.S. residential mortgages. By the end of 2008, U.S. financial institutions had begun to fail due to their exposure to the housing market, leading to one of the deepest recessions in the history of the United States and to extensive government bailouts of the financial sector.

    Subprime and the collapse of the U.S. mortgage market

    The early 2000s had seen explosive growth in the U.S. mortgage market, as credit became cheaper due to the Federal Reserve's decision to lower interest rates in the aftermath of the 2001 'Dot Com' Crash, as well as because of the increasing globalization of financial flows which directed funds into U.S. financial markets. Lower mortgage rates gave incentive to financial institutions to begin lending to riskier borrowers, using so-called 'subprime' loans. These were loans to borrowers with poor credit scores, who would not have met the requirements for a conventional mortgage loan. In order to hedge against the risk of these riskier loans, financial institutions began to use complex financial instruments known as derivatives, which bundled mortgage loans together and allowed the risk of default to be sold on to willing investors. This practice was supposed to remove the risk from these loans, by effectively allowing credit institutions to buy insurance against delinquencies. Due to the fraudulent practices of credit ratings agencies, however, the price of these contacts did not reflect the real risk of the loans involved. As the reality of the inability of the borrowers to repay began to kick in during 2007, the financial markets which traded these derivatives came under increasing stress and eventually led to a 'sudden stop' in trading and credit intermediation during 2008.

    Market Panic and The Great Recession

    As borrowers failed to make repayments, this had a knock-on effect among financial institutions who were highly leveraged with financial instruments based on the mortgage market. Lehman Brothers, one of the world's largest investment banks, failed on September 15th 2008, causing widespread panic in financial markets. Due to the fear of an unprecedented collapse in the financial sector which would have untold consequences for the wider economy, the U.S. government and central bank, The Fed, intervened the following day to bailout the United States' largest insurance company, AIG, and to backstop financial markets. The crisis prompted a deep recession, known colloquially as The Great Recession, drawing parallels between this period and The Great Depression. The collapse of credit intermediation in the economy lead to further issues in the real economy, as business were increasingly unable to pay back loans and were forced to lay off staff, driving unemployment to a high of almost 10 percent in 2010. While there has been criticism of the U.S. government's actions to bailout the financial institutions involved, the actions of the government and the Fed are seen by many as having prevented the crisis from spiraling into a depression of the magnitude of The Great Depression.

  9. F

    30-Year Fixed Rate FHA Mortgage Index

    • fred.stlouisfed.org
    json
    Updated Oct 8, 2025
    + more versions
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    (2025). 30-Year Fixed Rate FHA Mortgage Index [Dataset]. https://fred.stlouisfed.org/series/OBMMIFHA30YF
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    jsonAvailable download formats
    Dataset updated
    Oct 8, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Description

    Graph and download economic data for 30-Year Fixed Rate FHA Mortgage Index (OBMMIFHA30YF) from 2017-01-03 to 2025-10-07 about FHA, 30-year, mortgage, fixed, rate, indexes, and USA.

  10. F

    Bank Prime Loan Rate Changes: Historical Dates of Changes and Rates

    • fred.stlouisfed.org
    json
    Updated Sep 24, 2025
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    (2025). Bank Prime Loan Rate Changes: Historical Dates of Changes and Rates [Dataset]. https://fred.stlouisfed.org/series/PRIME
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    jsonAvailable download formats
    Dataset updated
    Sep 24, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Bank Prime Loan Rate Changes: Historical Dates of Changes and Rates (PRIME) from 1955-08-04 to 2025-09-17 about prime, loans, interest rate, banks, interest, depository institutions, rate, and USA.

  11. g

    Federal Reserve Bank of New York, State Level Subprime Loan Characteristics,...

    • geocommons.com
    Updated Jun 3, 2008
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    Brendan (2008). Federal Reserve Bank of New York, State Level Subprime Loan Characteristics, USA, January 2008 [Dataset]. http://geocommons.com/search.html
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    Dataset updated
    Jun 3, 2008
    Dataset provided by
    Federal Reserve Bank of New York
    Brendan
    Description

    This dataset displays characteristics regarding state level sub prime loans. There are over 50 characteristics regarding a wide range of loan, housing, ant mortgage information. Included are the number of sub prime loans, foreclosure, and the number of ARM loans are some of the highlights. This data was made available by the Federal Reserve Bank of New York. Source: FirstAmerican CoreLogic, LoanPerformance Data, U.S. Census Bureau, and Federal Reserve Bank of New York (a) Statistics calculated on first-lien and active (includes REO) loans. (b) Statistics calculated on first-lien, owner-occupied, active (includes REO) loans. (c) 'Prepayment penalty in force' denotes that the loan age is less than the prepayment penalty term. (d) Statistics calculated on first-lien, owner-occupied, active (includes REO), variable rate loans.

  12. Mortgage debt service ratio of households in the U.S. 1980-2024, by quarter

    • statista.com
    Updated May 14, 2025
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    Statista (2025). Mortgage debt service ratio of households in the U.S. 1980-2024, by quarter [Dataset]. https://www.statista.com/statistics/1400044/mortgage-debt-service-ratio/
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    Dataset updated
    May 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The mortgage debt service ratio in the United States remained fairly stable in 2024, after recovering from a dip in 2020 and 2021. The ratio measures the mortgage debt service payments as a percentage of disposable personal income during a specific quarter and shows the financial burden placed on households by mortgage borrowing. In the fourth quarter of 2024, the total required mortgage payments amounted to approximately **** percent of disposable personal income. This was substantially lower than the spike recorded during the subprime mortgage crisis.

  13. Share of U.S. loans in foreclosure processes 2000-2025, by quarter

    • statista.com
    Updated Sep 1, 2025
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    Statista (2025). Share of U.S. loans in foreclosure processes 2000-2025, by quarter [Dataset]. https://www.statista.com/statistics/205983/total-loans-in-foreclosure-process-in-the-us-since-1990/
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    Dataset updated
    Sep 1, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  14. o

    Data and Code for "Borrowing and Spending in the Money: Debt Substitution...

    • openicpsr.org
    delimited
    Updated May 12, 2025
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    Elliot Anenberg; Tess Scharlemann; Eileen van Straelen (2025). Data and Code for "Borrowing and Spending in the Money: Debt Substitution and the Cash-out Refinance Channel of Monetary Policy" [Dataset]. http://doi.org/10.3886/E229322V1
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    delimitedAvailable download formats
    Dataset updated
    May 12, 2025
    Dataset provided by
    American Economic Association
    Authors
    Elliot Anenberg; Tess Scharlemann; Eileen van Straelen
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    We show that the strong negative effect of higher mortgage rates on cash-out refinancing reflects substitution into other borrowing products, not large changes in total new household borrowing. We exploit plausibly exogenous changes in interest rates due to unconventional monetary policy surprises to show that changes in cash-out and other borrowing are roughly offsetting. The elasticity of new household borrowing with respect to mortgage rates is low and varies little with the borrower's outstanding mortgage rate. Our results suggest that the cash-out refinance channel of unconventional monetary policy is weak and not path-dependent.

  15. H

    Data from: "Racial and Spatial Targeting: Segregation and Subprime Lending...

    • dataverse.harvard.edu
    Updated Mar 9, 2015
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    Jackelyn Hwang; Michael Hankinson; Kreg Steven Brown (2015). "Racial and Spatial Targeting: Segregation and Subprime Lending within and across Metropolitan Areas [Dataset]. http://doi.org/10.7910/DVN/26653
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 9, 2015
    Dataset provided by
    Harvard Dataverse
    Authors
    Jackelyn Hwang; Michael Hankinson; Kreg Steven Brown
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Recent studies find that high levels of black-white segregation increased rates of foreclosures and subprime lending across U.S. metropolitan areas during the housing crisis. These studies speculate that segregation created distinct geographic markets that enabled subprime lenders and brokers to leverage the spatial proximity of minorities to disproportionately target minority neighborhoods. Yet, the studies do not explicitly test whether the concentration of subprime loans in minority neighborhoods varied by segregation levels. We address this shortcoming by integrating neighborhood-level data and spatial measures of segregation to examine the relationship between segregation and subprime lending across the 100 largest U.S. metropolitan areas. Controlling for alternative explanations of the housing crisis, we find that segregation is strongly associated with higher concentrations of subprime loans in clusters of minority census tracts but find no evidence of unequal lending patterns when we examine minority census tracts in an aspatial way. Moreover, residents of minority census tracts in segregated metropolitan areas had higher likelihoods of receiving subprime loans than their counterparts in less segregated metropolitan areas. Our findings demonstrate that segregation played a pivotal role in the housing crisis by creating relatively larger areas of concentrated minorities into which subprime loans could be efficiently and effectively channeled. These results are consistent with existing but untested theories on the relationship between segregation and the housing crisis in metropolitan area s.

  16. T

    United States Mortgage Originations

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Mar 15, 2025
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    TRADING ECONOMICS (2025). United States Mortgage Originations [Dataset]. https://tradingeconomics.com/united-states/mortgage-originations
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    json, csv, xml, excelAvailable download formats
    Dataset updated
    Mar 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 31, 2003 - Jun 30, 2025
    Area covered
    United States
    Description

    Mortgage Originations in the United States increased to 458.28 Billion USD in the second quarter of 2025 from 425.63 Billion USD in the first quarter of 2025. This dataset includes a chart with historical data for the United States Mortgage Originations.

  17. Home mortgage debt of households and nonprofit organizations U.S. 2012-2025

    • statista.com
    • tokrwards.com
    Updated Jul 29, 2025
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    Statista (2025). Home mortgage debt of households and nonprofit organizations U.S. 2012-2025 [Dataset]. https://www.statista.com/statistics/248289/home-mortgage-sector-debt-outstanding-in-the-united-states/
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    Dataset updated
    Jul 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The home mortgage debt of households and nonprofit organizations amounted to approximately 13.46 trillion U.S. dollars in the first quarter of 2025. Mortgage debt has been growing steadily since 2014, when it was less than ten billion U.S. dollars and has increased at a faster rate since the beginning of the coronavirus pandemic due to the housing market boom. Home mortgage sector in the United States Home mortgage sector debt in the United States has been steadily growing in recent years and is beginning to come out of a period of great difficulty and problems presented to it by the economic crisis of 2008. For the previous generations in the United States, the real estate market was quite stable. Financial institutions were extending credit to millions of families and allowed them to achieve ownership of their own homes. The growth of the subprime mortgages and, which went some way to contributing to the record of the highest US homeownership rate since records began, meant that many families deemed to be not quite creditworthy were provided the opportunity to purchase homes. The rate of home mortgage sector debt rose in the United States as a direct result of the less stringent controls that resulted from the vetted and extended terms from which loans originated. There was a great deal more liquidity in the market, which allowed greater access to new mortgages. The practice of packaging mortgages into securities, and their subsequent sale into the secondary market as a way of shifting risk, was to be a major factor in the formation of the American housing bubble, one of the greatest contributing factors to the global financial meltdown of 2008.

  18. M

    Mortgage-Backed Security Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Dec 30, 2024
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    Data Insights Market (2024). Mortgage-Backed Security Report [Dataset]. https://www.datainsightsmarket.com/reports/mortgage-backed-security-1366822
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    doc, ppt, pdfAvailable download formats
    Dataset updated
    Dec 30, 2024
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global mortgage-backed security market is projected to grow from USD XXX million in 2023 to USD XX million by 2033, exhibiting a CAGR of XX% between 2023 and 2033. The market growth is primarily attributed to the increasing demand for home loans and growing investment in the residential real estate sector. Furthermore, government initiatives to promote homeownership and the development of innovative mortgage products are expected to drive market expansion. Key market drivers include the rising population, increasing urbanization, and growing disposable income, which are contributing to the increased demand for housing. Additionally, favorable government policies, such as low interest rates, tax incentives, and mortgage insurance programs, are encouraging homeownership and stimulating market growth. Moreover, the increasing popularity of non-traditional mortgage products, such as Alt-A loans and subprime mortgages, is broadening the market's reach and catering to a wider range of borrowers.

  19. A

    Auto Finance Service Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Jul 16, 2025
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    Market Report Analytics (2025). Auto Finance Service Report [Dataset]. https://www.marketreportanalytics.com/reports/auto-finance-service-131725
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    ppt, pdf, docAvailable download formats
    Dataset updated
    Jul 16, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The auto finance services market, currently valued at $278.03 billion (2025 estimated), is projected to experience robust growth, exhibiting a Compound Annual Growth Rate (CAGR) of 7.2% from 2025 to 2033. This expansion is fueled by several key factors. Increased consumer demand for new and used vehicles, coupled with the rising popularity of financing options like auto loans and leasing, is a primary driver. Furthermore, the proliferation of online lending platforms and the development of sophisticated credit scoring models have streamlined the borrowing process, making auto financing more accessible to a wider range of consumers. The market is also witnessing an uptick in the adoption of innovative financing products tailored to specific customer segments, including subprime borrowers and those seeking environmentally friendly vehicles. Competition among established players like Ally Financial, Wells Fargo, Chase, Capital One, and major auto manufacturers such as Toyota, Ford, Nissan, and Honda, is intensifying, resulting in increased innovation and improved customer service. However, potential headwinds exist. Fluctuations in interest rates and economic downturns can significantly impact consumer borrowing behavior, potentially dampening market growth. Rising inflation and increased regulatory scrutiny pose additional challenges. To mitigate risks, auto finance companies are increasingly focusing on developing robust risk management strategies, enhancing data analytics capabilities, and diversifying their product offerings to cater to evolving consumer preferences. The increasing emphasis on responsible lending practices and stricter regulatory compliance requirements also play a crucial role in shaping the market's trajectory. Segmentation strategies that target specific demographics and risk profiles are becoming more critical to success.

  20. Subprime Auto Loans in the US - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Aug 7, 2025
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    IBISWorld (2025). Subprime Auto Loans in the US - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/united-states/market-research-reports/subprime-auto-loans-industry/
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    Dataset updated
    Aug 7, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2015 - 2030
    Description

    Companies in the Subprime Auto Loans industry have contended with rising interest rates and significant economic volatility. Several small, specialized creditors have been pushed to bankruptcy because of growing subprime auto loan delinquencies. According to Fitch Ratings Inc., the index of the 60-day delinquency rate of subprime auto loans has climbed significantly over the past five years. In June 2025, the 60-day delinquency rate of subprime auto loans was 6.31% compared to 5.62% in June of 2024 (latest data available). As a result, many businesses have exited the industry. However, the Fed is anticipated to cut interest rates in the latter part of the current period which will reduce borrowing costs and positively impact the industry. As the economy has stabilized and economic factors have improved following disruptions at the onset of the period, the industry has benefited. For example, employment levels, access to credit and rising per capita disposable income have risen, enabling consumers to better afford car loans for used and new cars. Overall, industry revenue has climbed at a CAGR of 4.6% to $19.3 billion over the five years to 2025, including an expected increase of 0.5% in the current year alone. Industry profit has also grown and will comprise 20.4% of revenue in the current year. Despite the potential payout of subprime interest rates, many companies in the Auto Leasing, Loans and Sales Financing industry (IBISWorld report 52222) still chose not to expand the number of high-risk loans in their portfolios. Instead, they have sought super-prime and prime borrowers during heightened delinquency rates. Moreover, many primary auto dealers have begun reducing their auto financing divisions to eliminate high-risk borrowers. Moving forward, industry revenue will hike due to a rise in access to credit and consumer confidence, which will accelerate vehicle sales. Also, interest rates are expected to come down as the FED continues to monitor inflation and reduce rates accordingly. In addition, some consumers will seek to lock in financing deals as interest rates are cut. Overall, industry revenue is forecast to push up at a CAGR of 1.4% over the five years to 2030.

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Statista (2025). Mortgage delinquency rate in the U.S. 2000-2025, by quarter [Dataset]. https://www.statista.com/statistics/205959/us-mortage-delinquency-rates-since-1990/
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Mortgage delinquency rate in the U.S. 2000-2025, by quarter

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3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Sep 8, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

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.

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