How AI can help asset owners unravel the private markets puzzle
Artificial intelligence (AI) could be a game-changer in resolving complicated data management issues in the alternatives portfolios of asset owners with regards to valuation, reporting, and analysis.
Managing data in alternative portfolios – from extraction and validation to forward-looking analysis – is predominantly a manual process for asset owners and managers currently, with a heavy reliance on spreadsheets or PDF documents.
“Because of how bespoke it is, it is something a lot of clients, both asset managers and asset owners, are pushing us to provide a service around,” Alex Popp, global head of sales and account management for private markets at Charles River told AsianInvestor.
Charles River
During his recent visit to Asia, Popp noted that the most frequently asked questions by asset owners were around practical use cases of AI in managing private assets and when the technology could be accessed by limited partners (LPs).
The unstructured data that investors receive in their private asset portfolios can vary across document types, asset classes, GPs, frequencies, and geographies.
Organisations spend significant time and effort analysing data from emails, spreadsheets, and PDFs, he said.
Currently, technologies for private market data processing are template-based, where investors can map the template and teach it to extract data.
However, when a new investment is made, investors must go through the mapping process again.
Data extraction is the first area where AI can be leveraged, Popp said, noting that Charles River is piloting a system that can customise templates and locate data in documents.
Some very large global asset owners are building out their own processes and mandating that general partners (GPs) fill out their templates – usually spreadsheet-based – with details about the underlying investments.
This has led to broader industry adoption where more GPs have started to offer it as standard procedure for LPs, he said.
ADVANCED ANALYSIS
Another developing trend is utilising AI to validate data and improve data quality. Both AI-driven data extraction and validation are being developed by Charles River.
The longer-term innovation will enable investors to query the system for specific data or proactively alert users to potential issues, as opposed to current practices where dashboards need to be configured manually.
“The practical usage of AI is starting to become much more real as it relates to how we're leveraging it in our products for clients,” Popp said, noting that the firm is investing substantial resources to utilise AI in streamlining private market data management.
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Mercer
Other asset managers are experimenting as well.
Earlier this month, Schroders Capital unveiled its generative AI investment analyst platform.
It can help its in-house private equity specialists automatically screen data and generate draft investment summaries in significantly less time, freeing up the investment team to reallocate more time to value-adding investment activities, the firm said.
At the moment, AI can help asset owners to quickly capture and input valuation figures and the key assumptions on which those valuationa are based, according to Johnny Adji, Asia alternatives leader at Mercer.
“However, the current AI or machine learning capabilities are not mature enough to assess the ‘reasonableness’ of a valuation figure. We view this as an evolving trend,” Adji told AsianInvestor.
On private debt, for example, some fund managers have started to use generative AI or machine learning to predict the potential default risk of a loan.
“Despite anecdotal ‘success stories’ of their predictive power, an industry-wide analysis is required before one can determine the effectiveness of these AI models,” he said.
The latest survey of Preqin also noted that the use of technology and an AI-leveraged approach to investments does not rank high on the priority list for Asian investors.
Preqin
“However.... this is definitely something that investors will monitor, as it could also develop quite fast once there are more breakthroughs,” Angela Lai, head of APAC and valuations, research insights at Preqin told AsianInvestor.
PRACTICAL USES
Generally, data on private assets is difficult to source, and public filing disclosure standards differ between markets and could be very time-consuming to gather.
Private asset valuations are typically based on comparable transaction data.
Aside from the sourcing issue, there are qualitative analyses involved to determine appropriate proxies. These are areas where Lai sees AI could provide immediate help.
Nick Kelly, head of private markets research, Asia Pacific at WTW, believes more asset managers and service providers will look to leverage AI to provide more integrated solutions to asset owners for their private markets investments.
WTW
One of the primary benefits is likely to be in enhanced data analysis and predictive analytics, like using AI to forecast traffic flows for toll roads or grid efficiency for renewables, he said.
It can help analyse limited market data and reduce subjectivity in valuation judgments, which is a pain point in private markets investing, he added.
“This will hopefully lead to improved valuation accuracy and decision-making,” he told AsianInvestor.
These developments aim to reduce costs, optimise resources and strengthen risk management through AI-driven assessments.
“The big question is how long will it take to realise these benefits?” he said.