In FOCUS: 4 Questions for a Fundamental Research Expert and Masterclass Presenter

As a result of working with clients across diverse industries to optimize their investment workflows, Jana Ievins has a panoramic view of key trends and needs across the fundamental research process. We sat down with Jana ahead of her fundamental research masterclass presentation, slated for the FactSet FOCUS event, April 29 – May 2 in Miami.

Given you work with a range of asset management clients, what is the No. 1 challenge they’re discussing with you in the current financial environment?

The main themes are cost pressures and the significant increase in their responsibilities. For example, we have observed that coverage lists have expanded as much as 10x, which puts an immense strain on time. Additionally, the scope of data they need to comprehend for each company has been growing, adding to the complexity of their tasks.

The rapid pace at which complex data is generated also poses a major challenge. To be competitive, our clients have to distinguish between relevant/irrelevant data, and within the relevant bucket they need to discern the great data that is primary to their objectives from the good data that is secondary.

We provide our clients with tools and solutions that streamline their workflows, improve data comprehension, and alleviate information overload. We help them leverage technology, data analytics, and AI-powered tools, all of which enable them to make strategic investment decisions with greater efficiency and confidence.

What workflow trends are helping asset managers make incremental improvements in productivity and the pursuit of alpha?

Our clients are under pressure to outperform, and they need to find unique investment insights—quickly. Several key trends include:

1. Data focus: Asset managers increasingly rely on concise, targeted market news and research reports such as StreetAccount summaries. These offer a consolidated overview of important market developments, analyst recommendations, and macroeconomic insights. Because managers don’t have to sift through multiple sources of information, they free up time for their most critical priorities.

2. Automation and machine learning: AI technologies help streamline tedious tasks and generate insights from copious amounts of data. This opens additional time for value-added activities.

3. Data integration and management: Asset managers are adopting robust data management systems that enable them to efficiently aggregate, organize, and analyze datasets while integrating internal metrics, ratings, and commentary. This helps them gain a comprehensive view of market trends, company performance, and other factors affecting their investment decisions.

4. Collaborative work platforms: We’ve seen a big trend in the importance of connectivity between fundamental researchers and PMs and an increasing expectation that technology helps to facilitate that. Asset managers are adopting collaborative work platforms for seamless communication and collaboration across teams. These platforms, such as FactSet's Research Management Solutions, enable real-time sharing of information, research, and insights.

5. Agile and flexible workflows: Asset managers are embracing agile and flexible workflows to respond faster to emerging trends and adjust their investment strategies appropriately.

6. Data-driven decisions: Advanced analytics techniques, such as predictive modeling and data visualization, are helping asset managers extract valuable insights from complex datasets. These tools enable them to identify patterns, detect anomalies, and make data-driven investment decisions more effectively. We also help our clients increase their overall scale and efficiency through technology, including generative AI, FactSet’s Programmatic Environment, and other tools.

How are portfolio managers and researchers factoring macro-environment uncertainties (e.g., interest rates, geopolitical tensions, inflation) into their fundamental research?

We have been seeing portfolio managers and researchers consider various scenarios, analyze economic indicators, adopt a top-down approach, stress test portfolios, seek input from expert networks, conduct fundamental analysis, and maintain diversification.

Over the last four years, macroeconomic factors have been at the forefront of our clients’ minds. Geopolitical conflicts, rising interest rates, and a desire to have more direct control over resources and supply chains can all have massive effects on a portfolio and present unique challenges to research teams.

Clients are using FactSet’s Revere data, which provides insight into who companies work with, what they do, and where exactly they derive revenue. They map risks and opportunities across their investible universe through a combination of geographic revenue analysis, business-driven sector taxonomies, and our own interconnected supply chain database.

How do you see AI supporting research workflows in the near term?  

AI is already helping researchers and PMs save time and find new insights in their pursuit of alpha.

For example, amid the hundreds of calls and transcripts during earnings season, our first interactive generative AI solution available to all firm types—Transcript Assistant—extracts the key points. Five pre-populated prompts are offered, and users can type their own questions, similar to chatting with a colleague.

They also can view a concise summary of the Q&A discussion between management and analysts, which FactSet StreetAccount capital markets writers quality check to prevent hallucinations. These are big wins for our clients as they no longer have to sift through transcripts or attend so many calls, freeing up time for other valuable work.

In December, we also launched the beta release of a LLM-based research agent—FactSet Mercury—to enhance fact-based decision making. Mercury is focused on the company research workflow, providing a conversational interface to the Company/Security reports in the FactSet Workstation. It accesses a breadth of content, including key fundamentals data, the latest 10-K filings for the S&P 1500, and supply chains, for example.

FactSet's portfolio monitoring and simulation workflow tools also provide proprietary recommendations and insights. These tools leverage AI capabilities to analyze portfolios, connect the dots across the investment team, and offer valuable recommendations for portfolio optimization and risk management.

By bringing these AI-powered solutions to the market ahead of competitors, FactSet demonstrates its expertise and commitment to harnessing AI for the benefit of clients. FactSet's tools have received praise from numerous clients, highlighting the quality of the solutions and our dedication to leveraging AI to enhance research workflows and help clients drive alpha generation.

This blog post is for informational purposes only. The information contained in this blog post is not legal, tax, or 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.