DPC DATA tool to map directly to underlying obligors of muni debt

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DPC DATA is rolling out an obligor- and sector-mapping methodology tool to identify the direct obligor in each muni transaction, with its only criterion being 'credit,' as part of its MuniCREDIT Solutions portfolio.

It then will re-map all sector classifications based on this identification, the firm said.

The new product is an offshoot of development work on financial data DPC DATA has been collecting and working on, said President Ken Hoffman.

The new product is an offshoot of development work on financial data that DPC has been collecting and working on in the past few years, said DPC DATA President Ken Hoffman. This particular tool has been under development for the past year.

“Anyone in the muni market knows there is a lot of legacy reference data we have now that does not have a consistent way to identify or drill down into the underlying obligors,” said Triet Nguyen, vice president of strategic data operations at DPC. “Legacy systems often simply identify purpose but not who the obligor is. Who is paying the debt service? All too often, they default to vague categories such as 'Facilities' or even 'Miscellaneous,’” he said. “This is an industry problem we’re trying to solve.”

The two largest reference providers in the muni space are Bloomberg and ICE, which are widely used across the municipal market.

All existing obligor identification systems typically rely on the issuer itself, the borrower/guarantor, the security pledge, the purpose and use of bond proceeds and the party responsible for disclosure compliance. DPC’s view is that the borrower and the security pledge stand out as the basis for identifying the ultimate obligor.

Nguyen said bond pricing is probably one of the primary applications for this new tool. Participants have been having problems trying to find comparable trades and DPC’s goal is to help them drill down to find better reference data, he said.

DPC DATA identified four areas the tool is expected to address: Risk identification and aggregation; compliance with investment diversification rules; trading; and bond pricing and evaluation.

“Accurate obligor identification can allow any matrix-based bond evaluation system to improve pricing accuracy and reduce manual intervention by pricing analysts,” a release said.

The goal is to identify the sector and subsector, focus on the nature of the borrower and or the pledged revenue source and not on use of proceeds.

As an example, DPC pointed to linking an enterprise fund obligor to the host general government obligor, for example Chicago water revenue bonds to the City of Chicago. The Chicago Water Authority can be found under the umbrella of the city itself, but is clearly a different obligor than the city.

Another example is to link a municipal pool program or bond bank to the individual credit of each participant in those pools or the joint action agency to the participant obligors.

Nonprofit higher-ed and healthcare deals, issued through conduits, are also examples of what data the tool seeks to provide.

Ronak Patel, vice president of product management, said the obligor and sector data is mapped to the CUSIP-9 level.

It’s currently tough to do comparisons between two entities and two different sectors, such as healthcare, comparing hospitals to assisted living facilities, he said.

“It’s not as simple as comparing two different types of revenue streams. You cannot compare cities and counties, who rely on property taxes as their primary source of revenue, to that of states that do not,” Patel said.

At this point, the tool is a stand-alone data feed that users can integrate into their own systems; however the goal is to eventually build out a user interface.

“We have been trying to at least correctly identify the correct obligors with about 100 sectors and subsectors to have something more precise that, say, the broker-dealer side can trade off of,” Patel said.

There is a lot of granularity to the sector classification, Nguyen said. “Analytically, it will be very fascinating to see how people use it. In the current environment, they can quickly identify their portfolio exposure to sectors most affected by COVID-19, such as Dedicated Tax issues, etc.”

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