Credit-to-GDP Ratio
Get the total credit to a non-financial sector as a share of GDP: all loans and debt securities owed by households, non-financial corporations or the government, whoever the lender is (banks, other financial institutions, foreign lenders or bond holders). It measures how leveraged an economy is and where the debt sits, such as the high corporate debt in China or the high household debt in Australia and Canada.
Unlike bank lending alone, it also counts market and cross-border funding, so it is comparable across countries where companies borrow from banks (the euro area, Japan) and where they issue bonds (the United States). The data is compiled by the Bank for International Settlements for around 45 economies, quarterly and back to the 1940s for some, from national financial accounts. No API key is needed.
See definition: https://data.bis.org/topics/TOTAL_CREDIT and https://www.bis.org/publ/qtrpdf/r_qt1303h.htm
Also known as: total credit to GDP, debt to GDP by sector, private debt to GDP, leverage ratio of the economy.
Credit-to-GDP Ratio in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_credit_to_gdp_ratio as shown below.
from financetoolkit import Economics
economics = Economics(start_date='2025-01-01', end_date="2025-12-31")
economics.get_credit_to_gdp_ratio(countries=['United States', 'Euro Area', 'China', 'Japan'])
Or, after setting up the Finance Toolkit MCP, ask:
How large was private sector credit relative to GDP in the United States, the euro area, China and Japan in each quarter of 2025?
Which returns:
| United States | Euro Area | China | Japan | |
|---|---|---|---|---|
| 2025Q1 | 1.416 | 1.553 | 2.019 | 1.71 |
| 2025Q2 | 1.41 | 1.545 | 2.018 | 1.701 |
| 2025Q3 | 1.406 | 1.537 | 2.015 | 1.713 |
| 2025Q4 | 1.402 | 1.533 | 2.008 | 1.734 |
Parameters
get_credit_to_gdp_ratio accepts the following parameters.
| Parameter | Type | Description | Example |
|---|---|---|---|
countries | list[str] | str | None | The countries to include in the data. Defaults to None. | ["United States", "Germany"] |
borrowers | str | The borrowing sector: “private” (households and non-financial corporations), “households”, “corporations” (non-financial corporations), “government” (at nominal value) or “non_financial” (all three together). Defaults to “private”, the measure behind the credit-to-GDP gap. | "private", the measure behind the credit-to-GDP gap |
rolling | int | The rolling window size to use for smoothing the data (simple moving average). Defaults to None. | 4 |
trailing | int | The trailing window size to use for summing the data over trailing periods. Defaults to None. | 4 |
growth | bool | Whether to return the growth data or the actual data. Defaults to False. | True |
lag | int | The number of periods to lag the data by. Defaults to 1. | 4 |
standardize | bool | Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False. | True |
rounding | int | None | The number of decimals to round the results to. Defaults to None. | 2 |