April 9, 2018

Banks’ Balance Sheets Data

Bank balance sheets and income statements are able to describe the operational structure of a bank. In some cases balance sheets also report information regarding banks’ foreign operations, making these data suitable to explore banks’ international linkages. Due to regulatory reasons, banks usually report their balance sheet data directly to central banks and regulatory agencies. Many countries make these data available for researchers and offer the chance of conducting research at the bank level.

Links to data sources

Bank balance sheet data (BankFocus)

Provides bank balance sheet and income statement data for banks and non-bank financial institutions worldwide. Offers different variables measuring this (e.g. net interest income, operating profit, loans, off-balance sheet items). Database delivers comparable data (a standardized format) for private and public banks across countries. Contains data for 44.000 banks worldwide and has up to 16 years of data for each bank.
Data Provider: BankFocus
Level/Frequency: Bank-Level Data
Geographic Coverage: World
Time Range: n.a.
Availability: No free access to data

Bank balance sheet data (S&P Global Market Intelligence)

Provides in-depth data for banking, insurance industries, and financial services. The provided real time data for the global financial industry are in a standardized format, such that they can be compared more easily across different countries.
Data Provider: S&P Global Market Intelligence (former SNL Financial)
Level/Frequency: Bank-Level Data / Real time
Geographic Coverage: World
Time Range: n.a.
Availability: No free access to data
Where has it been used? ECB Financial Stability Review – November 2014

Bank balance sheet data, market data (Datastream, Thomson Reuters)

Provide current and historical data on bank-level on a daily basis. Include information on market capitalization and stock returns for international markets. Also deliver data on bonds, trading volumes, options, currencies and market indices.
Data Provider: Datastream /Thomson Reuters
Level/Frequency: Bank-Level Data / Daily
Geographic Coverage: World
Time Range: n.a.
Availability: No free access to data

Banking Organization Systemic Risk Report (FR Y-15)

The FR Y-15 is the Banking Organization Systemic Risk Report, which is filed by 33 large U.S. bank holding companies (BHCs), savings and loan holding companies (SLHCs) with total consolidated assets of $50 billion or more, foreign banking organizations (FBOs) with combined U.S. operations that total $50 billion or more in assets as of the June 30th prior to the December 31st as-of date and any U.S.-based organizations identified as global systemically important banks (G-SIBs as of November 1, 2012) that do not otherwise meet the consolidated assets threshold for BHCs. The FR Y-15 is filed annually as of the last calendar day of December starting 2013. The data items collected in this report mirror those developed by the Basel Committee on Banking Supervision (BCBS) to assess the global systemic importance of banks indicating size, interconnectedness, substitutability, complexity and cross-jurisdictional activity.
Data Provider: The National Information Center (NIC)
Level/Frequency: Bank-Level Data / Annually
Geographic Coverage: United States  
Time Range: since 2013, regularly updated
Availability: Free access online

Bundesbank BISTA (Deutsche Bundesbank)

It lists domestic banks’ assets and liabilities based on the books at the end of the month. Also provides assets and liabilites of foreign branches and subsidiaries of German banks. They thus represent the most comprehensive statistical survey of the banking industry in Germany and are at the core of the banking statistics reporting system.
Data Provider: Deutsche Bundesbank
Level/Frequency: Bank-Level Data / Monthly
Geographic Coverage: Germany
Time Range: since 1993, regularly updated
Availability: Available upon project-application at the Research Department of the German Bundesbank.

Capital Assessments and Stress Testing Information Collection

FR Y-14 consists of the FR Y-14A, Q, and M reports. The FR Y-14A report collects detailed data on bank holding companies’ (BHCs), savings and loan holding companies’ (SLHCs), and intermediate holding companies’ (IHCs) quantitative projections of balance sheet assets and liabilities, income, losses, and capital across a range of macroeconomic scenarios and qualitative information on methodologies used to develop internal projections of capital across scenarios. The FR Y-14Q collects detailed data on BHCs’, IHCs’, and SLHCs’ various asset classes, capital components, and categories of pre-provision net revenue (PPNR). The FR Y-14M report collects monthly detailed data on BHCs’, IHCs’, and SLHCs’ loan portfolios. The report is comprised of three loan- and portfolio-level collections, and one detailed address matching collection. The data are used to assess the capital adequacy of large firms using forward-looking projections of revenue and losses, to support supervisory stress test models, and continuous monitoring efforts as well as to inform the Federal Reserve’s operational decisionmaking as it continues to implement the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010.

Data Provider: Board of Governors of the Federal Reserve System
Level/Frequency: Firm/loan-level, yearly/quarterly/monthly
Geographic Coverage: United States
Availability: No free access to data
Where has it been used? Ivanov, I.T., M. S. Kruttli, and S. W. Watugala (2022). Banking on Carbon: Corporate Lending and Cap-and-Trade Policy. Available at SSRN: https://ssrn.com/abstract=3650447.

Credit Register Data, Example: Spain (CIRBE)

Contains monthly data about all loans with a value over 6000 Euros that are granted by all credit institutions in Spain (commercial, saving and cooperative banks as well as credit finance establishments). It also includes information about certain characteristics of each loan (e.g. instrument, currency) and information about each borrower (e.g. province and sector). Data is on bank-level and provides very detailed information on lending activities of individual banks. Data is not freely available and is just available for individual countries.
Data Provider: Credit Register of the Bank of Spain (CIRBE)
Level/Frequency: Bank-Level Data / Monthly
Geographic Coverage: Spain  
Time Range: n.a.
Availability: Limited access
Where has it been used? Jiménez, G., V. Salas, and J. Saurina (2006).  Determinants of Collateral. Journal of Financial Economics 81(2): 255‐281.

Financial Structure Dataset (Worldbank)

Provides country-level data on financial development and structure. Includes in total 31 indicators that measure e.g. size, efficiency as well as activity of financial intermediaries and markets.
Data Provider: World Bank
Level/Frequency: Country-Level Data / Yearly
Geographic Coverage: World  
Time Range: 1960-2015
Availability: Free access online
Where has it been used? Čihák, M., A. Demirgüç-Kunt, E. Feyen and R. Levine (2012). Benchmarking Financial Development around the World. World Bank Policy Research Working Paper 6175.

Funding of the Irish Domestic Banking System

Information on foreign and domestic banks operating in Ireland including the bank’s assets, funding and their composition of sources and type of liabilities. Irish Central Bank’s money and banking statistics as well as composition and source of interbank funding.
Data Provider: Philip R. Lane (Trinity College Dublin)
Level/Frequency: Bank-Level / aggregate Data – annually / quarterly / monthly (depending on type)
Geographic Coverage: Ireland 
Time Range: 2000/03 – 2008 (differs across variables)
Availability: Free access online
Where has it been used? Philip R. Lane (2015).  The Funding of the Irish Domestic Banking System During the Boom.  Journal of the Statistical and Social Inquiry Society of Ireland  forthcoming.

Global Financial Development Database (Worldbank)

Provides data on depth, access, efficiency as well as stability of financial institutions and financial markets. Also delivers measures of competition and concentration in the banking sector. Includes data for 214 economies and contains annual data for the period 1960 – 2021.
Data Provider: World Bank
Level/Frequency: Country-Level Data / Yearly
Geographic Coverage: World
Time Range: 1960-2021
Availability: Free access online
Where has it been used? Čihák, M., A. Demirgüç-Kunt, E. Feyen, and R. Levine (2012). Benchmarking Financial Systems Around the World. Worldbank Policy Research Working Paper 6175.

Uniform Bank Performance Report (FFIEC)

Provides bank-level data for commercial and saving banks in the USA. Offers data e.g. on balance sheets, liquidity and asset quality. It also provides data for a comparison of the performance of an individual bank against a comparable group of peer-banks and against itself over time.
Data Provider: Federal Financial Institutions Examination Council (FFIEC)
Level/Frequency: Bank-Level Data / Quaterly
Geographic Coverage: USA
Time Range: since March 2001, regularly updated
Availability: Free access online

Fintech and big tech credit database

Compiles information on fintech and big tech operations, whose emerging has considerably transformed the credit market system in the past years, complementing and replacing traditional bank lending. This dataset records credit volumes of these alternative lending practices between 2013 and 2019 for a wide range of countries.
Data Provider: Giulio Cornelli, Jon Frost, Leonardo Gambacorta, Raghavendra Rau, Robert Wardrop and Tania Ziegler
Level/Frequency: Country-Level Data / Yearly
Geographic Coverage: 79 countries worldwide
Time Range: 2013-2019
Availability: Free access online
Where has it been used? Cornelli, G., Frost, J., Gambacorta, L, Rau, R., Wardrop, R. and Ziegler, T. (2020). Fintech and big tech credit: a new database. BIS working paper 887.

Data on Brazilian banks and other regulated financial institutions (GitHub)

The R package compiles publicly-available data on Brazilian banks and other regulated financial institutions. This panel dataset includes information ranging from total assets to number of physical branches to the growth in credit to specific economic sectors according to a maturity bucket.
Data Provider: Central Bank of Brazil
Level/Frequency:   Yearly/ Quarterly Data
Geographic Coverage: Brazil
Time Range:
Availability: Free access online

The full set of geo-coded bank branches in China (GitHub)

Provides a set of geo-coded bank branches in China from official sources. The data spans between 1948 and 2016. The geocoding service from Gaode Map is used to obtain the coordinates (latitude, longtitude) for each bank branch.
Data Provider: Sibo Liu
Level/Frequency: Bank-Level Data / Yearly
Geographic Coverage: China
Time Range: 1948-2016
Availability: Free access online