Transparency first: why open-data infrastructure must precede large-scale reconstruction capital
A policy brief on the sequencing of recovery financing for Ukraine
Ukraine's recovery will require an unprecedented inflow of capital from international partners, private investors, and state programmes. Yet the experience of previous post-conflict reconstructions reveals a pattern: when large sums arrive before transparency infrastructure — open data, shared assessment methodologies, and spending-tracking mechanisms — is in place, the risk of misallocation, duplication, and abuse rises, and donor trust is quickly exhausted. In this brief we make the case for a sequencing in which investment in transparency precedes large-scale reconstruction capital. Drawing on recognised methodologies for assessing damage, loss, and needs (the World Bank RDNA and DaLA) and on the principle of open by default, we show that transparency should be regarded not as an administrative burden but as infrastructure that lowers the cost of capital, accelerates decisions, and makes reconstruction verifiable. The brief is addressed to donors, international financial institutions, and the bodies responsible for coordinating recovery.
Key messages
- Capital poured into reconstruction before transparency infrastructure is built systematically raises the risk of inefficient spending and lost donor trust.
- Open data and spending traceability are not an add-on to reconstruction but a precondition for it: they lower the cost of attracting capital and accelerate decisions.
- A shared assessment methodology (RDNA/DaLA) and open datasets make comparison across sectors and periods possible and verifiable.
Recommendations
- 1Introduce a shared, open methodology for assessing damage, loss, and needs (based on RDNA/DaLA) as a mandatory condition of coordinated financing.
- 2Build and fund open-data and spending-tracking infrastructure before or alongside the deployment of large-scale capital, not after it.
- 3Make open by default the norm: datasets, methodologies, and assessment results should be public and machine-readable.
- 4Provide for independent peer review and audit of assessment methodologies so that the figures underpinning decisions withstand external scrutiny.