Quarterly non-bank outstanding residential mortgages by insurance status, amortization period, total debt service ratio, loan-to-value and, days in arrears, by lender type and number of mortgages, displayed in thousands of dollars, unless otherwise specified.

Graph and download economic data for Non-Bank Financial Institutions' Assets to GDP for United States (DDDI03USA156NWDB) from 1960 to 2020 about nonbank, finance companies, companies, finance, financial, assets, GDP, and USA.

This API is providing other Mainland-related non-bank exposures in Mainland-related lending and other non-bank exposures.

In 2023, there were *** million non-bank loan holders in Poland, an increase compared to the previous years.

Bangladesh Loan: Disbursement: Non Bank Financial Institutions data was reported at 13.900 BDT bn in Sep 2019. This records a decrease from the previous number of 17.400 BDT bn for Jun 2019. Bangladesh Loan: Disbursement: Non Bank Financial Institutions data is updated quarterly, averaging 9.950 BDT bn from Sep 2004 (Median) to Sep 2019, with 61 observations. The data reached an all-time high of 52.300 BDT bn in Dec 2018 and a record low of 3.100 BDT bn in Sep 2004. Bangladesh Loan: Disbursement: Non Bank Financial Institutions data remains active status in CEIC and is reported by Bangladesh Bank. The data is categorized under Global Database’s Bangladesh – Table BD.KB005: Banking Sector: Loans.

Graph and download economic data for Non-Bank Financial Institutions' Assets to GDP for Indonesia (DDDI03IDA156NWDB) from 2009 to 2021 about nonbank, Indonesia, finance companies, companies, finance, financial, assets, and GDP.

As of October 2024, monetary financial institutions (MFI) granted most of the lending to individuals in the United Kingdom (UK). Meanwhile, other non-bank lenders gave approximately *** million British pounds worth of loans just in March 2024. During the past years, non-bank lenders have been increasing their market share. Non-MFI lenders also had a growing market share of the new consumer lending market in the UK.

Quarterly non-bank outstanding residential mortgages, for Canada and provinces, displayed in thousands of dollars, unless otherwise specified.

Quarterly non-bank residential mortgages extended by type of increase and new funds advanced by term to maturity, by insurance status, by lender type and number of mortgages, displayed in thousands of dollars, unless otherwise specified.

As of March 2024, approximately ***** million accounts of the non-bank personal loan under the supervision of the Bank of Thailand took on loans that did not cover hire purchases and leasing of automobiles and motorcycles. In the same period, the total number of personal loan accounts with non-banks amounted to approximately ***** million.

In June 2025, most consumer loans in the United Kingdom (UK) were granted by monetary financial institutions (MFI). Nevertheless, other lenders gave over 12.7 billion British pounds worth of consumer credit. During the past years, non-bank lenders have been increasing their market share. Credit cards made up most of the new monthly consumer lending in the UK.

Graph and download economic data for Non-Bank Financial Institutions' Assets to GDP for Trinidad and Tobago (DDDI03TTA156NWDB) from 1960 to 2021 about nonbank, Trinidad and Tobago, finance companies, companies, finance, financial, assets, and GDP.

This API is providing Mainland-related lending by type of AIs in Mainland-related lending and other non-bank exposures.

China Loan: New Increased: Non Bank Financial Institution data was reported at -170.200 RMB bn in Mar 2025. This records a decrease from the previous number of 284.400 RMB bn for Feb 2025. China Loan: New Increased: Non Bank Financial Institution data is updated monthly, averaging -9.900 RMB bn from Jan 2015 (Median) to Mar 2025, with 123 observations. The data reached an all-time high of 886.400 RMB bn in Jul 2015 and a record low of -338.600 RMB bn in Jan 2019. China Loan: New Increased: Non Bank Financial Institution data remains active status in CEIC and is reported by The People's Bank of China. The data is categorized under China Premium Database’s Money and Banking – Table CN.KB: Loan.

These data relate to new mortgage lending on residential property in Ireland on an annual basis. Data relates to those institutions [(banks and non-bank mortgage lenders)] who issue at least €50 million of new mortgage lending in a six-month period and are subsequently required to submit loan-level information to the Central Bank for the purposes of the macroprudential mortgage measures. The value and volume of new lending is provided, by borrower type, along with the distribution of lending by Loan-to-value and Loan-to-income ratio. Average characteristics are also provided. These data do not constitute official statistics. These data are published to support transparency and understanding of market developments.

The analysis considers the role of non-performing loans (NPLs) for bank lending rates on newly granted loans. It is based on euro area data. The focus is on an effect caused by the stock of NPLs that extends beyond losses that banks have already incorporated into their reported capital positions. The paper assesses the channels through which such an effect occurs most importantly whether it runs through banks' idiosyncratic funding costs.

File 0 contains a description of the data used for the analysis. It does not contain actual data as most data used for the analysis is confidential. The file contains the names of the Stata-dta-Files in which the datasets are stored. These Stata-dta-Files are the starting point for the data processing which is activated by the code in the subsequent Stata-do-Files.

Files 1-3 contain the code for processing SNL and Bankscope / Orbis data. This data includes the banking group level data for the analysis (most importantly NPL / regulatory capital data). File 1 contains the code for the processing of SNL data. File 2 contains the code for the of the Bankscope / Orbis data. File 3 contains the code for merging SNL and Bankscope / Orbis data.

Files 4-6 contain the code for processing the CSDB data which includes data on the cost of bond funding on the banking group level, iBSI / iMIR data which includes data on lending rates and lending volumes on the single bank level and the macroeconomic data. File 4 contains the code for the processing of the CSDB data. Note that this data is initially on the single security level and is processed such, that information on costs of bond funding on the banking group level is retrieved. File 5 contains the code for the processing of the iBSI / iMIR data. File 6 contains the code for the processing of the macroeconomic variables.

File 7 contains the code for merging all datasets. File 8 contains the code for producing the descriptive statistics in Section 3 of the paper. File 9 contains the code for the estimation of Equations 1 and 3 of the paper. File 10 contains the code for the estimation of Equations 1 and 3 with random samples (Appendix D of the paper). File 11 contains the code for estimations with loan growth as dependent variable (Section 5.2 of the paper).

Files 12 and 13 contain code for the data processing and estimation of Equation 2 on the banking group level.

Spain NF: Demand: Factors: Use of Alternative Finance: Loans from Non Banks data was reported at 0.000 % in Sep 2018. This stayed constant from the previous number of 0.000 % for Jun 2018. Spain NF: Demand: Factors: Use of Alternative Finance: Loans from Non Banks data is updated quarterly, averaging 0.000 % from Dec 2002 (Median) to Sep 2018, with 64 observations. The data reached an all-time high of 5.000 % in Sep 2017 and a record low of -5.000 % in Sep 2016. Spain NF: Demand: Factors: Use of Alternative Finance: Loans from Non Banks data remains active status in CEIC and is reported by Bank of Spain. The data is categorized under Global Database’s Spain – Table ES.KB011: Bank Lending Survey: Non Financial Corporations.

Replication package for "Nonbank lenders as global shock absorbers: Evidence from US monetary policy spillovers", by David Elliott, Ralf Meisenzahl, and Jose-Luis Peydro, published in Journal of International Economics (2024).

Bangladesh Loan: Outstanding: Non Bank Financial Institutions data was reported at 305.300 BDT bn in Sep 2019. This records an increase from the previous number of 298.200 BDT bn for Jun 2019. Bangladesh Loan: Outstanding: Non Bank Financial Institutions data is updated quarterly, averaging 96.350 BDT bn from Sep 2004 (Median) to Sep 2019, with 61 observations. The data reached an all-time high of 305.300 BDT bn in Sep 2019 and a record low of 28.100 BDT bn in Sep 2004. Bangladesh Loan: Outstanding: Non Bank Financial Institutions data remains active status in CEIC and is reported by Bangladesh Bank. The data is categorized under Global Database’s Bangladesh – Table BD.KB005: Banking Sector: Loans.

Thailand Others: DF: Non-banks data was reported at 0.000 THB mn in Sep 2018. This stayed constant from the previous number of 0.000 THB mn for Jun 2018. Thailand Others: DF: Non-banks data is updated quarterly, averaging 0.000 THB mn from Dec 2017 (Median) to Sep 2018, with 4 observations. Thailand Others: DF: Non-banks data remains active status in CEIC and is reported by Fiscal Policy Office. The data is categorized under Global Database’s Thailand – Table TH.F025: Government Finance Institutions: Loan by Type of Debtor.