Australia's State Super has hired Neuberger Berman LLC for an equity mandate and to help the fund accelerate development of data science and machine learning tools that can complement its more traditional investment capabilities.
The move reflects continued concerns that conventional approaches to managing the Sydney-based fund's A$44 billion ($30.2 billion) portfolio may not meet the moment in unconventional times.
"My biggest concern is what happens if the market is behaving in an abnormal way," outside of the industry's knowledge base and modeling conventions, said Charles Wu, State Super's deputy chief investment officer and general manager, defined contribution investments, in an interview.
In that regard, Mr. Wu said the emergence of negative sovereign bond yields three years ago was a warning bell.
In the current environment, "a different way of thinking is required" and machine learning — with its potential to come to a problem without prejudices or preconceptions — can help State Super's team navigate a world growing evermore different from the one everyone has been trained to think about, he said.
On May 21, citing data science capabilities as a "key differentiator," State Super awarded Neuberger Berman a mandate for a concentrated global equities portfolio of 35 stocks.
State Super selected the New York-based firm from more than 100 managers responding to its request for proposals at least partly on the strength of what Andrew Huang, the fund's senior investment manager of equities, termed a "unique and compelling" approach to having data scientists and fundamental analysts work hand in hand to add alpha.
Mr. Huang declined to reveal the size of the mandate. Lucas Rooney, Neuberger's Sydney-based managing director and head of institutional business, Australia, would only say it was "large."
The mandate is the first for Neuberger's global equity data-science integrated strategy, the culmination of three years of effort to complement fundamental analysis with capabilities to mine data for better insights into company-specific fundamentals, Mr. Rooney said.
As part of that integration, "we see data scientists go to company research meetings" and traditional analysts learning to write code and understand data sets, Mr. Rooney said.
Neuberger's data scientists, working in tandem with fundamental analysts, comb through credit card data, job postings and social media to better understand the "long-term intrinsic value" of the companies that are part of the strategy, said Hari Ramanan, New York-based managing director of Neuberger's research-centric core and thematic funds, in an interview.
Data scientists can effectively bring "power tools" to the table, capable of looking beyond key metrics such as same-store sales to, for example, a more useful analysis of those sales on a store-by-store basis, said Michael Recce, the veteran of Singapore sovereign wealth fund GIC and Point72 Asset Management who joined Neuberger in 2017 as managing director and chief data scientist.
Mr. Ramanan said his team's analysis of credit card data — including distinguishing brick and mortar vs. online transactions and using statistical inference for demographics and customer cohorts — "increased our confidence" that Nike Inc., one of the strategy's top holdings, could maintain midteen margin levels even as consensus estimates pointed to a decline to low-teen margins. Meanwhile, the Neuberger team's ability to track sales on China's TMall.com online platform allowed it to confirm that Nike's strong momentum in the country, which accounts for 20% of the company's total sales, wasn't being derailed by the COVID-19 crisis.