Asset owners lagging on using AI for investing
Many asset owners may be keen to insource more investment capabilities, but there is one skill set that most seem happy to leave to fund managers for now: artificial intelligence.
Pension plans, sovereign wealth funds, insurance firms are increasingly allocating technology spend to boost efficiency and returns. Yet while large hedge funds such as the UK's Man Group have been using AI capabilities for some years, they are not yet a priority for most institutional investors.
The Teacher Retirement System of Texas, for instance, recently set up a dedicated portfolio analytics group for its private market portfolio and is putting more money into factor- and quantitatively driven strategies.
However, said chief investment officer Jase Auby, the $153 billion fund will be “resource-constrained for the near future” on areas such as AI and big data.
Asia is particularly behind when it comes to usage of AI for investing, Justin Ong, Asia-Pacific asset and wealth management leader at consulting firm PwC, told AsianInvestor last month.
“The development of AI in asset management is still relatively nascent and is not expected to be ready for commercialisation any time soon,” he said. “This is even more so where asset owners in [Asia] are concerned, as much of the actual assessment and processes remains relatively traditional.
“While many are exploring the application of AI," Ong added, "it is still at a conceptual stage and will need some years for enough historical back-testing and data lakes to be established for an AI tool to become viable.”
Still, argued Auby of Texas Teachers, it is ultimately only a matter of time before AI-based investment techniques – which are very much cutting-edge now – standardise and “become more accessible for folks like us to do internally”.
ASIA FIRMS PUSH INTO AI
While a lot of the work to make AI tools more ubiquitous is likely to take place among US funds, at least a few investors based in Asia are also looking to build systems.
Chinese financial services group Ping An is being a trailblazer, building a platform that combines AI with environmental, social and governance (ESG) information to drive its investing decisions.
Moreover, law firm Sidley Austin has recently helped set up “quite a number” of joint ventures for regional hedge fund clients, whereby the firms acquired technology or partnered technology providers to develop AI-driven systems, said Effie Vasilopoulos, a Hong Kong-based partner.
“What I’m seeing more of in Asia and what we saw a lot of last year was managers using big data technology analytics to help them make better decisions faster,” she told AsianInvestor. “It’s about smarter decision-making, more efficient operations, and the use of technology around that.”
This is not related to quantitative investment, which has been around a long time, Vasilopoulos stressed, but is a new trend. These techniques don’t fully automate investment decision-making, but enhance it, she added.
One example of a fund house operating such a model is Alaska-based McKinley Capital Management. The firm, which focuses on global growth equity strategies, uses AI chiefly in two areas, said chief executive and chief investment officer Rob Gillam.
Firstly, it analyses mega-large data sets that are too big to be dealt with by the naked eye or traditional tools. McKinley covers some 50,000 securities and crunches 96 data points on every company at least every day, and in some cases at every price change.
READING THE SIGNALS
Perhaps the “sexier” area where it employs AI technology is for analysing text for investment signals at high speed, Gillam told AsianInvestor.
“You or I will take a few minutes to read a news story,” he said. “With a computer, I can read every news story published in the last week in an eighth of a second.”
McKinley does a lot of analysis into search algorithms that look for certain word combinations and textual definitions.
“We’re trying to look for the nuance in a news story that determines whether they are additive or negative about a company or industry or sector or country. Whether companies have earnings that are positively or negatively taken by the street. Whether information is new or not new information. Whether it’s material for a company or not material.”
The aim is to broaden the scope and scale of companies and countries that McKinley can invest in, said Gillam. It is not, he stressed, designed to automate stock-picking decisions; merely to try to help the firm make better ones.
It may be some time before asset owners implement such systems themselves, but in the meantime they want to hear more. “Every meeting I have with an institutional consultant or gatekeeper or asset owner asks me about AI in some capacity,” Gillam said. “It’s top of mind.”
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