Data warehousing key to smooth tech transition

Private equity CFOs have had an exhausting 12 months watching public markets whipsaw and assessing the impact on their investments. There is, of course, a lag between public and private markets’ reactions to economic events. But Hamilton Lane noted in a recent report that, while 40 percent of companies listed on the Russell 2000 index had negative earnings through Q3 2022, only 8 percent of private companies were in the red.

Valuations of private fund investments remain far from exact science. But as technology advances continue at pace, fund administrators are finding that they are now better placed to provide GPs (and their LPs) with far more data than was possible a few years ago. Implementing technology can be complex and costly, however, requiring firms to find the right balance between developing in-house solutions and working with third parties.

“We have a very large technology team led by our chief digital information officer, Marie Measures, who are responsible for developing our technology stack in-house. But we continue to develop strategic partnerships with vendors as well,” notes David Fowler, global co-head of product, private equity at Apex Group. “We are developing our own RPA technology and we also have a data team who are building and developing a data lake, which is going to be important in terms of reporting to clients.”

Alter Domus, a leading private equity fund administrator, has sought to partner with Canoe Intelligence to deliver automation and enhanced data management accuracy, and on May 11 this year, the firm announced its latest acquisition: Solvas, a loan and debt servicing software platform developed by Deloitte.

“There is a fine line between partnering with firms and internal development. Over the past 12 months, we have significantly increased our own internal team to build modular tools,” says Tim Toska, global sector head in Alter Domus’ Private Equity group.

Increased demand for data transparency, accelerated by the pandemic, has forced fund administrators to harness new technologies to pull data from portfolio companies, adding an extra layer to intelligently process that data. That, in turn, helps to streamline the valuation and reporting process.

“It has been an exciting journey for us and opened up a lot of great conversations within our data analytics teams on the use of data warehouses and knowing how to connect legacy systems internally and externally for our clients with advanced technology,” says Toska.

Data lakes trump blockchain

Data warehousing is a key development for private equity’s ongoing technology evolution. “It’s firmly on our clients’ minds. They are interested in understanding our data policy and data warehouse housing strategy, and how it links in with their own operations,” says Fowler.

Clive Bellows is head of global fund services, EMEA at Northern Trust. He says “the next stage for us will be using data warehouse technology, using data meshes with each of our clients to exchange data in real time.

“We want to move away from ‘push and pull’ technology,” he says, referring to point-in-time data exchanges through mechanisms such as secure FTP file deliveries.

“The data warehouse will be a repository which clients can access in real time to see where we are in the valuation lifecycle.”

CFOs and CFOs have identified data warehouses (otherwise known as data lakes) as a priority. These solutions have similarities to blockchain, a technology that only works when two or more parties are committed to using it.

“It’s really the same with these data warehouses. I do think in the private capital space, that is where the sharing of data is going to go, rather than using blockchain,” Bellows says.

This is because, in his view, data warehouses provide a flexibility to deliver and receive data from multiple constituents, regardless of the platform decisions made by the counterpart.

“Blockchain can perform similar functions but it is usually dependent on the stakeholders participating in the blockchain ecosystem and is therefore less versatile,” explains Bellows.

From excel to… AI

Multi-manager CFOs in particular, are in dire need of improvements to the way they monitor and analyze portfolio valuations. And with continuous advances being made in AI, there is tremendous scope for progress there.

“Our data and analytics team have assisted clients with managing data from multiple sources, getting it to a single source of truth to feed the reporting needs downstream so that a CFO can say, ‘I have the most up to date information.’ That’s so important and critical in this day and age. When we start thinking about new technologies, such as ChatGPT, to overlay a data warehouse, you need to have access to the data digitally. It’s a journey to get there to take advantage of the data,” says Toska.

As the flow of data increases within private markets – both as GPs request more data points from their investee companies and LPs request more granular insights from their fund managers – the role of data warehouses is likely to play a pivotal role. At Northern Trust, significant capital has been invested in developing workflow tools to eliminate the use of email, says Bellows, “so that we can share data and managers can see where we are in the NAV production process via dashboards.”

This helps avoid having to send manual updates and provide more regular insights into the performance of private equity funds.

“Also, it’s not just about valuations. It is also about risks. Investors want to make sure they don’t unintentionally have too much exposure to a particular sector,” adds Bellows.

More data, faster

Inevitably, as technology improves, the role of generative AI to source and manage large data sets should help private equity valuations become more reliable over time; of course, this is contingent on the source data being accurate.

Fowler sees private equity moving towards public equity markets in terms of the quantity of data and the transparency being demanded.

“It follows the trend that we’re seeing towards the ‘retailization’ of private market funds. We’re seeing more evergreen structures and hybrid structures. However, I don’t see us getting to a point where daily NAVs will be common.”

Toska says that advancements in this field will enable CFOs and their teams to provide further value-added functions like supporting the IR team by having a clearer, more comprehensive view of a company’s performance, and responding quicker to LP requests.

“It is all about removing the robot from the person. CFOs are getting access to much more informed data but we are still in the early innings of determining what that net impact will be,” says Toska.

Apex Group is also looking at AI as a possible part of their future client service processes, according to Fowler.

“I think it’s an opportunity for CFOs to become more strategic and make decisions in a quicker time period,” he says.

With AI developments taking place at breakneck speed, the virtues of data warehousing, and their ability to organize and present large volumes of data in a coherent manner, are becoming increasingly attractive to fund administrators. All of which augurs well for CFOs.