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Keeping Up with Rapid Shifts in Research Management

Data Science and Technology

By Danielle L. Karr  |  May 5, 2021

RMS hub graphic NEW2Research Management Solutions (RMS) is the hub of the cyclical, end-to-end research process and most often serves asset managers, asset owners, and private equity firms of all sizes. Analysts contribute notes that reflect daily monitoring, changes in sentiment due to earnings releases or due diligence updates, shifts in fundamental analysis, and thoughts on new products or strategies. A centralized RMS can allow wealth advisors to stay connected to their research desk. It will often power marketing efforts and satisfy compliance requirements.

While there are of course some commonalities across clients, each firm’s RMS configuration is truly unique, reflecting not just the differentiators of their current research process, but also its next horizon.

As these applications are so impactful to each firm’s day-to-day efficiency as well as long-term outcomes, RMS users are very invested in adopting the latest updates and finding ways to continually refine their workflows. The applications themselves have evolved over the years, based on a constant flow of requests from our clients, which often serve as canaries in the coal mine for new trends and shifts in the market. The pace of these shifts has accelerated massively in the past several years and new requirements of an RMS are centered in a few key areas.

Truly Multi-Asset Class Support

Firms that previously operated with independent teams on opposite ends of the asset manager and asset allocator spectrum are consolidating and seeing operational gains by sharing research in a single location. That location—the RMS—must serve the needs of those writing about everything from equities to fixed income to private companies to managers, funds and strategies, as well as the CIO or Director of Research who wishes to understand the full research landscape and opportunities for efficiency improvement across the teams.

Multi Asset Class Support

Collaboration

There’s been a substantial shift in mentality with our clients on the need for collaboration within and across their research teams. This started out as nice-to-have, but is now an essential way of working, to improve operations as well as returns. RMS rollouts that were initially a series of small silos within larger asset managers are often now combined to reach large, interconnected teams across asset classes. We also see an increasing need to break out new idea development into smaller, team-oriented collaboration spaces, that maintain a connection to the larger research ecosystem.

Another shift relates to the type of content that’s being shared. In the past, the emphasis was on formal research like target price and estimate updates and manager ratings. Today, portfolio managers also want to see a curated view of the interim updates on each name, ready for them at any time.

Of course the pandemic accelerated the need to collaborate virtually; a newly released document collaboration feature on FactSet saw adoption rates of over 29% in a matter of weeks. We also expect collaboration via Microsoft Teams to expand rapidly within the financial community and are seeing numerous firms adopt Teams integrations with RMS, again, to capture that curated view of daily chatter and documentation.

Environmental, Social, and Governance (ESG)

With recent regulatory changes in Europe and an explosion in consumer demand for ESG-focused products, capture of internal ESG scores and related commentary into the RMS is now a must-have globally. This content can be layered on top of third-party ESG content for a holistic view of each company or fund and fed directly into portfolio construction. We project a 123% increase in ESG-related RMS field content in 2021 based on current adoption.

Increase in ESG Related RMS Fields

Digital, Cognitive, and Open

With increasing pressure on margins and an explosion in data sources, leveraging technology solutions to improve efficiency and interconnectedness of previously separate solutions has become essential to the research process. RMS clients expect that cognitive capabilities—artificial intelligence (AI) and specifically machine learning (ML), natural language processing (NLP), and robotic process automation (RPA)—will reduce the burden of repetitive tasks and help cut the volume of incoming data—news, external research, filings, due diligence questionnaires, and reminders—down to just the most relevant content for each portfolio. Features like AI-enhanced search, signals capabilities, automated content tagging, and turnkey integration with external data sources like due diligence platforms and alternative data are critical components of the RMS as that central hub of the holistic research process.

Beyond core product integrations, clients are also taking control of their own ecosystems through open RMS architecture, which can make internal research exponentially more powerful. RMS APIs are used for a variety of augmented solutions, both for contributing new research from other locations—like automating trade logging alongside internal research—and for layering note content directly into parallel systems—like keeping block lists in a compliance system up-to-date, augmenting internal portals, or connecting with data lakes or visualization tools like Tableau or PowerBI.

Conclusion

The goal of any worthwhile RMS deployment is to not just slide seamlessly into the existing research process, but also evolve as quickly as each team and the market itself. Ideally the system will easily support changes, through a combination of continual product enhancement, self-serve tools for workflow agility, and expert support for larger shifts and best practice recommendations. These adaptations serve to keep research teams connected, focused on the bottom line, and ahead of the curve.

Read more about FactSet’s RMS suite here.

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Danielle L. Karr

Senior Vice President, Senior Director of Research Strategy

Ms. Danielle L. Karr is Senior Vice President, Senior Director of Research Strategy at FactSet. In this role, she focuses on developing holistic buy side and research management solutions strategies. Ms. Karr earned a B.S. in computer science and economics from Brown University.

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