21 datasets found
  1. Monthly credit card debt in the UK 1993-2025

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Monthly credit card debt in the UK 1993-2025 [Dataset]. https://www.statista.com/statistics/286416/united-kingdom-uk-outstanding-balance-value-on-credit-cards/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 25, 2025
    Area covered
    United Kingdom
    Description

    Total credit card debt in the UK grew by over ****billion British pounds between March and April 2025, now reaching a similar level of debt as seen in early 2020. The annual growth rate of credit card debt stayed about the same in April 2025, reaching *** percent when compared to aApril 2024. The growth rate in 2024 has been decreasing until 2025 where it started to increase again, which may potentially be attributed to growing interest rates and the cost of living crisis.

  2. T

    United States Consumer Credit Change

    • tradingeconomics.com
    • fr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 7, 2025
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    TRADING ECONOMICS (2025). United States Consumer Credit Change [Dataset]. https://tradingeconomics.com/united-states/consumer-credit
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    json, xml, csv, excelAvailable download formats
    Dataset updated
    Nov 7, 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 - Sep 30, 2025
    Area covered
    United States
    Description

    Consumer Credit in the United States increased to 13.09 USD Billion in September from 3.13 USD Billion in August 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.

  3. Distribution of credit card debt in the U.S. 2019, by generation

    • statista.com
    Updated Nov 29, 2025
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    Statista (2025). Distribution of credit card debt in the U.S. 2019, by generation [Dataset]. https://www.statista.com/statistics/1021953/distribution-of-credit-card-debt-usa-by-generation/
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    Dataset updated
    Nov 29, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2019
    Area covered
    United States
    Description

    This statistic presents the distribution of credit card debt in the United States in 2019, by generation. In March 2019, ** percent of Millennials had not credit card debt at all, *** percentage point lower than the national rate.

  4. Distribution of credit card debt in the U.S. 2019, by debt value

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Distribution of credit card debt in the U.S. 2019, by debt value [Dataset]. https://www.statista.com/statistics/1021979/distribution-of-credit-card-debt-usa-by-amount/
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2019
    Area covered
    United States
    Description

    This statistic presents the distribution of total credit card debt in the United States in 2019, by value of debt. In March 2019, ** percent of respondents had some credit card debt, but the total was less than ***** U.S. dollars.

  5. I

    India Household Debt

    • ceicdata.com
    Updated Jan 27, 2017
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    CEICdata.com (2017). India Household Debt [Dataset]. https://www.ceicdata.com/en/indicator/india/household-debt
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    Dataset updated
    Jan 27, 2017
    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, 2014 - Mar 1, 2025
    Area covered
    India
    Description

    Key information about India Household Debt

    • India Household Debt reached 681.5 USD bn in Mar 2025, compared with the reported number of 617.3 USD bn in the previous year
    • India Household Debt: USD mn data is updated yearly, available from Mar 1998 to Mar 2025
    • The data reached an all-time high of 681.5 USD bn in Mar 2025 and a record low of 8.8 USD bn in Mar 1998

    *This indicator will be no longer available from March 2026, 4th onwards. CEIC has a plan to remove the non-standard frequency indicator after the standard frequency indicator has been added and be available on this table. CEIC converts annual Household Debt into USD. The Reserve Bank of India provides Household Debt in local currency. The Federal Reserve Board period end market exchange rate is used for currency conversions. Loans are used due to the lack of Flow of Funds statistics. Household Debt includes Consumer Durables, Housing and Rest of Personal Loans. Household Debt is in annual frequency, ending in March of each year.


    Further information about India Household Debt

    • In the latest reports, India Household Debt accounted for 17.6 % of the country's Nominal GDP in Mar 2025
    • Money Supply M2 in India increased 793.0 USD bn YoY in Sep 2025
    • India Foreign Exchange Reserves was measured at 564.6 USD bn in Oct 2025
    • The Foreign Exchange Reserves equaled 7.4 Months of Import in Oct 2025
    • India Domestic Credit reached 3,320.5 USD bn in Sep 2025, representing an increased of 10.4 % YoY

  6. Distribution of Baby Boomer credit card debt in the U.S. 2019, by debt value...

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Distribution of Baby Boomer credit card debt in the U.S. 2019, by debt value [Dataset]. https://www.statista.com/statistics/1021978/distribution-of-baby-boomer-credit-card-debt-usa-by-amount/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2019
    Area covered
    United States
    Description

    This statistic presents the distribution of Baby Boomer credit card debt in the United States in 2019, by value of debt. In March 2019, ** percent of Baby Boomerers had some credit card debt, but the total was less than ***** U.S. dollars.

  7. Debt Settlement Market Analysis, Size, and Forecast 2024-2028: North America...

    • technavio.com
    pdf
    Updated Oct 8, 2024
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    Technavio (2024). Debt Settlement Market Analysis, Size, and Forecast 2024-2028: North America (US and Canada), Europe (France, Germany, Italy, UK), Middle East and Africa , APAC (China, India, Japan, South Korea), South America , and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/debt-settlement-market-industry-analysis
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    pdfAvailable download formats
    Dataset updated
    Oct 8, 2024
    Dataset provided by
    TechNavio
    Authors
    Technavio
    License

    https://www.technavio.com/content/privacy-noticehttps://www.technavio.com/content/privacy-notice

    Time period covered
    2024 - 2028
    Area covered
    Canada, United States
    Description

    Snapshot img

    Debt Settlement Market Size 2024-2028

    The debt settlement market size is forecast to increase by USD 5.07 billion at a CAGR of 10.3% between 2023 and 2028.

    The market is experiencing significant growth due to the increasing trend of consumers seeking relief from mounting credit card debts. One-time debt settlement has gained popularity as an effective solution for individuals looking to reduce their outstanding debt balances. However, the time-consuming nature of negotiations between debtors and creditors poses a challenge for market expansion. Despite this, the market's strategic landscape remains favorable for companies offering debt settlement services. Key drivers include the rising number of consumers struggling with debt, increasing awareness of debt settlement as a viable debt relief option, and the growing preference for affordable and flexible debt repayment plans.
    Companies seeking to capitalize on market opportunities should focus on streamlining the negotiation process, leveraging technology to enhance customer experience, and building trust and transparency with clients. Effective operational planning and strategic partnerships with creditors can also help companies navigate the challenges of a competitive and complex market.
    

    What will be the Size of the Debt Settlement Market during the forecast period?

    Request Free Sample

    The market encompasses a range of companies offering financial wellness programs to help consumers manage and reduce their debt. These programs include medical Debt collection, consumer debt relief, and financial education resources. Online financial resources and debt management software are increasingly popular, providing consumers with affordable debt solutions and debt negotiation strategies. However, it's crucial for consumers to be aware of debt settlement scams and their settlement success rates. Debt consolidation loans and financial planning tools are also viable options for responsible debt management. Furthermore, financial literacy education and workshops are essential for consumers to understand debt reduction calculators and credit reporting errors.
    Consumer financial protection agencies offer financial counseling services and financial planning advice to promote financial wellness strategies and responsible borrowing. Student loan forgiveness programs are also gaining traction in the market. Overall, the market for debt settlement and financial wellness solutions continues to evolve, with a focus on providing accessible and effective debt relief options for consumers.
    

    How is this Debt Settlement Industry segmented?

    The debt settlement industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

    Type
    
      Credit card debt
      Student loan debt
      Medical debt
      Auto loan debt
      Unsecured personal loan debt
      Others
    
    
    End-user
    
      Individual
      Enterprise
      Government
    
    
    Distribution Channel
    
      Online
      Offline
      Hybrid
    
    
    Service Type
    
      Debt Settlement
      Debt Consolidation
      Debt Management Plans
      Credit Counseling
    
    
    Provider Type
    
      For-profit Debt Settlement Companies
      Non-profit Credit Counseling Agencies
      Law Firms
      Financial Institutions
    
    
    Geography
    
      North America
    
        US
        Canada
    
    
      Europe
    
        France
        Germany
        Italy
        UK
    
    
      Middle East and Africa
    
    
    
      APAC
    
        China
        India
        Japan
        South Korea
    
    
      South America
    
    
    
      Rest of World (ROW)
    

    By Type Insights

    The credit card debt segment is estimated to witness significant growth during the forecast period.

    The market experiences significant activity due to the escalating credit card debt among consumers. In India, for instance, the rising financial hardships faced by borrowers are evident in the increasing credit card defaults. The latest data indicates that credit card defaults in India reached 1.8% in June 2024, a notable increase from 1.7% six months prior and 1.6% in March 2023. This trend underscores the mounting financial pressures on consumers. The outstanding credit card debt in India mirrors this trend, with approximately USD3.25 billion in outstanding balances as of June 2024, a slight increase from the previous year.

    Debt elimination and negotiation strategies, such as debt relief programs and debt consolidation, have become increasingly popular among consumers seeking financial relief. Credit reporting agencies play a crucial role in this process, as they maintain and report consumers' credit histories to lenders. Student loan debt, medical debt, tax debt, and payday loans are other significant contributors to the market. Consumers often turn to debt validation, credit repair, and financial coaching for guidance in managing their debts. Online platforms, mobile apps, and budgeting tools have become esse

  8. k

    Data from: Subprime Credit Card Delinquencies Have Fallen

    • kansascityfed.org
    pdf
    Updated Apr 2, 2025
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    (2025). Subprime Credit Card Delinquencies Have Fallen [Dataset]. https://www.kansascityfed.org/research/economic-bulletin/subprime-credit-card-delinquencies-have-fallen/
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    pdfAvailable download formats
    Dataset updated
    Apr 2, 2025
    Description

    Credit card delinquencies rose steadily for subprime borrowers from March 2022, when monetary policy tightening began, to November 2024. As of January 2025, however, the subprime delinquency rate has fallen for two consecutive months. This fall coincided with declines in both subprime credit card purchases as well as the annual percentage rate (APR) for subprime credit cards. Together, these declines suggest subprime borrowers had lower demand for credit card financing in recent months.

  9. Debt Collection Agencies in the US - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Aug 6, 2006
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    IBISWorld (2006). Debt Collection Agencies in the US - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/united-states/market-research-reports/debt-collection-agencies-industry/
    Explore at:
    Dataset updated
    Aug 6, 2006
    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

    Debt collection agencies have been significantly impacted by several macroeconomic events and uneven consumer sentiment, resulting in substantial shifts in debt payments and new debt accrual. Following the pandemic, debt collection agencies struggled to regain their footing, as a multitude of government assistance measures, including policies such as the American Rescue Plan of March 2021 and a student loan freeze, bolstered individual consumers’ debt repayment capabilities and resulted in a considerable slowdown in overall debt accrual. While previous interest rate spikes and the lifting of the student loan freeze created additional repayment stresses for consumers, new interest rate cuts and student loan forgiveness programs are moderately easing financial pressures across many households. Despite the more recent recovery, the overarching effects of debt repayment freeze and generous federal stimulus resulted in revenue slipping at a CAGR of 6.3% to an estimated $13.6 billion over the past five years. Small debt collection agencies face significant pressure from emerging accounts receivable platforms and virtual debt collection companies that aim to replace traditional practices. Prominent debt collectors can invest in new communication methods and data analytics, giving them an edge in outreach techniques such as telephone calling and social media communications. Competitive pressures intensify as new technology enables companies to manage their own debt collection, while out-of-market firms like fintech, Buy Now, Pay Later (BNPL) providers and payment platforms gain new revenue streams. Prominent companies, such as Alorica Inc., have responded tactically, with the company pursuing an AI cloud partnership with Google in October 2024, which bolstered profitability through more efficient internal workflow and direct-to-consumer services. Moving forward, debt collection agencies face modest prospects amid a reduction in interest rates and continued growth in medical and student loan debt. Consumers will use less revolving debt and hold larger balances in a higher-interest-rate environment. According to 2025 data from the New York Fed, outstanding credit card debt exceeded $1.2 trillion in the second quarter, a 5.9% gain from the same period a year ago. Nonetheless, continued pressure from in-house alternatives among established financial organizations will force debt collection agencies to remain at the forefront of workflow modernization when procuring debt portfolios. Revenue is expected to accelerate at a CAGR of 1.6% to an estimated $14.7 billion through the end of 2030. However, these revenue levels remain substantially lower than they were before the pandemic.

  10. U

    Buckeye State Poll, March 1999

    • dataverse-staging.rdmc.unc.edu
    Updated Nov 30, 2007
    + more versions
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    UNC Dataverse (2007). Buckeye State Poll, March 1999 [Dataset]. https://dataverse-staging.rdmc.unc.edu/dataset.xhtml?persistentId=hdl:1902.29/D-33497
    Explore at:
    tsv(479872), pdf(87029), application/x-sas-transport(1117520), txt(1508472), application/x-spss-por(405567)Available download formats
    Dataset updated
    Nov 30, 2007
    Dataset provided by
    UNC Dataverse
    License

    https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/D-33497https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/D-33497

    Area covered
    Ohio
    Description

    This survey focuses on perception of the economy, credit card use and overall debt, computer and internet usage, and telephone service. Definite increase in the attention paid to media exposure, specifically on television, magazines, and computer and internet activities. Also includes political affiliations and activities.

  11. I

    Israel Credit Cards Market Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 28, 2025
    + more versions
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    Market Report Analytics (2025). Israel Credit Cards Market Report [Dataset]. https://www.marketreportanalytics.com/reports/israel-credit-cards-market-99607
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    ppt, pdf, docAvailable download formats
    Dataset updated
    Apr 28, 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
    Israel
    Variables measured
    Market Size
    Description

    The Israeli credit card market, valued at $142.44 million in 2025, is projected to experience robust growth, driven by increasing digitalization, rising e-commerce adoption, and a growing preference for cashless transactions among Israeli consumers. The 8.59% CAGR (Compound Annual Growth Rate) from 2019 to 2033 indicates a significant expansion over the forecast period. Key segments fueling this growth include general-purpose credit cards, followed by specialty cards catering to specific consumer needs. The application segments show strong growth across categories, notably food & groceries, health & pharmacy, and travel & tourism, reflecting changing consumer spending patterns and lifestyle choices. Leading players like Isracard, Leumi Bank, CAL (Israel Credit Cards Ltd), American Express, and others are vying for market share through innovative product offerings, loyalty programs, and strategic partnerships. The competitive landscape is dynamic, with banks and specialized credit card providers engaged in a constant battle for customer acquisition and retention. Growth is further supported by the increasing penetration of financial technology (FinTech) solutions, enhancing transaction processing efficiency and security. However, regulatory changes and potential economic fluctuations pose challenges to sustained market growth. While the specific drivers, trends, and restraints aren't detailed, we can infer likely factors. Drivers include increasing consumer spending power, government initiatives promoting digital finance, and the expansion of online retail. Trends involve the increasing popularity of contactless payments, reward programs, and personalized financial management tools. Restraints may include concerns regarding data security, the potential for increased debt among consumers, and evolving regulatory frameworks governing the credit card industry. This robust market offers significant opportunities for both established players and new entrants leveraging innovative technological solutions and customer-centric approaches. The forecast period of 2025-2033 holds considerable promise for continued expansion and transformation within the Israeli credit card market. Recent developments include: May 2023: Bank Leumi and CAL (Israel Credit Cards Ltd.) announced the signing of an agreement for issuing and operating Visa, MasterCard, and Diners credit cards to Leumi customers. The long-term strategic agreement relates to all the commercial terms, operating arrangements, and services that CAL will provide to Leumi and its customers., March 2023: The Bank of Israel instructed local banks to report more frequently on the movement of money in and out of Israel; the new directive comes amid volatility in the Israeli shekel since plans were laid out to overhaul the judiciary.. Key drivers for this market are: Usage of Credit Card Give the Bonus and Reward Points. Potential restraints include: Usage of Credit Card Give the Bonus and Reward Points. Notable trends are: Visa Cards Occupied the Major share in E-Commerce Payments.

  12. w

    Banks – Assets

    • data.wu.ac.at
    • data.gov.au
    xls
    Updated Aug 23, 2015
    + more versions
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    Reserve Bank of Australia (2015). Banks – Assets [Dataset]. https://data.wu.ac.at/schema/data_gov_au/NWNkNjFlMjItNGM0MC00MDJlLWE0NjEtOTdjNGQ2OGU3MGRl
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    xls(236544.0)Available download formats
    Dataset updated
    Aug 23, 2015
    Dataset provided by
    Reserve Bank of Australia
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    These data are derived from returns submitted to the Australian Prudential Regulation Authority (APRA) by banks authorised under the Banking Act 1959. APRA assumed responsibility for the supervision and regulation of banks on 1 July 1998. Data prior to that date were submitted to the RBA.

    Up to and including June 2000, data are averages of weekly (Wednesday) figures. From July 2000, data are for the last business day of every month. Up to and including March 2002, banks submitted Form D (Statement of Liabilities and Assets on the Australian Books). In March 2002, APRA implemented new reporting forms for banks. The data, dating from April 2002, are derived from ARF 320.0 Statement of Financial Position (Domestic Books).

    ARF 320.0 covers the domestic books of the licensed bank and is an unconsolidated report of the Australian bank’s operations/transactions that are booked or recorded inside Australia (with Australian residents and non-residents). ARF 320.0 does not consolidate Australian and offshore-controlled entities (thus offshore branches of the Australian bank are excluded). ARF 320.0 includes transactions of Australian-based offshore banking units of the licensed ADI but excludes transactions of overseas-based offshore banking units.

    An Australian ‘resident’ is any individual, business or other organisation domiciled in Australia. Australian branches and subsidiaries of foreign businesses are regarded as Australian residents. A ‘non-resident’ is any individual, business or other organisation domiciled overseas. Foreign branches and subsidiaries of Australian businesses are regarded as non-residents.

    ‘Resident assets – notes and coins, and deposits due from RBA’ includes: Australian and foreign currency notes and coins; settlement account balances with the RBA and any other central bank; and any other funds held at the RBA.

    ‘Resident assets – bills receivables’ refers to assets arising from undertakings by customers to pay bills of exchange drawn by the banks. From April 2002, this item includes Australian dollar- and foreign currency-denominated (AUD equivalent) bill receivables. Prior to that date, foreign currency-denominated (AUD equivalent) bill receivables are included in ‘resident assets – other assets’.

    ‘Resident assets – loans and advances – residential’ include: owner-occupied and investment housing loans. ‘Resident assets – loans and advances – personal’ include: revolving credit; credit cards; personal lease financing; and other personal term loans. ‘Resident assets – loans and advances – commercial’ include: loans to community service organisations and non-profit institutions; loans to non-financial corporations; loans to general government; and loans to financial corporations. The loans and advances data are net of specific provisions for bad and doubtful debts, but gross of general provisions for bad and doubtful debts. Loans and advances exclude: bills of exchange, commercial paper, promissory notes, certificates of deposit, and some other debt securities. From April 2002, loans and advances refer to Australian dollar- and foreign currency-denominated (AUD equivalent) loans and advances. Prior to that date, foreign currency-denominated (AUD equivalent) loans and advances are included in ‘resident assets – other assets’.

    ‘Resident assets – other assets’ refers to all other resident assets not included in the above items. Prior to April 2002, this item includes: shares; bullion; past-due bills; accounts receivable; prepayments made; public sector securities; and all other resident assets other than accrued interest not yet receivable and intangible assets. From April 2002, this item includes: cash and liquid assets other than notes and coins and deposits due from RBA; trading and investment securities; fixed assets; intangible assets; other investments and all other assets not reported above. Note that, from April 2002, this item also includes unrealised gains on trading derivatives – prior to that date, these were excluded.

    ‘Resident assets – total’ refers to total assets on the Australian books of banks that are due from residents, and is the sum of the above items. ‘Resident assets – of which: denominated in foreign currency’ refers to the Australian dollar equivalent of ‘resident assets – total’ on the Australian books of banks that are denominated in foreign currency.

    ‘Non-resident assets – total’ refers to total assets on the Australian books of banks that are due from non-residents, though from April 2002, this series excludes the total amount due from banks’ overseas operations, which have been separately identified on the new reporting form. ‘Non-resident assets – of which: denominated in foreign currency’ refers to the Australian dollar equivalent of ‘non-resident assets – total’ on the Australian books of banks that are denominated in foreign currency.

    ‘Total assets’ is the sum of ‘resident assets – total’ and ‘non-resident assets – total’. From April 2002, this item also includes the ‘amount due from overseas operations’, which is identified separately from ‘resident assets – total’ and ‘non-resident assets – total’. The ‘amount due from overseas operations’ refers to domestic book on-balance sheet assets due from overseas operations of banks which have not been included in the above items.

  13. G

    Ghana External Debt: Public: Bilateral Creditors

    • ceicdata.com
    Updated Oct 15, 2025
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    CEICdata.com (2025). Ghana External Debt: Public: Bilateral Creditors [Dataset]. https://www.ceicdata.com/en/ghana/external-debt-quarterly/external-debt-public-bilateral-creditors
    Explore at:
    Dataset updated
    Oct 15, 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
    Dec 1, 2014 - Sep 1, 2017
    Area covered
    Ghana
    Description

    Ghana External Debt: Public: Bilateral Creditors data was reported at 1.216 USD bn in Mar 2018. This records an increase from the previous number of 1.211 USD bn for Dec 2017. Ghana External Debt: Public: Bilateral Creditors data is updated quarterly, averaging 1.212 USD bn from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 4.192 USD bn in Dec 2014 and a record low of 409.190 USD mn in Jun 2005. Ghana External Debt: Public: Bilateral Creditors data remains active status in CEIC and is reported by Bank of Ghana. The data is categorized under Global Database’s Ghana – Table GH.JB004: External Debt: Quarterly. Prior to March 2015 the Export Credit Agencies and Other Concessional Creditors were part of Bilateral Creditors

  14. U

    Buckeye State Poll, March 2002

    • dataverse-staging.rdmc.unc.edu
    Updated Nov 30, 2007
    + more versions
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    UNC Dataverse (2007). Buckeye State Poll, March 2002 [Dataset]. https://dataverse-staging.rdmc.unc.edu/dataset.xhtml?persistentId=hdl:1902.29/D-33548
    Explore at:
    pdf(146598), application/x-sas-transport(789120), tsv(245182), application/x-spss-por(235791), txt(575640)Available download formats
    Dataset updated
    Nov 30, 2007
    Dataset provided by
    UNC Dataverse
    License

    https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/D-33548https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/D-33548

    Area covered
    Ohio
    Description

    This survey focuses on personal finances, perception of the economy, credit card use, and overall debt, including mortgages, bank loans, and installment loans. The primary focus is on the source of the respondents' economic information and their habits regarding the communication of economic information with others. Maintains queries on media exposure, computer use, telephone service, level of educational attainment, and political affiliation.

  15. r

    Melbourne Institute Historical Time Series Data: Household Savings

    • researchdata.edu.au
    Updated Aug 21, 2013
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    Institute of Applied Economic and Social Research; Institute of Applied Economic and Social Research (2013). Melbourne Institute Historical Time Series Data: Household Savings [Dataset]. https://researchdata.edu.au/melbourne-institute-historical-household-savings/186606
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    Dataset updated
    Aug 21, 2013
    Dataset provided by
    The University of Melbourne
    Authors
    Institute of Applied Economic and Social Research; Institute of Applied Economic and Social Research
    Time period covered
    2001 - Present
    Area covered
    Melbourne
    Description

    Quarterly Data from March 2001 Made up of : -Patterns of Savings - Deposit with Bank. -Patterns of Savings - Managed Trust. -Patterns of Savings - Ownership Shares. -Patterns of Savings - Investment Properties. -Patterns of Savings - Superannuation. -Patterns of Savings - Others. -Patterns of Savings - Don't Know. -Patterns of Savings - No Saving. -Forms of Household Savings - Bank Debt. -Forms of Household Savings - Credit Card Debt. -Forms of Household Savings - Hire Purchase Store Credit. -Forms of Household Savings - Car Finance/Leasing. -Forms of Household Savings - Owe Money Family/Friends. -Forms of Household Savings - Others. -Forms of Household Savings - No Debt. -Forms of Household Savings - HECS Debt. -Forms of Household Savings - Mortgage.

      Part of Consumer Attitudes, Sentiments & Expectations (CASiE) in Australia. The survey is conduct monthly by telephone and the sample size is typically 1200 households. Each respondent is characterized by: gender, age, occupation, education, political party preference, home ownership, household income, and postcode. The Household savings part of this survey is used to compile the following Report:
      Melbourne Institute Household Saving and Investment Report. The report contains information about households' current and future saving behaviour, their reasons for saving, and the structure of household assets and debts. The Melbourne Institute Household Saving and Investment Report is produced quarterly.
    
  16. d

    All India and Monthly Growth Rate of Consumer Price Index in Old Format

    • dataful.in
    Updated Nov 20, 2025
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    Dataful (Factly) (2025). All India and Monthly Growth Rate of Consumer Price Index in Old Format [Dataset]. https://dataful.in/datasets/17646
    Explore at:
    xlsx, csv, application/x-parquetAvailable download formats
    Dataset updated
    Nov 20, 2025
    Dataset authored and provided by
    Dataful (Factly)
    License

    https://dataful.in/terms-and-conditionshttps://dataful.in/terms-and-conditions

    Area covered
    India
    Variables measured
    Consumer Price Index
    Description

    The dataset contains All India Yearly External Debt from Handbook of Statistics on Indian Economy. IDBs : India Development Bonds FCCBs : Foreign Currency Convertible Bonds IFC(W) : International Finance Corporation (Washington) FC(B&O) : Foreign Currency (Banks & Others) Deposits

    Note: 1. Other concessional multilateral Government borrowing refers to debt outstanding to Institutions like IFAD, OPEC & EEC (SAC). 2. Multilateral non-concessional Government/ public sector/ financial institutions other borrowings refers to debt outstanding against loans from ADB. 3. Securitised commercial borrowings (inclu. IDBs and FCCBs) includes net Investment by 100% Fll debt funds, Resurgent India Bonds (RIBs) and India Millenium Deposits(IMDs). 4. Rupee debt refers to debt owed to Russia denominated in Rupees and converted at current exchange rates, payable in exports. 5. Civillian's rupee debt includes Supplier’s credit from end-March 1990 onwards. 6. Short-term debt does not include suppliers’ credit of up to 180 days from 1994 till 2004. 7. Multilateral loans do not include revaluation of IBRD pooled loans and exchange rate adjustment under IDA loans for Pre-1971 credits. 8. Debt- service ratio from the year 1992 - 93 includes the revised private transfer contra-entry on account of gold and silver imports.

  17. U

    Buckeye State Poll, March 1997

    • dataverse-staging.rdmc.unc.edu
    Updated Nov 30, 2007
    + more versions
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    UNC Dataverse (2007). Buckeye State Poll, March 1997 [Dataset]. https://dataverse-staging.rdmc.unc.edu/dataset.xhtml?persistentId=hdl:1902.29/D-33461
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    pdf(61609), tsv(65027), application/x-sas-transport(255680), application/x-spss-por(68850), txt(490860)Available download formats
    Dataset updated
    Nov 30, 2007
    Dataset provided by
    UNC Dataverse
    License

    https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/D-33461https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/D-33461

    Area covered
    Ohio
    Description

    This survey focuses on perception of the economy, credit card usage and overall debt, media exposure, and internet usage. Also maintains a focus on political party affiliations.

  18. U

    Buckeye State Poll, March 1998

    • dataverse-staging.rdmc.unc.edu
    Updated Nov 30, 2007
    + more versions
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    UNC Dataverse (2007). Buckeye State Poll, March 1998 [Dataset]. https://dataverse-staging.rdmc.unc.edu/dataset.xhtml?persistentId=hdl:1902.29/D-33478
    Explore at:
    pdf(177360), application/x-sas-transport(1303760), txt(1100790), application/x-spss-por(470691), tsv(539796)Available download formats
    Dataset updated
    Nov 30, 2007
    Dataset provided by
    UNC Dataverse
    License

    https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/D-33478https://dataverse-staging.rdmc.unc.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=hdl:1902.29/D-33478

    Area covered
    Ohio
    Description

    This survey focuses on perception of the economy, credit card usage and overall debt, voting activity, internet usage, and opinions regarding current events, such as urbanization and pollution. Also maintains a particular focus on individual religious beliefs.

  19. g

    Buckeye State Poll, March 2001

    • datasearch.gesis.org
    • dataverse-staging.rdmc.unc.edu
    Updated Jan 22, 2020
    + more versions
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    Center for Survey Research, The Ohio State University (2020). Buckeye State Poll, March 2001 [Dataset]. https://datasearch.gesis.org/detail?q=httpsdataverse.unc.eduoai--hdl1902.29D-33531
    Explore at:
    Dataset updated
    Jan 22, 2020
    Dataset provided by
    Odum Institute Dataverse Network
    Authors
    Center for Survey Research, The Ohio State University
    Area covered
    Ohio
    Description

    This survey focuses on personal finances, perception of the economy, credit card use, and overall debt, including mortgages, bank loans, and installment loans. Includes questions regarding approval of political figures and government spending, as well as media exposure, telephone service, level of educational attainment, computer use, and political affiliation.

  20. w

    Banks – Consolidated Group Capital

    • data.wu.ac.at
    xls
    Updated Mar 7, 2015
    + more versions
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    Reserve Bank of Australia (2015). Banks – Consolidated Group Capital [Dataset]. https://data.wu.ac.at/odso/data_gov_au/NWVmNDBmNmYtMmFkNC00YWJiLWI2ZTQtNzhmYTVkM2NkNmE5
    Explore at:
    xls(103424.0)Available download formats
    Dataset updated
    Mar 7, 2015
    Dataset provided by
    Reserve Bank of Australia
    Description

    These data are derived from returns submitted to the Australian Prudential Regulation Authority (APRA) by banks authorised under the Banking ActA 1959. APR assumed responsibility for the supervision and regulation of banks on 1 July 1998. Data prior to that date were submitted to the RBA.

    Prior to March 2002, banks reported to APR on the Capital Adequacy Return. From that date, banks report quarterly on ARF 110.0: Capital Adequacy. Following the introduction of a new capital framework (Basel II) on 1 January 2008, the data from March 2008 contain significant breaks. For details of the Basel II framework, refer to APR prudential standards APS 110aAPS 116, APS 120 and APS 150. For detailed definitions of the capital components listed below, refer to APS 111.

    aConsolidated groupa, for a locally incorporated bank, refers to the global operations of the bank and its subsidiaries, excluding those involved in insurance, funds management/trustee and non-financial business.

    This table excludes data of foreign banks authorised to operate in Australia as branches.

    Measures of capital are net of deductions such as future income tax benefits, intangible assets, investments in non-consolidated subsidiaries, holdings of other banksa capital instruments and other assets that are not eligible for inclusion in capital.

    The breaks in Tier 1 and Tier 2 capital in March 2008 are largely due to changes in the items that banks are required to deduct from capital. Under Basel II, there are a number of new deductions from Tier 1 and Tier 2 capital, and amounts that were previously deducted from the capital base are instead generally deducted half from Tier 1 capital and half from Tier 2 capital.

    aTier 1a capital consists of aShare capitala and other Tier 1 capital items.

    aShare capitala comprises the paid-up value of ordinary shares and non- innovative Tier 1 capital instruments such as irredeemable preference shares on which dividends are non-cumulative.

    Other Tier 1 capital includes retained earnings, certain reserves and innovative Tier 1 capital instruments up to certain limits.

    aTier 2a capital consists of aUpper Tier 2a capital and lower Tier 2 capital.

    aUpper Tier 2a capital includes perpetual cumulative preference shares, mandatory convertible notes and subordinated debt, excess Tier 1 capital instruments, and revaluation reserves of premises, securities and other assets. Under Basel I and the standardised approach to credit risk under Basel II, upper Tier 2 capital also includes the eligible amount of provisions for credit losses (up to a maximum of 1.25 per cent of risk-weighted assets). Banks using the Basel II internal ratings based approach can include any excess of eligible provisions over the amount of their expected losses in upper Tier 2 capital (up to a limit of 0.6 per cent of risk-weighted assets).

    Lower Tier 2 capital includes limited life redeemable preference shares, term subordinated debt and other similar instruments; it cannot exceed 50 perA cent of Tier 1 capital.

    aTier 2a capital cannot exceed aTier 1a capital.

    Under Basel I, the aTotal capital basea is calculated as the sum of net Tier 1 and net Tier 2 capital minus additional capital deductions. Under Basel II, the aTotal capital basea is the sum of net Tier 1 and net Tier 2 capital.

    aRisk-weighted assetsa comprise a acredit riska component and a amarket risk and other exposuresa component. Basel II led to significant changes in the calculation of credit risk weights. Under Basel II, banks must also calculate an explicit charge for operational risk, which is included in amarket risk and other exposuresa from March 2008.

    aOn-balance sheeta assets represent the risk-weighted gross amounts of banking book assets.

    aOff-balance sheeta assets represent the risk-weighted credit equivalent amounts of commitments, derivatives and other business considered to be aoff- balance sheeta prior to the introduction of AIFRS.

    aTier 1 capital ratioa refers to Tier 1 capital expressed as a proportion of total risk-weighted assets.

    aTotal capital base ratioa refers to the capital base as a proportion of total risk-weighted assets.

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Statista (2025). Monthly credit card debt in the UK 1993-2025 [Dataset]. https://www.statista.com/statistics/286416/united-kingdom-uk-outstanding-balance-value-on-credit-cards/
Organization logo

Monthly credit card debt in the UK 1993-2025

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Dataset updated
Nov 29, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Aug 25, 2025
Area covered
United Kingdom
Description

Total credit card debt in the UK grew by over ****billion British pounds between March and April 2025, now reaching a similar level of debt as seen in early 2020. The annual growth rate of credit card debt stayed about the same in April 2025, reaching *** percent when compared to aApril 2024. The growth rate in 2024 has been decreasing until 2025 where it started to increase again, which may potentially be attributed to growing interest rates and the cost of living crisis.

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