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Debt service ratios (quarterly, 32 economies)

BIS debt service ratios — interest payments plus amortisations relative to income, in per cent — for households & NPISHs, non-financial corporations and the private non-financial sector. Bank for International Settlements, BIS Data Portal.

Source: Bank for International Settlements7,182 lignesMis à jour: 22/09/2026
debtcredithouseholdscorporatesfinancial-stability

Qualité

97

Attribution

Bank for International Settlements

Schéma

ColonneTypeDescription
datestringObservation period (the TIME_PERIOD column of the BIS SDMX-CSV response). Monthly series use YYYY-MM; quarterly series use YYYY-QN, stored as the first day of the quarter.
series_idstringBIS area code plus borrower-sector code for debt service ratios, e.g. 'US', 'US.H': the unique identifier of the series in the BIS Data Portal.
series_labelstringBorrower sector from the BIS's own CL_TC_BORROWERS codelist (Households & NPISHs, Non-financial corporations, Private non-financial sector) followed by the economy name from CL_AREA.
valuefloatObserved debt service ratio for the economy, borrower sector and quarter (the OBS_VALUE column). Unit 367: per cent.

Exemple de lignes

dateseries_idseries_labelvalue
1999-01-01AU.HHouseholds & NPISHs — Australia10
1999-04-01AU.HHouseholds & NPISHs — Australia10.1
1999-07-01AU.HHouseholds & NPISHs — Australia10.3
1999-10-01AU.HHouseholds & NPISHs — Australia10.5
2000-01-01AU.HHouseholds & NPISHs — Australia10.8

Télécharger un échantillon

Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).

Utiliser avec un LLM

Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/bis/bis_debt_service_ratios" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/bis/bis_debt_service_ratios").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

Point d’accès API: https://datazimuts.com/v1/datasets/bis/bis_debt_service_ratios

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.