Japan’s Government Pension Investment Fund (GPIF) has, in recent years, made itself noticed for a reason other than its status as the world’s largest pension fund, with ¥161.76 trillion ($1.49 trillion) of assets under management as of September 30 2019.
A revamp of its investment approach – including a new performance-based fee structure – has fundamentally changed the pension fund. All eyes have especially been on its chief investment officer, Hiromichi Mizuno, who has been spearheading this process since 2015.
Under Mizuno’s tutelage, the use of artificial intelligence (AI) is another area where GPIF has ventured into uncharted asset owner territory. And the pension fund is not only in search of gains for itself, but also to shake up the AI notion among asset managers and other asset owners alike.
“I have been very frustrated about the speed of AI technology adaptation into the investment industry,” Mizuno told AsianInvestor. “We wanted to show the industry that people like GPIF, such a boring institution, can benefit from AI. We are basically sending a message to the rest of the industry that they could be doing the same.”
GPIF has outsourced the AI project to Tokyo-based Sony Computer Science Laboratories (Sony CSL), which has been working on it since it was hired in November 2017. The aim of the commissioned AI research is to help the pension fund optimise its fund manager structure.
The project is now trying to create a self-learning technology to improve asset manager portfolio monitoring. The pension fund is testing this technology on its investment portfolio, which is advancing its plans to add artificial intelligence into its investment management.
Mizuno believes that AI has the potential to improve the work of GPIF by giving a better understanding of where an asset owner can benefit from technologic innovations. At the same time, he underscores that “human wisdom should prevail” in some areas of the business, such as the push into ESG, stewardship and alternatives.
“By us using AI not to replace asset managers but to monitor asset managers we are sending the message that we still believe in the human wisdom to give us a return. We also don’t want AI to decide certain things, like environment and social issues. That is something we want to decide, not AI.”
Takao Tajiri, project leader for the GPIF’s AI project at Sony CSL, told AsianInvestor that the project has most recently widened its prototypes data set, attempting to quantify how much of fund performance is down to skill versus market movements.
It will then combine “these components into an integrated system in order to provide an additional new way of evaluating fund managers, which will augment GPIF officers' business processes”.
Mizuno’s message, that other asset owners ought also to look into AI, could seem a bit harsh given the relatively larger resources at hand for the world’s largest pension fund. But GPIF’s AI efforts are likely to reveal benefits scalable for much smaller portfolios.
While Sony CSL’s technology has been designed for the vast assets of GPIF, Tajiri believes it could prove useful for smaller asset owners too, noting that pension funds of all sizes face similar challenges when it comes to identifying good external managers.
To meet this, he and his team have proposed that global asset owners establish a data consortium that pools all data about their investment activities. That would accelerate and improve the prototype AI’s learning ability, and make it applicable for other research too.
Practically speaking, AI could also help smaller pension funds overcome a dearth of qualified investment professionals.
“Pension funds with relatively smaller assets or those located in provincial cities in Japan are strongly affected by [the country’s] depopulation, so the recruitment market has been tighter than ever,” said Tajiri. “We expect our new AI solution could enhance their monitoring and assessment capabilities.”
Institutional investors in Japan and across the world will be likely to follow the impact of GPIF and Sony CSL’s AI prototype with great interest. The results could help them to identify fund houses that better represent their investment preferences and identify alpha and beta due to judgement rather than luck. That could mean the writing is on the wall for underperforming active managers.