21 datasets found
  1. Quarterly credit card debt in the U.S. 2010-2025

    • statista.com
    Updated Jun 4, 2025
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    Statista (2025). Quarterly credit card debt in the U.S. 2010-2025 [Dataset]. https://www.statista.com/statistics/245405/total-credit-card-debt-in-the-united-states/
    Explore at:
    Dataset updated
    Jun 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Credit card debt in the United States has been growing at a fast pace between 2021 and 2025. In the fourth quarter of 2024, the overall amount of credit card debt reached its highest value throughout the timeline considered here. COVID-19 had a big impact on the indebtedness of Americans, as credit card debt decreased from *** billion U.S. dollars in the last quarter of 2019 to *** billion U.S. dollars in the first quarter of 2021. What portion of Americans use credit cards? A substantial portion of Americans had at least one credit card in 2025. That year, the penetration rate of credit cards in the United States was ** percent. This number increased by nearly seven percentage points since 2014. The primary factors behind the high utilization of credit cards in the United States are a prevalent culture of convenience, a wide range of reward schemes, and consumer preferences for postponed payments. Which companies dominate the credit card issuing market? In 2024, the leading credit card issuers in the U.S. by volume were JPMorgan Chase & Co. and American Express. Both firms recorded transactions worth over one trillion U.S. dollars that year. Citi and Capital One were the next banks in that ranking, with the transactions made with their credit cards amounting to over half a trillion U.S. dollars that year. Those industry giants, along with other prominent brand names in the industry such as Bank of America, Synchrony Financial, Wells Fargo, and others, dominate the credit card market. Due to their extensive customer base, appealing rewards, and competitive offerings, they have gained a significant market share, making them the preferred choice for consumers.

  2. T

    United States Debt Balance Credit Cards

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Debt Balance Credit Cards [Dataset]. https://tradingeconomics.com/united-states/debt-balance-credit-cards
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    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

    Debt Balance Credit Cards in the United States increased to 1.21 Trillion USD in the second quarter of 2025 from 1.18 Trillion USD in the first quarter of 2025. This dataset includes a chart with historical data for the United States Debt Balance Credit Cards.

  3. U

    United States Household Debt

    • ceicdata.com
    Updated Feb 27, 2025
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    CEICdata.com (2025). United States Household Debt [Dataset]. https://www.ceicdata.com/en/indicator/united-states/household-debt
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    Dataset updated
    Feb 27, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    United States
    Description

    Key information about United States Household Debt

    • United States Household Debt reached 18,036.0 USD bn in Dec 2024, compared with the reported number of 17,943.0 USD bn in the previous quarter
    • US Household Debt: USD mn data is updated quarterly, available from Mar 1999 to Dec 2024
    • The data reached an all-time high of 18,036.0 USD bn in Dec 2024 and a record low of 4,540.0 USD bn in Mar 1999

    Federal Reserve Board of New York provides quarterly Household Debt in USD. Household Debt includes Mortgages, Home Equity Revolving, Auto Loans, Bankcards, Student Loans and Others.


    Further information about United States Household Debt

    • In the latest reports, United States Household Debt accounted for 61.7 % of the country's Nominal GDP in Dec 2024
    • Money Supply M2 in United States increased 21,533.8 USD bn YoY in Dec 2024
    • United States Foreign Exchange Reserves was measured at 34.9 USD bn in Dec 2024
    • The Foreign Exchange Reserves equaled 0.1 Months of Import in Dec 2024
    • United States Domestic Credit reached 30,648.3 USD bn in Mar 2024, representing an drop of 0.3 % YoY

  4. T

    United States Consumer Credit Change

    • tradingeconomics.com
    • fr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 6, 2025
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    TRADING ECONOMICS (2025). United States Consumer Credit Change [Dataset]. https://tradingeconomics.com/united-states/consumer-credit
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset updated
    Jun 6, 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
    Feb 28, 1943 - Jun 30, 2025
    Area covered
    United States
    Description

    Consumer Credit in the United States increased to 7.37 USD Billion in June from 5.13 USD Billion in May of 2025. This dataset provides the latest reported value for - United States Consumer Credit Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  5. f

    Dataset summary for various data sources used in the study.

    • plos.figshare.com
    xls
    Updated May 30, 2023
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    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh (2023). Dataset summary for various data sources used in the study. [Dataset]. http://doi.org/10.1371/journal.pone.0191863.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh
    License

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

    Description

    Dataset summary for various data sources used in the study.

  6. f

    Transaction based features.

    • figshare.com
    xls
    Updated Jun 1, 2023
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    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh (2023). Transaction based features. [Dataset]. http://doi.org/10.1371/journal.pone.0191863.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh
    License

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

    Description

    Transaction based features.

  7. T

    United States Private Debt to GDP

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated Dec 15, 2024
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    TRADING ECONOMICS (2024). United States Private Debt to GDP [Dataset]. https://tradingeconomics.com/united-states/private-debt-to-gdp
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    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Dec 15, 2024
    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
    Dec 31, 1995 - Dec 31, 2024
    Area covered
    United States
    Description

    Private Debt to GDP in the United States decreased to 142 percent in 2024 from 147.50 percent in 2023. United States Private Debt to GDP - values, historical data, forecasts and news - updated on September of 2025.

  8. f

    Demographic based features.

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
    + more versions
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    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh (2023). Demographic based features. [Dataset]. http://doi.org/10.1371/journal.pone.0191863.t006
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh
    License

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

    Description

    Demographic based features.

  9. T

    United States Debt Balance Auto Loans

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Debt Balance Auto Loans [Dataset]. https://tradingeconomics.com/united-states/debt-balance-auto-loans
    Explore at:
    json, excel, xml, csvAvailable download formats
    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

    Debt Balance Auto Loans in the United States increased to 1.66 Trillion USD in the second quarter of 2025 from 1.64 Trillion USD in the first quarter of 2025. This dataset includes a chart with historical data for the United States Debt Balance Auto Loans.

  10. f

    T-test for AUCROC.

    • figshare.com
    xls
    Updated May 31, 2023
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    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh (2023). T-test for AUCROC. [Dataset]. http://doi.org/10.1371/journal.pone.0191863.t008
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh
    License

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

    Description

    T-test for AUCROC.

  11. f

    Call/Call duration data based features.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh (2023). Call/Call duration data based features. [Dataset]. http://doi.org/10.1371/journal.pone.0191863.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh
    License

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

    Description

    Call/Call duration data based features.

  12. f

    Testing results—Predicting financial trouble as a function of different...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh (2023). Testing results—Predicting financial trouble as a function of different feature sets. [Dataset]. http://doi.org/10.1371/journal.pone.0191863.t007
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh
    License

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

    Description

    Testing results—Predicting financial trouble as a function of different feature sets.

  13. m

    Coface SA - Gross-Profit

    • macro-rankings.com
    csv, excel
    Updated Aug 11, 2025
    + more versions
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    macro-rankings (2025). Coface SA - Gross-Profit [Dataset]. https://www.macro-rankings.com/Markets/Stocks/COFA-PA/Income-Statement/Gross-Profit
    Explore at:
    csv, excelAvailable download formats
    Dataset updated
    Aug 11, 2025
    Dataset authored and provided by
    macro-rankings
    License

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

    Area covered
    france
    Description

    Gross-Profit Time Series for Coface SA. COFACE SA, through its subsidiaries, provides credit insurance products and related services for microenterprises, small and medium enterprises, mid-market companies, international corporations, financial institutions, and clients of distribution partners. It offers credit insurance products to protect companies against default on payment of its trade receivables. The company also provides integrated credit management solutions comprising credit insurance, single risk insurance, and business information and debt collection services for insured and uninsured businesses; and factoring services, as well as contract and environmental surety, customs and excise, and legal bonds; and payment guarantees. In addition, it offers business information services through its iCON portal, a credit risk management technology platform; and Universal Risk Business Assessment (URBA) information services platform that contains portfolio management and corporate risk monitoring options. The company has operations in Western Europe, Northern Europe, Central and Eastern Europe, the Mediterranean and Africa, North America, Latin America, and the Asia-Pacific. COFACE SA was founded in 1946 and is headquartered in Bois-Colombes, France.

  14. f

    Top-10 features for each category, as well as the sign (positive or...

    • figshare.com
    xls
    Updated Jun 18, 2023
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    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh (2023). Top-10 features for each category, as well as the sign (positive or negative) of their Pearson’s correlation with the outcome variable (having financial trouble or not). [Dataset]. http://doi.org/10.1371/journal.pone.0191863.t010
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 18, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Rishav Raj Agarwal; Chia-Ching Lin; Kuan-Ta Chen; Vivek Kumar Singh
    License

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

    Description

    Top-10 features for each category, as well as the sign (positive or negative) of their Pearson’s correlation with the outcome variable (having financial trouble or not).

  15. 🦈 Shark Tank US dataset 🇺🇸

    • kaggle.com
    Updated Jul 27, 2025
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    Satya Thirumani (2025). 🦈 Shark Tank US dataset 🇺🇸 [Dataset]. https://www.kaggle.com/datasets/thirumani/shark-tank-us-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 27, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Satya Thirumani
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    SharkTank dataset of USA/American business reality television series. Currently, the data set has information from SharkTank season 1 to Shark Tank US season 16. The dataset has 53 fields/columns and 1440+ records.

    Below are the features/fields in the dataset:

    • Season Number - Season number
    • Startup Name - Company name or product name
    • Episode Number - Episode number within the season
    • Pitch Number - Overall pitch number
    • Season Start - Season first aired date
    • Season End - Season last aired date
    • Original Air Date - Episode original/first aired date, on OTT/TV
    • Industry - Industry name or type
    • Business Description - Business Description
    • Company Website - Website of startup/company
    • Pitchers Gender - Gender of pitchers
    • Pitchers City - US city of pitchers
    • Pitchers State - US state or country of pitchers, two letter shortcut
    • Pitchers Average Age - Average age of all pitchers, <30 young, 30-50 middle, >50 old
    • Entrepreneur Names - Pitcher names
    • Multiple Entrepreneurs - Multiple entrepreneurs are present ? 1-yes, 0-no
    • US Viewership - Viewership in US, TRP rating, in millions
    • Original Ask Amount - Original Ask Amount, in USD
    • Original Offered Equity - Original Offered Equity, in percentages
    • Valuation Requested - Valuation Requested, in USD
    • Got Deal - Got the deal or not, 1-yes, 0-no
    • Total Deal Amount - Total Deal Amount, in USD, including debt/loan amount
    • Total Deal Equity - Total Deal Equity, in percentages
    • Deal Valuation - Deal Valuation, in USD
    • Number of sharks in deal - Number of sharks in deal
    • Investment Amount Per Shark - Investment Amount Per Shark
    • Equity Per Shark - Equity received by each Shark
    • Royalty Deal - Is it royalty deal or not (1-yes)
    • Advisory Shares Equity - Deal with Advisory shares or equity, in percentages
    • Loan - Loan/debt (line of credit) amount given by sharks, in USD
    • Deal has conditions - Deal has conditions or not? (yes or no)
    • Barbara Corcoran Investment Amount - Amount Invested by Barbara Corcoran
    • Barbara Corcoran Investment Equity - Equity received by Barbara Corcoran
    • Mark Cuban Investment Amount - Amount Invested by Mark Cuban
    • Mark Cuban Investment Equity - Equity received by Mark Cuban
    • Lori Greiner Investment Amount - Amount Invested by Lori Greiner
    • Lori Greiner Investment Equity - Equity received by Lori Greiner
    • Robert Herjavec Investment Amount - Amount Invested by Robert Herjavec
    • Robert Herjavec Investment Equity - Equity received by Robert Herjavec
    • Daymond John Investment Amount - Amount Invested by Daymond John
    • Daymond John Investment Equity - Equity received by Daymond John
    • Kevin O Leary Investment Amount - Amount Invested by Kevin O'Leary
    • Kevin O Leary Investment Equity - Equity received by Kevin O'Leary
    • Guest Investment Amount - Amount Invested by Guests
    • Guest Investment Equity - Equity received by Guests
    • Guest Name - Name of Guest shark, if invested in deal
    • Barbara Corcoran Present - Whether Barbara Corcoran present in episode or not
    • Mark Cuban Present - Whether Mark Cuban present in episode or not
    • Lori Greiner Present - Whether Lori Greiner present in episode or not
    • Robert Herjavec Present - Whether Robert Herjavec present in episode or not
    • Daymond John Present - Whether Daymond John present in episode or not
    • Kevin O Leary Present - Whether Kevin O Leary present in episode or not
    • Guest Present - Whether Guest present in episode or not
  16. Business credit outstanding, by supplier type and industry

    • www150.statcan.gc.ca
    • open.canada.ca
    • +2more
    Updated Apr 25, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Business credit outstanding, by supplier type and industry [Dataset]. http://doi.org/10.25318/3310001401-eng
    Explore at:
    Dataset updated
    Apr 25, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Semi-annual business debt for all supplier types, by financing characteristics and by the North American Industry Classification System (NAICS), displayed in millions of dollars unless otherwise specified.

  17. FHFA Data: Public Use Database

    • datalumos.org
    delimited
    Updated Feb 14, 2025
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    Federal Housing Finance Agency (2025). FHFA Data: Public Use Database [Dataset]. http://doi.org/10.3886/E219482V1
    Explore at:
    delimitedAvailable download formats
    Dataset updated
    Feb 14, 2025
    Dataset authored and provided by
    Federal Housing Finance Agencyhttps://www.fhfa.gov/
    License

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

    Time period covered
    2018 - 2023
    Area covered
    United States of America
    Description

    The Public Use Database (PUDB) is released annually to meet FHFA’s requirement under 12 U.S.C. 4543 and 4546(d) to publicly disclose data about the Enterprises’ single-family and multifamily mortgage acquisitions. The datasets supply mortgage lenders, planners, researchers, policymakers, and housing advocates with information concerning the flow of mortgage credit in America’s neighborhoods. Beginning with data for mortgages acquired in 2018, FHFA has ordered that the PUDB be expanded to include additional data that is the same as the data definitions used by the regulations implementing the Home Mortgage Disclosure Act, as required by 12 U.S.C. 4543(a)(2) and 4546(d)(1).The PUDB single-family datasets include loan-level records that include data elements on the income, race, and sex of each borrower as well as the census tract location of the property, loan-to-value (LTV) ratio, age of mortgage note, and affordability of the mortgage. New for 2018 are the inclusion of the borrower’s debt-to-income (DTI) ratio and detailed LTV ratio data at the census tract level. The PUDB multifamily property-level datasets include information on the unpaid principal balance and type of seller/servicer from which the Enterprise acquired the mortgage. New for 2018 is the inclusion of property size data at the census tract level. The multifamily unit-class files also include information on the number and affordability of the units in the property. Both the single-family and multifamily datasets include indicators of whether the purchases are from “underserved” census tracts, as defined in terms of median income and minority percentage of population.Prior to 2010 the single-family PUDB consisted of three files: Census Tract, National A, and National B files. With the 2010 PUDB a fourth file, National C, was added to provide information on high-cost mortgages acquired by the Enterprises. The single-family Census Tract file includes information on the location of the property based on the 2010 Census for acquisition years 2012 through 2021, and the 2020 Census beginning with the 2022 acquisition year. The National files contain other information but lack detailed geographic information in order to protect Enterprise proprietary data. The multifamily datasets also consist of a Census Tract file, and a National file without detailed geographic information.Several dashboards are available to analyze the data:Enterprise Multifamily Public Use Database DashboardThe Enterprise Multifamily Public Use Database (PUDB) Dashboard provides users an interactive way to generate and visualize Enterprise PUDB data of multifamily mortgage acquisitions by Fannie Mae and Freddie Mac. It shows characteristics about multifamily loans, properties and units at the national level, and characteristics about multifamily loans and properties at the state level. It includes key statistics, time series charts, and state maps of multifamily housing characteristics such as median loan amount, number of properties, average number of units per property, and unit affordability. The underlying aggregate statistics presented in the dashboard come from three multifamily data files in the Enterprise PUDB, updated annually since 2008, including two property-level datasets and a data file on the size and affordability of individual units.Enterprise Multifamily Public Use DashboardPress Release - FHFA Releases Data Visualization Dashboard for Enterprises’ Multifamily Mortgage AcquisitionsMortgage Loan and Natural Disaster DashboardFHFA published an interactive Mortgage Loan and Natural Disaster Dashboard that combines FHFA’s PUDB reports on single-family and multifamily acquisitions for the regulated entities, FEMA’s National Risk Index (NRI), and FHFA’s Duty to Serve 2023 High-Needs rural areas. Desired geographies can be exported to .pdf and Excel from the Public Use Database and National Risk Index Dashboard.Mortgage Loan and Natural Disaster DashboardMortgage Loan and Natural Disaster Dashboard FAQs

  18. F

    Data from: Personal Saving Rate

    • fred.stlouisfed.org
    json
    Updated Aug 29, 2025
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    (2025). Personal Saving Rate [Dataset]. https://fred.stlouisfed.org/series/PSAVERT
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 29, 2025
    License

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

    Description

    Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to Jul 2025 about savings, personal, rate, and USA.

  19. m

    ECN Capital Corp - Total-Debt-To-Ebitda

    • macro-rankings.com
    csv, excel
    Updated Aug 15, 2025
    + more versions
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    macro-rankings (2025). ECN Capital Corp - Total-Debt-To-Ebitda [Dataset]. https://www.macro-rankings.com/Markets/Stocks?Entity=ECN.TO&Item=Total-Debt-To-Ebitda
    Explore at:
    excel, csvAvailable download formats
    Dataset updated
    Aug 15, 2025
    Dataset authored and provided by
    macro-rankings
    License

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

    Area covered
    canada
    Description

    Total-Debt-To-Ebitda Time Series for ECN Capital Corp. ECN Capital Corp. originates, manages, and advises on credit assets on behalf of its partners in North America. It operates in two segments, Manufactured Housing Finance; and Recreational Vehicle and Marine Finance. The company offers manufactured housing, recreational vehicle, and marine loans; and commercial loans, such as floorplan and rental loans. It serves banks, credit unions, life insurance companies, and pension and investment funds. The company was incorporated in 2016 and is headquartered in Toronto, Canada.

  20. T

    Pakistan Total External Debt

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Pakistan Total External Debt [Dataset]. https://tradingeconomics.com/pakistan/external-debt
    Explore at:
    xml, excel, json, csvAvailable download formats
    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
    Jun 30, 2002 - Mar 31, 2025
    Area covered
    Pakistan
    Description

    External Debt in Pakistan decreased to 130310 USD Million in the first quarter of 2025 from 130921 USD Million in the fourth quarter of 2024. This dataset provides - Pakistan External Debt - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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Statista (2025). Quarterly credit card debt in the U.S. 2010-2025 [Dataset]. https://www.statista.com/statistics/245405/total-credit-card-debt-in-the-united-states/
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Quarterly credit card debt in the U.S. 2010-2025

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Dataset updated
Jun 4, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

Credit card debt in the United States has been growing at a fast pace between 2021 and 2025. In the fourth quarter of 2024, the overall amount of credit card debt reached its highest value throughout the timeline considered here. COVID-19 had a big impact on the indebtedness of Americans, as credit card debt decreased from *** billion U.S. dollars in the last quarter of 2019 to *** billion U.S. dollars in the first quarter of 2021. What portion of Americans use credit cards? A substantial portion of Americans had at least one credit card in 2025. That year, the penetration rate of credit cards in the United States was ** percent. This number increased by nearly seven percentage points since 2014. The primary factors behind the high utilization of credit cards in the United States are a prevalent culture of convenience, a wide range of reward schemes, and consumer preferences for postponed payments. Which companies dominate the credit card issuing market? In 2024, the leading credit card issuers in the U.S. by volume were JPMorgan Chase & Co. and American Express. Both firms recorded transactions worth over one trillion U.S. dollars that year. Citi and Capital One were the next banks in that ranking, with the transactions made with their credit cards amounting to over half a trillion U.S. dollars that year. Those industry giants, along with other prominent brand names in the industry such as Bank of America, Synchrony Financial, Wells Fargo, and others, dominate the credit card market. Due to their extensive customer base, appealing rewards, and competitive offerings, they have gained a significant market share, making them the preferred choice for consumers.

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