Bringing Structure to Municipal Bond Identification: Why Series-Level FIGI Matters

By Karen Cacella, Steven Meizanis  June 22, 2026

Municipal finance has changed significantly over the past 5 years. Deals are becoming increasingly complex, with multiple series associated within a single offering, and each series including numerous bonds – typically with different maturities, coupons, taxable-status and structures. Market participants – municipal issuers, underwriters, portfolio management, risk managers, and regulators all regard the bonds within a series as components of a single economic unit. Until now, associating individual bonds with their series has been a significant data management challenge.

Figure 1.

Let’s consider a series with 23 individual bonds (Figure 1).  When each bond is identified independently, it creates a data management challenge in recognizing that all bonds belong to the same series. A market participant with an interest in one or two of the bonds (e.g., bonds with maturity 7/1/2026 and 7/1/2046) may see changes in prices or spreads in those individual bonds. Without a clear hierarchy that relates the bonds to the series, it is impossible to deduce from a risk or portfolio management perspective whether the pricing moves are due to changes in the yield curve or an indication of changes in the outlook of the macro-view of the series (e.g., all 23 bonds in the series) or even the issuer. There is a fundamental disconnect - market participants are forced to work at the security level, even though the municipal’s bonds need to be understood as part of a broader issuance.

The Financial Instrument Global Identifier (FIGI) is an innovative open-source meta-data driven standard designed to provide unique, persistent financial instrument identification. Interoperable with other systems that provide simple instrument-level identification, FIGI provides hierarchical granularity to provide context needed to manage data effectively and unearth insights. For example, in equities, the FIGI provides a share class, a country and an individual exchange level view enabling market participants to track a security at different levels of its lifecycle and trading environment. FIGI provides a deal/facility hierarchical structure designed to manage the complexities of syndicated loans. In municipal finance, FIGI is evolving alongside the market with a new innovative hierarchy that identifies the relationships between bonds and their series. This structure establishes the connections that make municipal bonds AI-ready.

Today, market participants rely on identifiers that are assigned at the security level. While effective for identifying individual bonds, they do not provide a standardized way to link all maturities within the same series. As a result, bonds within the series are treated as disconnected instruments. Aggregating data across the series requires manual mapping, internal logic, or reliance on proprietary naming conventions. These are real costs. Proprietary naming conventions require internal support. And, because the mappings probably will vary across organizations – proprietary approaches lack interoperability. This introduces fragmentation, duplication, and inconsistency into datasets, making it more difficult to achieve a coherent view of municipal issuance, secondary-market bond performance, and risk.

This challenge extends beyond operations and is reflected in market outcomes. Academic research shows that increasing complexity in municipal bond disclosures is associated with higher borrowing costs, greater yield volatility, and reduced market efficiency, particularly for investors with limited resources to process information.[1] With nearly half of bonds held by individual investors and no standardized disclosure format, complexity creates real challenges in how information is interpreted and priced. The absence of a clear structural framework linking bonds within a series further compounds this issue, making it more difficult to contextualize risk, aggregate data, and derive consistent insights across an issuance.

A unique Financial Instrument Global Identifier (FIGI) is assigned to each of the nearly one million active municipal bonds. This provides precise, instrument-level identification across the market. However, while these identifiers effectively distinguish individual bonds, they do not on their own provide a standardized way to link those bonds back to the broader series under which they were issued.

This challenge has real data management implications for market participants and regulators. Without a standardized way to identify a municipal bond series, there is no single reference point that enables consistent aggregation across analytics, trade communication, and surveillance workflows. Each organization is left to construct its own approach, leading to expensive overhead and potential data quality concerns. Moreover, with the growing population of bonds issued within series structures, the lack of standardized series-level identification and alignment across the market further compounds these challenges.

Until now.

Series-Level FIGI (e.g., Figure 1 – BBG020RFSSH4) addresses this structural gap by introducing a standardized identifier, based on the offering documentation, that links all (23) bonds issued as part of the series. Rather than replacing existing identifiers, Series-Level FIGI complements them (e.g., FIGI, CUSIP, ISIN, etc.) by adding a new interoperable layer of structural identification. Individual bonds continue to be identified at the security level, while the series-level identifier provides a consistent way to group those instruments into a single, connected group. This enables both granular identification and issuance-level aggregation within the same framework. Series-Level FIGIs are backfilled to the 1960s for analytics, historical and AI-application purposes.

The impact is meaningful. By linking all maturities within a series, Series-Level FIGI provides a more holistic view of municipal bond issuances, allowing market participants to analyze pricing, liquidity, and trading activity across the full structure of the series rather than in isolation. It improves data consistency by removing the need for manual mappings and custom logic, providing a shared reference point across systems and datasets. It also reduces operational complexity, simplifying aggregation and reporting workflows while lowering the risk of reconciliation errors.

For regulators, the ability to view an issuance holistically enhances oversight and transparency. Monitoring market behavior across the full structure of a bond series becomes more straightforward, supporting more effective surveillance and analysis. For market participants, it enables better risk and exposure management by allowing positions to be understood at the series level rather than only at the individual security level.

Ultimately, Series-Level FIGI aligns data with the evolution of municipal finance. Rather than treating bonds as isolated records, it enables them to be understood as part of a connected structure that reflects how they are issued, traded, and analyzed in practice. AI is enabled to unearth insights at a higher and deeper level. As markets continue to evolve, extending identification frameworks to better represent real-world structures is a natural step toward more efficient, consistent, and transparent financial data.

Series-Level FIGI enables the municipal market to treat a bond issuance as a single, connected structure, rather than a collection of disconnected securities.

[1] Farrell, M., Murphy, D., Painter, M., and Zhang, G. (2023), “The Complexity Yield Puzzle: A Textual Analysis of Municipal Bond Disclosures.”