Bloomberg today announced the launch of its Impact & Allocation dataset for sustainable fixed income investors, a new offering that transforms fragmented issuer disclosures into normalized, instrument-level data on how sustainable bond proceeds are allocated and their outcomes.

The labeled bond universe has grown to $5.9 trillion for corporate and government bonds according to Bloomberg data, yet post-issuance reporting remains highly fragmented. Issuers publish allocation and impact reports in different formats, using different taxonomies, units, currencies, time horizons and reporting structures. To compare bonds and perform portfolio aggregation, investors need to manually review documents, reconcile issuer-specific language and normalize units.

Bloomberg’s new dataset directly addresses this gap by normalizing post-issuance allocation disclosures into comparable percentages across 22 allocation indicators (such as renewable energy, clean transportation, green buildings, biodiversity, and affordable housing) and 15 key performance impact indicators (such as GHG emissions reduced or avoided, renewable energy generated, and water saved). Processing more than 800,000 manually captured reported data points, the dataset delivers field values for 8,000 instruments across corporate and sovereign bonds.

Joshua Kendall, Head of Sustainable Fixed Income at Bloomberg, said:

“For investors in sustainable fixed income, understanding where funds are allocated and what impact they achieve is essential. Until now, investors had to manually review issuer documents and reconcile complex, inconsistent disclosures to compare bonds and assess entire portfolios. Bloomberg’s normalized Impact & Allocation dataset transforms this fragmented information into decision-ready data, giving investors a clear view of where capital was deployed and the impact reported by issuers.”

Bloomberg’s Impact & Allocation dataset is available on the Bloomberg Terminal via {ESGD <GO> or ASKB, Bloomberg’s new conversational AI interface, as well as via Data License.