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Financial & Economic Essentials
Economic indicators including inflation, unemployment, interest rates, and bank data from the FDIC, FRED, FFIEC, CFPB, BLS, and BIS
This product includes macroeconomic indicators and banking sector data to give users a view of the current state of the financial industry.
Example topics covered:
- Macroeconomic variables such as GDP, unemployment, housing starts, inflation, monthly state-level retail sales
- Financial variables such as interest rates, default rates
- Foreign exchange currency pairs
- Banking sector data such as deposits, insurance, complaints by financial institution
Financial & Economic Essentials combines data sourced from Federal Reserve Economic Data (FRED), Federal Deposit Insurance Corporation (FDIC), Federal Financial Institutions Examination Council (FFIEC), the Bank for International Settlements (BIS), Bureau of Labor Statistics (BLS), Consumer Financial Protection Bureau (CFPB), and various Central Banks.
All Cybersyn products follow the EAV (entity, attributes, value) model with a unified schema. Entities are tangible objects (e.g. geography, company). Entities may have characteristics (i.e. descriptors of the entity) in an index table and values (i.e. statistics, measure) in a timeseries table. Data is joinable across all Cybersyn products that have a
GEO_ID. Refer to Cybersyn Concepts for more details.
FRED, published by the St. Louis Federal Reserve, includes information aggregated from various government sources. This aggregate data features various economic metrics such as monthly state-level retail sales, foreign exchange rates, and industrial production as well as, financial-institution-specific data (e.g. flow of deposits for small and large banks, total bank liabilities, outstanding balance of commercial real estate loans). This product also includes central bank monetary policy rates from Brazil, Canada, England, Mexico, and Japan in the FRED table for ease of comparison with the Federal Funds Effective Rate.
The Bureau of Labor Statistics (BLS) publishes the Consumer Price Index (CPI), Average Prices (AP), Job Openings and Labor Turnover Survey (JOLTS), State and Metro Area Employment , Hours, & Earnings (SAE), and Local Area Unemployment Statistics (LAUS).
The FDIC publishes metadata about active and inactive banks including locations, charter types, and regulator information. The FDIC also publishes comprehensive historical financial data for individual banks going back to 1984 - including total assets, FDIC-insured deposits, and return on equity.
The Summary of Deposits (SOD) from the FDIC is an annual survey, capturing branch-level deposits as of June 30 for all FDIC-insured institutions, including U.S. branches of foreign banks.
The FFIEC data includes detailed location data and time series data for branch openings and closings.
The CFPB publishes the Consumer Complaints Database that provides complaint information for companies by product category, receipt, and company response timeliness by consumer’s zip code and state. The data is updated daily and dates back to Dec 1, 2011.
The Bank for International Settlements (BIS) is an international financial institution owned by 60+ central banks that represent countries accounting for ~95% of global GDP. As part of its mission is to support international monetary and financial cooperation, the BIS acts as a bank for central banks across the world. This product includes BIS data on residential property prices, central bank policy rates, consumer price indicators, and assets and liabilities of internationally active banks. Bank balance sheet data includes credit to the non-financial sector as well as the geographical and currency composition.
As with all Public Domain datasets, Cybersyn aims to release data on Snowflake Marketplace as soon as the underlying source releases new data. We check periodically for changes to the underlying source and, upon detecting a change, propagate the data to Snowflake Marketplace immediately. See our release process for more details.
timeseriestables, by default, contain the latest published version of all releases. In the future, we will maintain point-in-time pre-restatement values.
In some instances, multiple sources of data are combined into a single table. This is true both for aggregator data we propage (ie. FRED) and also for our own aggregatin For example, interest rate data from the Bank of Japan, ECB, etc. live in the
financial_fred_timeseriestable. Other sources like FFIEC and FDIC are combined to form a unified profile of financial institutions.
Although all FDIC-insured institutions must submit to this survey, institutions with only a main office are exempt. The survey requires respondents to provide deposit information at both the institution and branch levels.
Cybersyn builds Streamlit demos to visualize the data available in this product and provide a jumping off point.
Calculate the total quarterly net income for the banking industry over the last four decades.
FROM cybersyn.financial_fred_timeseries AS ts
JOIN cybersyn.financial_fred_attributes AS att ON (ts.variable = att.variable)
WHERE att.variable_name = 'Income and Expense: Net Income (Loss) Attributable to Bank, Not seasonally adjusted, Quarterly, USD'
AND ts.date >= '1984-01-01';
Determine which banks have the highest percentage of uninsured deposits.
WITH big_banks AS (
WHERE variable = 'ASSET'
AND date = '2022-12-31'
AND value > 1E10
1 - value AS pct_uninsured,
FROM cybersyn.financial_institution_timeseries AS ts
INNER JOIN cybersyn.financial_institution_attributes AS att ON (ts.variable = att.variable)
INNER JOIN cybersyn.financial_institution_entities AS ent ON (ts.id_rssd = ent.id_rssd)
INNER JOIN big_banks ON (big_banks.id_rssd = ts.id_rssd)
WHERE ts.date = '2022-12-31'
AND att.variable_name = '% Insured (Estimated)'
AND att.frequency = 'Quarterly'
ORDER BY pct_uninsured DESC;
Compare the growth/decline of bank branches by state since the start of the pandemic.
WITH pre_covid AS (
COUNT(*) AS pre_covid_count
WHERE start_date <= '2020-03-01'
AND (end_date >= '2020-03-01' OR end_date IS NULL)
GROUP BY state_abbreviation
COUNT(*) AS current_count,
current_count / pre_covid_count - 1 AS pct_change
FROM cybersyn.financial_branch_entities AS cur
INNER JOIN pre_covid ON (cur.state_abbreviation = pre_covid.state_abbreviation)
WHERE end_date IS NULL
GROUP BY cur.state_abbreviation, pre_covid_count
ORDER BY pct_change;
Count credit card complaints by month by company since 2012.
DATE_TRUNC('month', date_received) AS month,
COUNT(1) AS credit_card_complaint
WHERE product ILIKE '%card%'
AND date_received >= '2012-01-01'
GROUP BY company, month;
Create a time series of the average price paid for bananas, soft drinks, and ice cream nationwide starting in 2021.
FROM cybersyn.bureau_of_labor_statistics_price_timeseries AS ts
JOIN cybersyn.bureau_of_labor_statistics_price_attributes AS att
ON (ts.variable = att.variable)
WHERE ts.date >= '2021-01-01'
AND att.report = 'Average Price'
AND (att.product ILIKE 'Ice cream%' OR
att.product ILIKE 'Bananas%' OR
att.product ILIKE 'All soft drinks, per 2 liters%')
ORDER BY date;
Track the total count of employees in the finance industry in New York over time. Observe trends from the dot-com bubble, global financial crisis, and Covid-19 pandemic.
FROM cybersyn.bureau_of_labor_statistics_employment_timeseries AS ts
JOIN cybersyn.bureau_of_labor_statistics_employment_attributes AS att
ON (ts.variable = att.variable)
JOIN cybersyn.geography_index AS geo
ON (ts.geo_id = geo.geo_id)
WHERE att.report = 'State and Metro Employment'
AND att.industry = 'Financial Activities'
AND att.measure = 'All Employees'
AND att.frequency = 'Monthly'
AND att.seasonally_adjusted = FALSE
AND geo.geo_name ILIKE '%New York-Newark-Jersey City%'
ORDER BY date;
Time series of the effective federal funds effective rate and PCE.
WHERE variable_name IN ('Federal Funds Effective Rate',
'Trimmed Mean PCE Inflation Rate, Seasonally adjusted, Monthly, Percent Change YoY')
AND date >= '2019-01-01'
ORDER BY date;
Compare and contrast interest rate policies for major global economies.
FROM cybersyn.financial_fred_timeseries AS ts
JOIN cybersyn.financial_fred_attributes AS att
ON (att.variable = ts.variable)
WHERE variable_group IN ('Bank of Brazil Selic Interest Rate Target',
'Bank of Canada Overnight Lending Rate',
'Bank of England Official Bank Rate',
'Bank of Japan Policy-Rate Balance Rate',
'Bank of Mexico Official Overnight Target Rate',
'ECB Main Refinancing Operations Rate: Fixed Rate Tenders for Euro Area',
'Federal Funds Effective Rate');
12/5/23 - Added interest rates posted by major charted banks in Canada for selected products; Added secured overnight financing rates (SOFR) and US Treasury bill rates
Added interest rates for selected products posted by the six major chartered banks in Canada to the
FINANCIAL_FRED_VARIABLE_SERIES_ID_CROSSWALKtables. The typical rate is calculated based on the statistical mode of the rates published by the six banks.
The posted rates cover:
- Prime lending rate
- Conventional mortgages
- Guaranteed investment certificates
- Personal daily interest savings
- Non-checkable savings deposits
Added secured over night financing rates (SOFR) and US Treasury bill rates to the
Series added (FRED ID):
- Secured Overnight Financing Rate (SOFR)
- 30-Day Average Secured Overnight Financing Rate (SOFR30DAYAVG)
- 90-Day Average Secured Overnight Financing Rate (SOFR90DAYAVG)
- 180-Day Average Secured Overnight Financing Rate (SOFR180DAYAVG)
- Secured Overnight Financing Rate Index (SOFRINDEX)
- 3-Month Treasury Bill Minus Federal Funds Rate (TB3SMFFM)
- 6-Month Treasury Bill Minus Federal Funds Rate (TB6SMFFM)
Added monthly state-level retail sales by NAICS codes to the
FINANCIAL_FRED_VARIABLE_SERIES_ID_CROSSWALKtables. The US Census Bureau publishes year-over-year percent changes for each state using a composite model of Monthly Retail Trade Survey (MRTS) data, administrative data, and third-party data beginning in January, 2019.
Year-over-year percent change estimates for the following industries are now available at the state level:
- Total Retail Sales Excluding Nonstore Retailers
- Building Material and Garden Equipment and Supplies Dealers
- Clothing and Clothing Accessories Stores
- Electronics and Appliance Stores
- Food and Beverage Stores
- Furniture and Home Furnishings Stores
- Gasoline Stations
- Health and Personal Care Stores
- Motor Vehicle and Parts Dealers
- Sporting Good, Hobby, Musical Instrument and Book Stores
- Miscellaneous Stores
Added additional country groups and geography types to the
GEOGRAPHY_INDEXfrom the World Health Organization (WHO), World Trade Organization (WTO), and United Nations (UN). The member countries of the added geographies are mapped in the
GEOGRAPHY_RELATIONSHIPStable. Select new geographic regions include:
- BRICS members
- World Trade Organization (WTO) members
- Association of Southeast Asian Nations (ASEAN)
- UNICEF regions
- United Nations regions
- United Nations Sustainable Development Goal (SDG) regions
- World Bank regions
- World Health Organization (WHO) regions and income regions
- World Bank regions and income groups
11/22/23- Added data from the Bank for International Settlements (BIS) on global banking conditions, property prices, and consumer price indicators
Added data from the Bank for International Settlements (BIS) on global banking conditions, property prices, and consumer price indicators
The Bank for International Settlements (BIS) is an international financial institution owned by 60+ central banks that represent countries accounting for ~95% of global GDP. As part of its mission is to support international monetary and financial cooperation, the BIS acts as a bank for central banks across the world.
Added the below BIS data to two new tables,
BANK_FOR_INTERNATIONAL_SETTLEMENTS_ATTRIBUTES, which describes the metrics tracked by BIS, and
BANK_FOR_INTERNATIONAL_SETTLEMENTS_TIMESERIES, which provides the values of metrics:
- Residential property prices
- Central bank policy rates
- Consumer price indicators
- Assets and liabilities of internationally active banks, including credit to the non-financial sector as well as the geographical and currency composition of a bank’s balance sheet
Added 10 additional timeseries from FRED to the
- MORTGAGE15US: 15-Year Fixed Rate Mortgage Average in the United States
- MORTGAGE30US: 30-Year Fixed Rate Mortgage Average in the United States
- CUSR0000SEFV: Consumer Price Index for All Urban Consumers: Food Away from Home in U.S. City Average, Seasonally Adjusted
- CUUR0000SEFV: Consumer Price Index for All Urban Consumers: Food Away from Home in U.S. City Average, Not Seasonally Adjusted
- CUSR0000SETG01: Consumer Price Index for All Urban Consumers: Airline Fares in U.S. City Average, Seasonally Adjusted
- CUUR0000SETG01: Consumer Price Index for All Urban Consumers: Airline Fares in U.S. City Average, Not Seasonally Adjusted
- CUSR0000SS62031: Consumer Price Index for All Urban Consumers: Admission to Movies, Theaters, and Concerts in U.S. City Average, Seasonally Adjusted
- CUUR0000SS62031: Consumer Price Index for All Urban Consumers: Admission to Movies, Theaters, and Concerts in U.S. City Average, Not Seasonally Adjusted
- CUSR0000SEHB: Consumer Price Index for All Urban Consumers: Lodging Away from Home in U.S. City Average, Seasonally Adjusted
- CUUR0000SEHB: Consumer Price Index for All Urban Consumers: Lodging Away from Home in U.S. City Average, Not Seasonally Adjusted
The Summary of Deposits (SOD) data from the FDIC is an annual survey, capturing branch-level deposits as of June 30 for all FDIC-insured institutions, including U.S. branches of foreign banks.
fdic_branch_locations_indextable provides details on FDIC-insured bank branches, including branch-specific location information as well as institution-level regulatory and insurance data.
fdic_summary_of_deposits_attributestable describes the deposit types tracked by the Summary of Deposits (SOD) survey.
fdic_summary_of_deposits_timeseriestable provides the results of the annual Summary of Deposits (SOD) survey going back to 1994 for banks’ branch-level deposits.
Due to the discontinuation of certain currency conversion pairs by the European Central Bank (ECB), our primary source for daily FX rates, we have sourced a number of these pairs from an alternative source, the Bank for International Settlements (BIS), for ongoing history. The Bank for International Settlements will be used to get data for the following currency conversion pairs after September 27, 2023: USD:AED, USD:ARS, USD:CLP, USD:COP, USD:DZD, USD:MAD, USD:PEN, USD:QAR, USD:SAR, USD:TWD, USD:UAH.
Full history from the Bank for International Settlements was added for the following currency pairs: USD:ALL, USD:AUD, USD:BAM, USD:BHD, USD:BND, USD:EUR, USD:GBP, USD:IRR, USD:ISK, USD:KWD, USD:KZT, USD:LKR, USD:MKD, USD:MUR, USD:NPR, USD:NZD, USD:OMR, USD:RSD, USD:RUB, USD:TND, USD:TTD, USD:UYU, USD:VEF, USD:XDR.
9/18/23 - Added 6 timeseries from FRED covering core CPI and industry and commodity-specific PPI data
Added 6 new timeseries from FRED to the
- PPIFIS: Producer Price Index by Commodity: Final Demand
- PCU4841214841212: Producer Price Index by Industry: General Freight Trucking, Long-Distance Truckload
- PCU4841224841221: Producer Price Index by Industry: General Freight Trucking, Long-Distance Less Than Truckload
- PCU3313133131: Producer Price Index by Industry: Alumina and Aluminum Production and Processing
- WPU101707: Producer Price Index by Commodity: Metals & Metal Products: Cold Rolled Steel Sheet and Strip
- CPILFESL: (CORE CPI) Consumer Price Index for All Urban Consumers: All Items Less Food & Energy in U.S. City Average
8/10/23 - Added crosswalk to FRED series IDs & 107 new series from GDP, Employment Situation, Housing Starts, and Residential Construction reports
Added a new table,
financial_fred_variable_series_id_crosswalk, that enables a join between Cybersyn’s variable and FRED’s unique series ID
Added new series from the following four reports:
- Gross Domestic Product (data produced by the US Bureau of Economic Analysis)
- Employment Situation (US Bureau of Labor Statistics)
- New Residential Construction (US Department of Housing and Urban Development)
- Quarterly Starts and Completions by Purpose and Design (US Department of Housing and Urban Development
Two columns were added to
financial_fred_attributesto provide better categorization and discoverability:
release_name: The collection, group of data, or report from which a time series originates. This column can be used as a filter to find related series.
release_source: The organization (e.g. FDIC, Federal Reserve) that FRED collects the data from.
- Cover entire FRED timeseries library that is public domain
- Include point-in-time releases, to capture restatements by government agencies (source data)
- Include Cybersyn-specific metadata on releases (to capture Cybersyn data availability)
Last modified 3d ago