Institutional Investor Automating Alpha
On January 31, our President and Co-founder Greg McCall sat on an Institutional Investor’s Automating Alpha panel entitled “Building an Investment Idea Factory with Research Management Systems (RMS)” about how technology can help investors maximize successful decision-making within their investment process. He was joined by Northern Trust Asset Servicing’s Head of Investment Data Science Paul F. Fahey and William Blair Asset Management’s Director of Business and Technology Solutions, Kristina Blaschek.
Today, research management is far from optimized to its full potential. Many managers rely on legacy solutions to organize their research process, whether that be inputting and updating data into OneNote, Evernote, Outlook, Word, or Excel spreadsheets, or trying to piece together a plethora of solutions to determine the next best decision. The result is:
- Hard to optimize decision-making – your research is spread-out across multiple solutions.
- The information is often not up-to-date, so it requires wasted efforts to make sure it is correct.
- There is little consistency in presentation, making it difficult to compare two or more investment decisions.
Ensure your research and intelligence is effectively reflected in your decision-making.
Significant advantages accrue by modernizing your approach to research management:
Improved Decision-making
Centralizing all your data (qualitative, quantitative, internal, external) in real time – and in the presentation format that works for you –enables the most valuable content (opportunity or risk) to be surfaced in the most productive way possible. By capturing decisions and data that were made/not made (“your exhaust”), you improve your ability to learn “why” you succeed and where the blind spots are.
Real-time Analytics
In a world that seldom slows down, real-time internal, market and third-party data have become powerful tools in competing for alpha. Today’s investment teams require every idea to be supported by concrete evidence, largely analytics, which can only be done if they have a comprehensive data set. A modern research management program that leverages cloud-native software can provide the most “real-time” information available. This means managers can access the research they need, regardless of where they are. Transparency across teams improves, and team members can access and annotate the same research notes and view historical changes to better analyze results.
Increased Efficiency
Managers need collaboration, transparency and accountability, along with growing institutional knowledge, from their analyst teams. Housing the intelligence in a centralized, automated platform is the most efficient and effective way to accommodate these requirements. Collaboration is made easier with a team-based approach to research management. By housing all internal, market and third-party data in a single platform, teams can stay abreast of market shifts in real-time.
Effective Risk Management and Compliance
Investment teams are increasingly subjected to heightened regulations that require firms to adhere to a level of reporting and support documentation that addresses compliance needs. As a result, portfolio managers are demanding more from their risk systems in today’s financial landscape, but many of the current solutions are inflexible and siloed. Modernized research management systems can provide audit trails along with advanced reporting that is configurable and able to handle multiple portfolios, asset classes and indices.
Using Data to Get Ahead in the Battle for Alpha
Data proliferation has created a new world of opportunities for investment managers but has made the research management process more complicated. As the playing field continues to shift, it’s important for managers to harness the power of modern and intelligent automated solutions to optimize their research management. Armed with the right data, investment teams can tap into actionable insights in the ongoing battle for alpha.
For improved decision-making, your tech stack must be modern, flexible, easy-to-use and simple to implement.