Are asset managers long on plans, short on action in data science?

Survey finds nearly all investment managers focusing on data and analytics to improve outcomes, but most lagging in capabilities

Are asset managers long on plans, short on action in data science?

Faced with continuing pressure from rising costs as well as increased client demands for transparency and consistent performance, asset managers see data science and analytics as the wave of the future – but are they positioned to harness its full potential?

That was the question raised by a new white paper from Northern Trust, which draws from a survey of 300 representatives from global asset management firms and hedge funds with AUM between US$250 million and US$750 billion conducted in the second quarter of 2021.

“This survey shows asset managers are aware of the need to implement a digital operating model that enables efficient and safe growth, but at the same time are rightly focused on the imperative to spend scarce capital wisely,” said Paul Fahey, head of Investment Data Science (IDS) at Northern Trust.

According to the report The Art of Alpha: It’s All About Investment Data Science, 98% of the survey respondents were already using, planning to pursue, or were interested in incorporating data science or decision-support tools into their investment process within the next two years.

The majority cited the need for a centralized platform for their investment data to aid decision-making (57%), as well as current usage or plans to use natural language processing or sentiment analysis (54%) and predictive analytics using past returns (53%) to bolster their processes.

But despite that broad awareness and ambition to use data science, nearly half (48%) said they still rely on “qualitative measurement, which mainly relies on anecdotal evidence of proper decision-making” to measure their investment team’s skill. Just 24% said they use a decision-support platform to tease out drivers of performance and behavioural root causes behind decisions at a more granular and individualized level.

What’s more, only 12% said they use a formal research management platform that isn’t built on spreadsheets. More than half (52%) said their organizations still employ spreadsheets to consolidate internal and fundamental data; other data sources are accessed manually from email, PDF, and other channels and formats before being integrated to make investment decisions.

Looking at investment managers’ current data diet, 66% said they currently draw on five to eight sources of investment data. ESG data (59%) and traditional factor data (55%) were the top sources, followed by alternative data (51%), consumer data (27%), and sentiment data (10%).

When asked how they could derive the best benefit from data analytics, 52% of respondents said it would help most in “making their best investment ideas repeatable.” Other potential benefits identified were “understanding why our investment decisions result in particular outcomes” (38%), “ensuring we have a complete understanding of our risk profile” (32%) and “ensuring that our investment team has access to the totality of our research” (29%).

According to Gary Paulin, head of Global Strategic Solutions at Northern Trust: “Asset managers need to become more digitally conversant, not only because it will lead to improved investment outcomes, but because it’s being demanded more by their stakeholders, who are leveraging data science tools to do analysis of their own.”


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