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Buy-Side Trends: Open Architecture, Multi-Asset Strategies, and ESG

Data Science and AI

By FactSet Insight  |  July 22, 2021

FactSet’s Danielle Karr, Senior Vice President, Senior Director of Research Strategy, recently spoke with Cutter Associates at their Advance Together member meeting to discuss the advantages of platform consolidation and open architecture solutions to reduce the noise in day-to-day tasks, the importance of multi-asset strategies, and growth in the environmental, social, and governance (ESG) data space.

Q: What are some of the advantages of consolidation, but, at the same time, why should firms be looking for an open architecture?

Danielle KarrConsolidation has been a growing trend over the past couple of years. For financial professionals, supporting and maintaining multiple disparate systems to meet their workflow needs is a huge burden. Consolidation reduces overhead cost and creates opportunities for economies of scale; in turn, there are fewer disparate negotiations. Other benefits are that rollouts and training plans can be set at an enterprise level and most importantly, and in many cases, consolidation creates a better user experience for those who no longer have to context-switch between different applications for different tasks. This is all happening as we see assets under management (AUM) moving from active strategies to more of a blended approach (active, passive, thematic, and ESG-focused alternatives).

Firms are increasingly requiring open architecture to maintain flexibility and ownership of key parts of their day-to-day workflows as they embark on a consolidation strategy. They are looking for content and solutions accessible via web, mobile platforms, application programming interfaces (APIs), and customer relationship management (CRM) systems.

To fully support these firms’ digital transformation efforts, data and software providers need to provide guidance and suggestions on how to optimally use the available options. However, they need to keep in mind that a developer is not necessarily a full-time software engineer; they may be a research analyst who's looking, for example, to augment their core research process with an API-supported model or something of that nature. Firms want to see how these different solutions can be brought together to solve common problems often using low-code techniques, so anyone can enhance their existing research with open technology support.

Q: What are the strategies or technologies that firms can leverage to “reduce the noise”?

Every day, analysts and portfolio managers are seeing new alternative data on top of all the pre-existing news, research, filings, internal commentary, and core content they are already using. The volume is constantly growing, and it's usually sitting in separate systems and not concorded. It's becoming increasingly difficult to find value in all that noise and, on the flip side, easy to miss investment opportunities.

There are many newer and evolving technologies that can help. Artificial intelligence (AI) and machine learning (ML) solutions are now being used to extract high-value insights from large volumes of content. The goal is to develop signals that are more predictive and out ahead of market-changing events. Using ML, smart search technology enables financial professionals to search for keywords and topics quickly and efficiently across many different sources of data, including their own internal research. Ideally, the algorithms can provide context to help identify which documents are most important.

Q: With multi-asset strategies on the rise, portfolio allocations to alternatives are increasing. What does this mean for the financial industry?

One trend we’re seeing is growth in the use of Research Management Solutions (RMS), which allows teams to log their internal research on the different entities that they cover. 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 and collaborating on research, covering everything from equities to fixed income to funds, in a single location. RMS products need to accommodate all those families of securities as well as private assets that a firm might own.

Private markets are also growing in importance, both for fundamental research workflows as well as multi-asset class portfolio lifecycle flows. This means that firms need access to deep private company, private equity/venture capital (PE/VC), and M&A data, all presented in easy-to-use formats and fully integrated with portfolio analytics and risk solutions.

The trend toward multi-asset class investing speaks to that consolidation topic discussed earlier. As firms merge and bring together disparate teams, each with their own intellectual property and coverage lists, leveraging a single platform to support the entire asset class spectrum streamlines operations and reduces overhead.

Q: ESG is gaining attention and a lot more momentum across the industry. What does this mean for investment managers as well as software and data providers going forward?

When it comes to ESG, we’ve never seen a content set go from alternative to fundamental this quickly. A combination of factors has come together to make this one of the hottest topics of the last couple of years. These include regulatory drivers, the recognition of how clearly aligned ESG will be with long-term business growth, as well as market demand for sustainability-driven investment products. This shift has only been accelerated by the pandemic.

There are already several third-party ESG providers supplying the financial industry, with new niche providers targeting certain sectors or regions popping up constantly. Firms are often looking for two types of complementary ESG content: a data-based set of as-reported ESG metrics sourced from corporate social responsibility (CSR) reports and filings plus a source that provides a more independent lens (not information that the company has reported). For example, Truvalue Labs, a FactSet company, leverages AI techniques to analyze news updates and alternative data sources to produce structured ESG content and scoring.

Another feature that is increasingly important with ESG content is the need for concordance. When you have a mix of structured and unstructured data, it’s important to have a system that links it all together to seamlessly carry out your analysis. In addition, data shouldn’t sit disparately in different locations; it should be holistically connected to fundamentals, estimates, economics, and various other datasets.

Firms are at various stages of their ESG journey. Some are just starting to layer third-party ESG scores on top of their core research holdings to litmus test their current investments against those materiality dimensions. Others are tracking their internal scores, creating a third dimension of evaluation and commentary. Some are actively testing new products as they become available. This continues to be an exciting space to watch as products continue evolving around this ever-expanding content.

The industry is stepping up to ensure the consistent flow of information in this area. Recently, FactSet signed on to a joint statement from the leaders of global data and analytics providers in support of the work being proposed to develop a standardized methodology for ESG-related reporting. Information on sustainability that is consistent, comparable, and reliable is critical for the financial industry in supporting the global economy going forward.

You can read/listen to the full interview here.

Cutter Associates provides independent research, custom benchmarking, and a global consultancy for the asset and wealth management industry. Investment companies around the world partner with Cutter to improve capabilities, achieve higher scale and efficiency, and generate operational alpha.

The information contained in this article is not investment advice. FactSet does not endorse or recommend any investments and assumes no liability for any consequence relating directly or indirectly to any action or inaction taken based on the information contained in this article.

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The information contained in this article is not investment advice. FactSet does not endorse or recommend any investments and assumes no liability for any consequence relating directly or indirectly to any action or inaction taken based on the information contained in this article.