Graph and download economic data for Number of Bank Branches for United States (DDAI02USA643NWDB) from 2004 to 2019 about banks, depository institutions, and USA.

This data set is a digitized version of “All-Bank Statistics, United States, 1896-1955,” (ABS) which the Board of Governors of the Federal Reserve System published in 1959. That volume contained annual aggregate balance sheet aggregates for all depository institutions by state and class of institution for the years 1896 to 1955. The depository institutions include nationally chartered commercial banks, state chartered commercial banks, and private banks as well as mutual savings bank and building and loan societies. The data comes from the last business day of the year or the closest available data. This digital version of ABS contains all data in the original source and only data from the original source.This data set is similar to ICPSR 2393, “U.S. Historical Data on Bank Market Structure, ICPSR 2393” by Mark Flood. ICPSR 2393 reports data from ABS but excludes subcategories of data useful for analyzing the liquidity of bank balance sheets, the operation of financial markets, the functioning of the financial network, and depository institutions’ contribution to monetary aggregates. ICPSR 2393, for example, reports total cash assets from ABS but does not report the subcomponents of that total: bankers balances, cash in banks’ own vaults, and items in the process of collection. Those data are needed to understand how much liquidity banks kept on hand, how much liquidity banks stored in or hoped to draw from reserve depositories, and how much of the apparent cash in the financial system was double-counted checks in the process of collection, commonly called float. Those data are also needed to understand the contribution of commercial banks to the aggregate money supply since cash in banks’ vaults counts within monetary aggregates while interbank deposits and float do not. While this dataset provides comprehensive and complete data from ABS, ICPSR 2393 contains information from other sources that researchers may find valuable including data from the aggregate income statements of nationally chartered banks and regulatory variables. To facilitate the use of that information, the naming conventions in this data set are consistent with those in ICPSR 2393.

The estimated number of banks and thrifts in the United States fell from around ****** in 1920 to ****** in 1929, when the onset of the Great Depression would then see it fall further, below ****** in 1933. This marks a cumulative decline of over ****** banks and thrifts, which is equal to a drop of more than ** percent in 13 years. Tumultuous Twenties Despite the economic prosperity associated with the Roarin' 1920s in the U.S., it was a tumultuous decade in financial terms, with more separate recessions than any other decade. However, the ***** was also privy to frivolous lending policies among many banks, which saw the banking sector collapse in the wake of the Wall Street Crash in 1929. Many banks failed as the Great Depression and unemployment spread across the country, and customers or businesses could not afford to repay their loans. It was only after this financial crisis where the federal government began keeping more stringent and accurate records on its banking sector, therefore precise figures and the reasons behind these bank failures are not always clear. Franklin D. Roosevelt Just two days after assuming office in 1933, Franklin D. Roosevelt drastically declared a bank holiday, and all banks in the country were closed from ******* until ********. This break allowed Congress to pass the Emergency Banking Act on *******, which saw the Federal Reserve provide deposit insurance for all reopened banks thereafter. Through his first fireside chat, Roosevelt then encouraged Americans to re-deposit their money in the banks again, which successfully restored much of the public's faith in the banking system - it is estimated that over half of the cash withdrawn during the Great Depression was then returned to the banks by ********.

The H.8 release provides an estimated weekly aggregate balance sheet for all commercial banks in the United States. The release also includes separate balance sheet aggregations for several bank groups: domestically chartered commercial banks; large domestically chartered commercial banks; small domestically chartered commercial banks; and foreign-related institutions in the United States. Foreign-related institutions include U.S. branches and agencies of foreign banks as well as Edge Act and agreement corporations. Published weekly, the release is typically available to the public by 4:15 p.m. each Friday. If Friday is a federal holiday, then the data are released on Thursday.The H.8 release is primarily based on data that are reported weekly by a sample of approximately 875 domestically chartered banks and foreign-related institutions. As of December 2009, U.S. branches and agencies of foreign banks accounted for about 60 of the weekly reporters and domestically chartered banks made up the rest of the sample. Data for domestically chartered commercial banks and foreign-related institutions that do not report weekly are estimated at a weekly frequency based on quarterly Call Report data.

Graph and download economic data for Commercial Banks in the U.S. (DISCONTINUED) (USNUM) from Q1 1984 to Q3 2020 about commercial, banks, depository institutions, and USA.

Over the course of the 1920s, the value of money deposited in commercial banks grew at a fairly steady rate, rising from around 19 billion U.S. dollars in 1921 (the initial dip was due to the post-WWI recession), to 25 billion at the end of the decade. However, the onset of the Great Depression saw these figures drop drastically, and the value of deposits fell from around 26 to 16 billion dollars between 1930 and 1933. This was not only due to high unemployment and lower wages, but many Americans also lost faith in the banks during the Depression - many blamed the banks for the Depression as frivolous lending practices had contributed to the Wall Street Crash; banks demanded early repayment of debts and often repossessed the property of those who could not afford to do so (also leading to evictions), and many banks failed after the Crash and were not perceived as safe. It was not until 1936 where deposits in commercial banks returned to their pre-Depression levels, after the Roosevelt administration put a number of safeguards in place and helped restore public faith in the American banking system.

In contrast to commercial banks, the total amount of money deposited in savings accounts continued to rise throughout the Great Depression, albeit at a much slower rate than in the 1920s. The reason for continued increase was due to the disproportionate impact the Depression had across socioeconomic groups - most working and middle-class Americans did not have the means to have a savings account

Graph and download economic data for Deposits, All Commercial Banks (DPSACBM027NBOG) from Jan 1973 to Jun 2025 about deposits, banks, depository institutions, and USA.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Banks: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 9(1.23%) households where the householder is under 25 years old, 327(44.79%) households with a householder aged between 25 and 44 years, 323(44.25%) households with a householder aged between 45 and 64 years, and 71(9.73%) households where the householder is over 65 years old.
• In Banks, the age group of 25 to 44 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Banks median household income by age. You can refer the same here

Dataset Summary

This dataset contains information about the largest banks globally, including their rank, name, and total assets (in US$ billion as of 2023). The data was scraped from Wikipedia's List of Largest Banks. It can be used for financial analysis, market research, and educational purposes.

Dataset Structure

Columns

• Rank: The rank of the bank based on total assets.
• Bank Name: The name of the bank.
• Total Assets (2023, US$ billion): The total assets of the bank in billions of US dollars as of 2023.

Example

Source

The data was scraped from Wikipedia's List of Largest Banks using Python and Scrapy.

Usage

This dataset can be used for: - Financial market research. - Trend analysis in global banking. - Educational purposes and data visualization.

Licensing

The data is publicly available under Wikipedia's Terms of Use.

Limitations

• The data may not reflect real-time changes as it was scraped from a static page.
• Possible inaccuracies due to updates or inconsistencies on the source page.

Acknowledgements

Thanks to Wikipedia and the contributors of the "List of Largest Banks" page.

Citation

If you use this dataset, please cite it as: @misc{largestbanks2023, author = {Your Name or Organization}, title = {Largest Banks Dataset}, year = {2023}, publisher = {Hugging Face}, url = {https://huggingface.co/datasets/your-dataset-name} }

Q - What makes your data unique?
A - The data is based on Efficient Frontier Analysis (EFA) which accurately measures bank performance but also reveals the best level of performance for the given business portfolio of each bank as well as the optimal business portfolio for maximizing profit. The ratings are superior to any traditional or other measures of bank operational efficiency and business quality because they not only measure performance, but indicate the limits of performance based on the underlying business portfolio of each bank. Using EFA also eliminates the "noise" of industry and economic trends because the Efficient Frontier moves with such trends and automatically accounts for them. Further, Efficient Frontiers exist for each reported expense item allowing detailed ratings of each resource of a bank's operations. Q - How is the data generally sourced?
A - The ratings are generated using data from bank Call Reports filed with the FDIC quarterly. The Call Reports contain vast amounts of data on the financial and operating results of each bank and provides a robust and consistent set of measures from which to generate Efficient Frontiers. Because all banks with FDIC insurance must file Call Reports with the FDIC, we can provide ratings on more than 99% of all FDIC insured banks. Q - What are the primary use-cases or verticals of this Data Product? A - Investors use the measures to differentiate high performing banks from the pack or identify improving or declining banks. PE and other acquirers/owner firms will do likewise, as well as seek insights on how to best improve performance of portfolio companies, target acquisitions, model post-acquisition integrations, etc. Bank management use the measures to identify competitive advantages and weaknesses as well as measuring the potential benefit of improving/retaining a level of performance relative to peers. Q - How does this Data Product fit into your broader data offering? A - Hoeg & Company, Ltd. provides Operational Efficiency & Business Quality Ratings on Banks, Credit Unions & Insurers using EFA. These financial industries all have rigorous regulatory requirements and standards for financial and operational performance reporting (Call Reports & Statutory Financial Reports) which assures detailed, accurate and consistent data that facilitates EFA. Our bank ratings are our most extensively produced set of ratings.

Data were previously published in the Supplement to the Federal Reserve Bulletin, which ceased publication in December 2008. These tables will be discontinued with the final table released in April 2022. The source for these data is the Treasury International Capital System and future data publications can be found on Treasury’s website.

The FR 2644 is a balance sheet report that is collected as of each Wednesday from an authorized stratified sample of 875 domestically chartered commercial banks and U.S. branches and agencies of foreign banks. The FR 2644 is the only source of high-frequency data used in the analysis of current banking developments. The FR 2644 collects sample data that are used to estimate universe levels for the entire commercial banking sector in conjunction with data from the quarterly commercial bank Consolidated Reports of Condition and Income (FFIEC 031, FFIEC 041, and FFIEC 051; OMB No. 7100-0036) and the Report of Assets and Liabilities of U.S. Branches and Agencies of Foreign Banks (FFIEC 002; OMB No. 7100-0032) (Call Reports). Data from the FR 2644 and the Call Reports are utilized in construction of weekly estimates of U.S. bank credit, balance sheet data for the U.S. commercial banking sector, and sources and uses of banks' funds, and to analyze current banking developments, including the monitoring of broad credit and funding conditions. The Board publishes the data in aggregate form in the weekly H.8 statistical release, Assets and Liabilities of Commercial Banks in the United States, which is followed closely by other government agencies, the banking industry, financial press, and other users. The H.8 release provides a balance sheet for the commercial banking industry as a whole as well as disaggregated data for three bank groups: large domestically chartered banks, small domestically chartered banks, and U.S. branches and agencies of foreign banks.

Xtract.io's bank location data delivers a comprehensive geographical snapshot of the United States banking infrastructure. This dataset provides financial institutions, market researchers, and business strategists with granular insights into the distribution of top banks and their ATM networks. By mapping precise locations, organizations can analyze market penetration, identify potential expansion opportunities, and develop targeted marketing strategies. The data supports competitive intelligence, demographic studies, and strategic planning across the financial services landscape.

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About this dataset

Context

The dataset tabulates the Banks population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Banks. The dataset can be utilized to understand the population distribution of Banks by age. For example, using this dataset, we can identify the largest age group in Banks.

Key observations

The largest age group in Banks, AL was for the group of age 20 to 24 years years with a population of 76 (25.50%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Banks, AL was the 65 to 69 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Banks is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Banks total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Banks Population by Age. You can refer the same here

Graph and download economic data for Total Assets, All Commercial Banks (TLAACBW027SBOG) from 1973-01-03 to 2025-08-06 about assets, banks, depository institutions, and USA.

The Uniform Bank Performance Report (UBPR) serves as an analysis of the impact that management and economic conditions can have on a bank's balance sheet. It examines liquidity, adequacy of capital and earnings and other factors that could damage the stability of the bank. The Federal Financial Institutions Examination Council (FFIEC) is a formal U.S. government interagency body that includes five banking regulators—the Federal Reserve Board of Governors (FRB), the Federal Deposit Insurance Corporation (FDIC), the National Credit Union Administration (NCUA), the Office of the Comptroller of the Currency (OCC), and the Consumer Financial Protection Bureau (CFPB). It is "empowered to prescribe uniform principles, standards, and report forms to promote uniformity in the supervision of financial institutions".[1] It also oversees real estate appraisal in the United States.[2] Its regulations are contained in title 12 of the Code of Federal Regulations.

The FFIEC 002 is mandated by the International Banking Act (IBA) of 1978. It collects balance sheet and off-balance-sheet information, including detailed supporting schedule items, from all U.S. branches and agencies of foreign banks. The FFIEC 002S collects information on assets and liabilities of any non-U.S. branch that is managed or controlled by a U.S. branch or agency of a foreign bank.

In 2023, the number of data compromises in the financial services industry in the United States reached 744, up from 138 such incidents in 2020. The financial services sector was the second-most targeted industry by cyber security incidents resulting in data compromise. The number of data compromises includes data breaches, as well as exposure and leakage of private data.

Data are collected as of the end of the month for March, June, September and December, and generally are released three months later. There are two reports showing the same structure and asset information for each U.S. office, but in different orders. Offices located in Puerto Rico, American Samoa, Guam, the Virgin Islands and other U.S.-affiliated insular areas are excluded. The first report lists the offices by institution type. The second report is by the home country of the foreign bank. Each report shows asset totals and subtotals for the categories displayed.

The Department of Public Services and Procurement Canada, in its role as Receiver General for Canada, is responsible for the management and safeguarding of all federal government money. The Receiver General uses a centralized banking system (Government Banking System or GBS) to record the inflow of funds. Data is stored in the GBS detailing the dates and amounts for deposits made to financial institutions. This dataset, entitled “Deposits to Financial Institutions”, provides details extracted from the Government Banking System of all deposits made to Financial Institutions and their subsequent receipt at the Bank of Canada.

Updates will be posted quarterly.

The data has been divided into yearly files spanning one fiscal year, from April 1st to March 31st