Verifiable official statistics: a blockchain-based approach
Focus
Official statistics underpin monetary policy, financial stability analysis and public accountability. But SDMx, the standard used to disseminate them internationally – has no way for users to check that a data set really came from the issuing institution and has not been altered since publication, for example by third-party platforms or artificial intelligence systems. This paper asks how statistical authorities can give users an independent means of verifying the origin and integrity of published data or series of data, without disrupting the dissemination workflows they operate.
Contribution
We develop and test a method for binding each published SDMX data set to its source using a public blockchain. A cryptographic fingerprint is computed for the data set – and, where needed, for each individual time series within it – and a single summary value covering a batch of data sets is recorded on the XRP Ledger, where it is timestamped and cannot subsequently be altered. The published file itself carries everything needed to check it, including a digitally signed credential identifying the publisher, so a user can confirm both who issued the data and that the figures are unchanged from the file alone plus one lookup on the ledger. We provide an open source reference implementation and an economic model of the cost of running the system.
Findings
On the prototype, publishing takes three to five seconds and verification one to two seconds, fast enough for interactive use and for automated systems that consume data in real time. These figures describe a proof of concept rather than a hardened production system. The cost analysis shows that the on-chain fees are negligible once modest batches are used, since a single ledger entry can cover thousands of data sets, leaving ordinary processing and storage as the dominant costs. The practical trade-off is between batching for cost efficiency and the delay it imposes on urgent releases, for which we derive an optimal batch size. Because only fingerprints, never the underlying data, are placed on the ledger, confidentiality is preserved, and the same approach extends to other structured reporting formats such as XBRL.
Abstract
International organisations including the Bank for International Settlements (BIS) have adopted SDMx (Statistical Data and Metadata) as the standard for exchanging official statistics. Trust in published data is essential for evidence-based policymaking. This paper shows how binding each SDMx dataset to its source using blockchain technology can enhance confidence in official statistics. We present a proof of concept implemented on the XRP Ledger (XRPL) and contribute, as an integrated whole, (i) an SDMx native canonicalisation and per- hashing pipeline; (ii) a domain-separated Merkle aggregation scheme for batched anchoring; (iii) a self-contained, identity-bound verification artefact in which the SDMx message itself carries both the ordered Merkle leaves and a W3C Verifiable Credential signed by a publisher identity key cryptographically bound to the publisher’s XRPL address via an on-chain attestation registry, so that any consumer can re-derive the anchored root and verify the publisher’s identity from the file alone plus a single ledger lookup; (iv) an open-source XRPL-based reference implementation; and (v) a cost model that captures the batch size / latency / fee trade-off and is solved for an economically optimal batch size. The system enables near real-time data verification, provides cryptographic integrity guarantees, and establishes a foundation for future extensions, including zero knowledge proofs and automated verification by AI agents. Measurements on the prototype show median publication latency of 3–5 seconds and verification latency of 1–2 seconds under the controlled test conditions. The approach is data-format-agnostic and can be extended to other structured statistical or regulatory formats.
