Much is spoken of the data challenges that institutional asset managers are facing as they redraw their business models to meet the demands of a new economic environment, but less is said of asset owners, who are undergoing their own operational transformations.
For them, the data journey is just as challenging; as their operational models evolve – often seeing them take on some of the roles of asset managers – they need to service the difficult decision-making processes faced by investors on top of those they are already tackling in their traditional role as guardians of collected wealth.Unsurprisingly, they are looking to data and technology to aid their transformation. Equally expected, they are encountering challenges.
Pain Points
A recent report by Northern Trust indicates the extent to which asset owners are looking to solve many of the pain points associated with their new operations through data-heavy applications. Achieving efficiencies through automation topped the list of challenges faced by asset owners who responded to a survey for the report.
More than three-quarters cited this as a hurdle to their objectives, followed by two-thirds who said hiring and retaining talent was a challenge. About three-fifths said harnessing artificial intelligence was an operational difficulty. The report identified that almost four-fifths of the 180 asset owners questioned said they were looking to technology to bring the changes they need.
Strategy Rethink
Asset owners, which include pension funds and endowments, are being forced to reassess their data strategy as they adapt their operations to increasing inflationary pressures, political volatility, climate change and demographic and retirement shifts. With technology enabling them to play a more direct role in managing the huge amounts of capital they control – the 100 biggest asset owners oversee an estimated US$24 trillion in assets – many are assuming roles they’d traditionally have outsourced.
The challenges they are facing are clearly illustrated in asset owners’ shift to multi-asset strategies. More asset owners are allocating their capital to funds as they seek to diversify their holdings and take advantage of higher returns away from equity markets. The data uplift for that can be tremendous, however.
“Many in the industry believe that there will be a shift from strategic asset allocation to more of a total fund management view; that style of asset allocation requires a much bigger depth of data around… exposure, liquidity and valuations,” Melanie Pickett, Northern Trust head of asset servicing, Americas, told Data Management Insight.
A key feature of investment and capital allocation strategies over the past few years has been the move towards private and alternative assets. A Morningstar report in September indicated that asset owners worldwide are increasing their exposure to such markets by a couple of percentage points a year and that in 2025 they had committed about a fifth of their firepower to private equity, private credit, hedge funds and other opaque spaces.Sophisticated Strategy
Sourcing good-quality, complete and trusted data from markets is a fundamental part of any investment process, but there are difficulties in accessing information from private markets.
“Getting to the data certainly is a challenge,” Pickett said. “The levels of transparency that are given to clients from general partners can vary widely.”
In hedge funds “some may get long-only holdings on a lag. Some may get just sector and geography exposure,” she added.
Some “sophisticated” asset owners are including their private and alternative asset operations within their directly managed business, a prospect that presents a greater level of data complexity, said Pickett. Valuing assets is a particular challenge, requiring expertise to monitor specific factors that must be considered to put a dollar value on holdings.
In real estate, for instance, valuations will depend on a wide variety of metrics, including occupancy levels, rents and rates, service providers and so on, which asset owners may not be familiar with in their traditional role.
Often, that data is not easily available because those assets are not very liquid and valuations are infrequent. Consequently, many asset owners are unable to balance their accounting books of record against the investment books of record their new activities require them to keep. This can cause tension between the firm’s investment and accounting teams, said Pickett.
“It’s a governance challenge,” she said. “Most of these clients have boards that typically… want to see the performance numbers match the accounting numbers.”
Off Track
Misalignment of another sort touches on the report’s second-most cited pain point for asset owners. Talent shortages are compounded by the organisational realignment that’s necessary in any transformation. For asset owners, that has been made acutely apparent in the move towards a multi-asset strategy, which has led to difficulties in bringing together teams that had hitherto focused only on one asset type.
“The harder work for the client is the organisational alignment of the different investment teams,” said Pickett.
When firms make a transition to total fund management, the teams are typically having that conversation for the first time.
“Getting your venture team and your real estate team and your infrastructure team to think the same about risk tends to be challenging,” she said.
AI Application
Like all other parts of the financial services industry, asset owners are looking to artificial intelligence to bring the automated efficiencies and productivity boosts necessary to compete. Pickett said that many of Northern Trust’s clients are trying to find the “value proposition” in AI and are keenly interested in what their peers are doing.
Among the use cases to which they see potential value in applying AI is the use of their legal work to compare conditions and pricing across general partners and also to help in research activities, Pickett said. Smaller asset owners that are committed to a multi-asset strategy are also using AI to curate research reports in the absence of a large analytics team.
Within the companies’ private markets business, however, AI will not be sufficient to solve their data challenges.
“Many clients are at a phase right now where they are reevaluating their technology stack… what is difficult with the alternative space specifically is software alone is not going to solve the problem” they face, said Pickett. “Middle office teams will still have to do the hard work of gathering and compiling and normalising this data.”
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