Rimes Technologies is launching a new data solution for exchange-traded funds (ETFs) to its Managed Data Service.

Through the service, Rimes’ data development team ingests data directly from the ETF issuer, normalizes it, validates it, and enriches it with additional datasets that Rimes also captures, such as information on public and private markets, fundamentals, and analytics.

Instead of a client having to perform all of that normalization, transformation and merging of content on their side, Rimes takes on that burden, says Brett Schechterman, head of product for North America at Rimes.

Users can interact with the data through the Rimes Online web portal, which was rolled out earlier this year, or via an API or bulk-data feed.

“We can give you a bulk product—a bulk feed—and you can take it in in feed-ready form, or in an API form. Or, you can say, ‘Hey, I like the data I get from iShares that you guys get from an exposure perspective, but I also want extended analytics and I want you to normalize classifications by GICS [Global Industry Classification Standard] for me across fixed income and equities, because I need to bring it into my data lake to then feed downstream to my compliance and risk platforms,’” he says, as an example. “So there are a variety of different use cases that we’ll work on, but our core competency is ingesting, validating and owning the quality of that content—and managing [changes coming from the providers]—on your behalf.”

Rimes collects data from more than 400 sources and has direct relationships with issuers, such as Vanguard, BlackRock and Invesco, to name a few. The vendor hopes that this managed service will differentiate itself from other ETF data aggregators by having those direct relationships, bringing the data in its native form, and then use its experience in the index space to provide added symbology and cross-referencing capabilities, as well as performing validation checks, data scrubbing techniques, and data enrichment.

We have all the index data and now we have all the ETF data, and we’re basically going to be mapping all the ETF funds to their indices. [Through it] you’ll have that capability of comparing the two and tracking the two over time with returns, with decomposition, allowing you to do much more interactive analysis.

Brett Schechterman

“We are building relationships with [the ETF issuers], region by region. We are onboarding their datasets in the native form [in which] they send their content out of the door, and then we leverage what Rimes has done historically in the index space—that core tech stack and competency that we’ve operated with for 20 years in index land—and extend that to ETFs,” he says. “We have 400 different data partners that we work with, so we have the ability to overlay symbology that other shops can’t do. You might get a single file from one of these aggregators, but there are a lot of blank spaces.”

Rimes is phasing in the service via region, starting with the US, Canada and Europe. Next, the vendor will expand it into Japan, and after that, will roll it out to other Asian countries. According to the company, it sources over 90% of global ETF data directly from sponsors.

Changing Landscape

This release is targeted at buy-side firms and, specifically, around four different use cases.

First is for portfolio management. Schechterman says portfolio managers are using ETFs more aggressively these days for tasks like asset allocation and portfolio construction in order to move risk around more seamlessly.

“As a portfolio manager, you want to know not just the risk that you’re moving around, but you want transparency into what that underlying fund owns,” he says. “This way, you can do much more efficient portfolio construction if you understand what’s contained in those funds.”

Second, risk managers want a full look-through and exposure to everything that they own in order to help with exposure management, stress testing and scenario analysis. “If you have granularity, and you understand the underlying exposures—as opposed to just saying, ‘I’m going to map this ETF to an index and it will give me a ballpark [figure],’ [which is] not going to give you the granularity that you really need because people aren’t buying every single name from an index,” those risk tasks can be performed more accurately, he says.

The third use case is for compliance, specifically around disclosure reporting: “What do I own directly and indirectly [through mutual funds and ETFs]? If you don’t have that look-through capability, you can’t effectively speak to client guidelines or regulatory guidelines for issue concentration risk or sector risk,” Schechterman says.

And finally, he says that buy-side shops are increasingly asking about solutions that can help with performance and attribution measurement.

“People want to decouple ETF performance—especially in passive land, where every basis point counts. I think people really want to get after and understand the performance noise that might exist because of transaction activity and trading,” he says. “Any tracking error that you might have versus your given index, if you have rich exposure detail and look-through capability, you can load it into a performance attribution system and actually get granular detail on, ‘Why did my fund perform a certain way?’ and you can decouple that.”

For the Future, Marriage

Schechterman says that rolling out the Rimes Online portal will eventually enable the vendor to add more microservices to its offering, which it hopes will allow users to interact with the data in new and inventive ways. As the company continues to build its index and ETF datasets, users will be able to compare the two datasets and track them over time through its portal.

Right now, Rimes’ content team is focusing on the top funds by “AUM significance” in each region—rather than looking at each new ETF issuer that pops up on a weekly basis—then will look at those top funds in each region and map those to the corresponding indices.

“We have all the index data and now we have all the ETF data, and we’re basically going to be mapping all the ETF funds to their indices. [Through it] you’ll have that capability of comparing the two and tracking the two over time with returns, with decomposition, allowing you to do much more interactive analysis: ‘Is my manager using a synthetic approach via derivatives to replicate that index? Are they buying every bond or every security in the index? Are they using stratified sampling?” he says. “But this interactive portal is basically our common vessel where we’re building out microservices.”

While Rimes has started to build some mock-up reports that can be seen via the portal, a live rollout is not expected until next year.

“We’ve already have a good cross section of the top funds in each region mapped to their indices where we can look at those internally, but we haven’t released them outbound yet to clients because we’re still working on the navigation components,” Schechterman says. “We have mock-up screens, but we don’t have anybody working with that ETF content. It will probably be something more around Q1 2020 when that’s rolled out more broadly.”