Going forward, artificial intelligence will be a bigger factor for active managers and institutional investors, including investment advisors, and research will come from difference sources aside from investment banks and brokers, according to a new study released by Greenwich Associates and Thomson Reuters.
The study found that 90% of institutional investors say their in-house research is their main input to the process, and that active managers will need to “embrace new, alternative data sources, new technologies, and upgrade their skill sets to apply these tools effectively,” according the study, “The Futures of Research.”
Researchers surveyed 30 global portfolio managers, chief investment officers and investment analysts who represent institutional asset managers, pension plans and hedge funds. They were asked both qualitative and quantitative questions on their plans for the next five to 10 years. Other findings include:
- 56% of institutional investors are expected to increase the level of AI integration with the investment process and 40% expect to increase their AI budgets,
- 70% of those surveyed have either implemented an alternative data plan or plan to in the next 12 months, and will include it with their fundamental research approach,
- Only 17% currency use AI such as machine learning and natural language processing when analyzing data, news and content in their investment process,
- 50% believe the buy side will rely less on the sell side for research services. In fact, 43% expect to increase reliance on proprietary in-house research and 39% expect to increase their reliance on independent research providers.
- 71% of senior asset management and hedge fund professionals believe “competitive dynamics” will lead to increased research unbundling, even in regions that aren’t covered by MIFID II.
This unbundling of research will allow investment managers to be “less beholden” to brokers for their research, the study states, adding that “investment research will evolve into a more stand-alone business for banks and independent research providers, with the costs more likely borne by the asset management firms than the end investor.”
Alternative Data Rises
The study found 50% of participants will be less reliant on investment bank research, while 43% said they planned to increase their in-house proprietary research. Further, 50% of respondents said they would “increase the usage of alternative data sets.” These are defined as “unique data sets that, by themselves or in conjunction with traditional market data, could provide additional insight and competitive advantage.” The alternative data most used today by investors includes web-scraped data (36%), search trends (29%), expert networks data (29%) and web traffic (21%).
Web scraping, which is searching websites for key information such as trading prices or inventory on public retail websites to determine brand or company performance, is still the most used source of alternative data, with some firms utilizing their own software to gather the information.
Further, alternative data typically is used to augment existing models, i.e. 43% use it to find new investment opportunities and about 21% also used it to help with timing of a trade, the study found.
A majority (73%) of participants had yet to incorporate artificial intelligence into their systems, with 17% already using it and 10% stating they plan to in the next 12 months. Most see it helping with analyzing data, news and content, and “56% of the firms expect to increase the level of integration with the investment process and recruit additional internal expertise.”
The study also found that AI and data science will be much-sought skills by portfolio managers, with budget allocations having a large majority, more than 80%, projected going forward.