What is SDMX?

SDMX (Statistical Data and Metadata eXchange) is the international standard for exchanging statistical data and metadata. Central banks, statistical offices and international organisations use it to collect, share and publish statistics such as monetary, balance of payments and national accounts data.

Guide · Updated 2 November 2026 · By Jess Luper

How SDMX works

SDMX describes statistics with a small set of building blocks.

01Data structure definitionsThe shape of a dataset: its dimensions, attributes and measures.
02Code listsAgreed values for each dimension, such as countries, sectors, instruments and currencies.
03DataflowsA named stream of data that follows a structure, such as monthly bank balance sheet statistics.
04Exchange formats and APIsThe same data can travel as SDMX-ML, SDMX-JSON or SDMX-CSV, and be queried through a standard web API.
8sponsoring bodies, including the BIS, ECB, IMF, OECD and World BankSDMX →
ISO 17369SDMX is an international standardSDMX →
2013first global SDMX data exchanges, for national accounts, balance of payments and FDISDMX →

SDMX vs XBRL

XBRL grew out of business reporting: facts reported by individual firms in filings. SDMX grew out of official statistics: series across time, countries and sectors. Many central banks run both, with XBRL for supervisory returns and SDMX for statistical collection and publication, and too often they collect overlapping data from the same firms twice.

Who uses SDMX

SDMX is sponsored by the BIS, the ECB, Eurostat, the ILO, the IMF, the OECD, the UN Statistics Division and the World Bank (SDMX). Central banks use it to report to these bodies, to exchange data with each other and to publish their own statistics. Its first version was completed in 2004, and it is now an ISO standard.

Supervisory and statistical teams often collect the same numbers twice. They do not have to.

Where AI fits, and where people decide

AI can help map local classifications to standard code lists and answer plain-language questions about published series, citing the exact series it used. It must never produce a number that does not exist in the data. Statisticians and supervisors approve mappings and own the published figures.

Put it to workJoining up statistical and supervisory data
  1. 1Map which statistical series and supervisory returns draw on the same firm data.
  2. 2Agree shared code lists for sectors, instruments and currencies across both teams.
  3. 3Collect once and derive both views, instead of asking firms twice.
  4. 4Keep lineage, so any published statistic can be traced to the filings behind it.
  5. 5Publish through an SDMX API so others can reuse the data without asking.

Where Line4 fits

Line4 is a SupTech platform for financial regulators. It collects returns in XBRL, Excel and CSV, validates them against your taxonomies and rules at the point of submission, and puts AI to work reading them, with supervisors making every decision. If you work with a standard we have not yet run in production, we will say so plainly and show you how we would approach it.

Questions

What is SDMX?

SDMX (Statistical Data and Metadata eXchange) is an international standard, ISO 17369, for exchanging and sharing statistical data and metadata between organisations.

Who sponsors SDMX?

Eight international bodies: the BIS, the ECB, Eurostat, the ILO, the IMF, the OECD, the UN Statistics Division and the World Bank.

What is the difference between SDMX and XBRL?

XBRL is used mainly for reports from individual firms, such as financial statements and supervisory returns. SDMX is used mainly for statistical series across time, countries and sectors. Central banks often use both.

Do supervisors use SDMX?

Central banks use SDMX widely for statistical collection and exchange. Where statistical and supervisory teams collect overlapping data, a shared data model lets them collect once and serve both.