Using big data to gain an edge

From machine-learning algorithms to iPad apps and blockchain, funds of funds are embracing the data revolution.

The private equity industry has had a troubled relationship with transparency. Cautious general partners weighed up what data to provide, when and to whom. Limited partners were often at the forefront of the push for more transparency, dissatisfied with the provision of information by GPs. But the advent of big data has changed this. With data flows now contributing more to global gross domestic than flows of physical goods, private equity firms can no longer easily justify withholding it.

“It was not the case 10 years ago that every quarter you received a report from the manager with lots of data,” says Benoit Verbrugghe, head of the New York office at Ardian. “There has been a huge improvement from the GPs to get this information.”

Funds of funds have invested heavily to upgrade and create new platforms to manage and analyse this data. Previously reliant on manual input and manipulating Excel spreadsheets, advances in software mean fund investors don’t need an army of people. An algorithm can often do the heavy lifting.

One firm at the forefront of this revolution is Swiss fund of funds Schroder Adveq, which uses “machine-learning algorithms to screen the entire fund universe”, according to Nils Rode, chief investment officer at the firm.

New technology solutions have provided investors with the ability not only to deal with a greater quantity of data, but also to extract more quality data. Zurich-based fund of funds Alpha Investors says it was spurred to upgrade its platform five years ago by increased volumes.

“The system allows us to check the performance of individual managers and funds and compare managers in similar strategies”
Petr Rojicek

“The system allows us to check the performance of individual managers and funds and compare managers in similar strategies,” says Petr Rojicek, chief investment officer at Alpha. Rojicek also says the system is used for benchmarking terms such as management fees. “We don’t do this [analysis] only when managers come back to market but as a continuous process. This way, when a new fund does come back we know straight away if we want to go into due diligence,” he says.

The ability to outpace the competition is heavily prized among funds of funds. Verbrugghe says Ardian’s database is “critical” on the fund side, giving the firm visibility into potential investments. “When we buy for example a portfolio of 10 interests in funds it’s because we have the data and a clear view on the price. We can be very quick, efficient. We don’t need the reports from the seller about the portfolio, we already have the information. We just present our price. It’s a huge competitive advantage.”

Mining data at a level of granularity that wasn’t previously possible has presented funds of funds with new opportunities for analysis – and investment.

“We are following more than a thousand portfolio companies. From the underlying data you can extract very valuable information,” says Florian Kreitmeier, founder and co-chief executive officer at SwanCap Partners. He gives the example of performing due diligence on a co-investment in the pharmaceutical sector in a sub-segment in North America. “We can access detailed information on comparable public and private companies, comparable transactions, their recent development, their margins, their capital structures.” This granularity is also informing the LP-GP dynamic, with LPs able to form their own opinion on portfolio company valuations and exit timing, potentially challenging a GP’s view. Ardian’s Verbrugghe says the firm collects data on every underlying company held by its managers. “The EBITDA, the evolution of debt, the acquisition of new business, everything that gives you a precise view about what’s going on.”

Based on this data the firm conducts an exercise “where we look at what the exit value of each portfolio company could be and the possible timing of the exit”.

“The manager will have their view on the projected exit timing and price, but we have our own view as well. For every underlying company we have a downside case, a base case and an upside case,” Verbrugghe says. “So while we will probably not challenge the type of exit the manager will do, we will be more cautious about the timing and multiple of the exit in some cases. For example the manager might say we’ll exit at a multiple of 11 or 12x in two years and we will adjust that for a 9 or 10x multiple and two to three years.”

Robot reporting

Partners Group’s iPad app

Technology gains are also being used by funds of funds to get an edge on the reporting side. Alpha generates automated quarterly reports for its LPs with qualitative and quantitative data that reaches to underlying companies. Kreitmeier says SwanCap’s “customised IT infrastructure” allows them to provide LPs with “sophisticated and comprehensive insights into the fund performance, with a high degree of granularity down to detailed company data and industry analyses”.

Partners Group has instituted monthly reporting, an initiative its chief technology officer Raymond Schnidrig believes is “leading edge” compared with quarterly. Schnidrig says this “client-centric” data is available internally via the firm’s own staff web portal, via an iPad app or the firm’s customer portal for its clients. Schnidrig characterises the firm’s platform as “best of breed architecture” and says it is used for everything from “portfolio management to analytics, accounting to payments”.

Partners Group says it employs around 80 people globally within its overall technology team and continues to scale up its back-end, while Verbrugghe says Ardian invests around $10 million a year on its system.

With such significant investments being made, what level of return do funds of funds expect? Rojicek at Alpha says quantifying to what extent its data platform contributes to investment performance is difficult, but he says “it makes processes inside Alpha more efficient so we don’t have to grow in-house resources with regards to back office”.

Even in private equity then, robots are taking jobs. But while machine learning and automation is ideally suited to certain data processing tasks, “human intelligence is more vast than machine intelligence and is needed for broader questions such as valuations”, says Rode. Private equity professionals shouldn’t worry about the robots taking over just yet.

New kid on the block

Partners Group is one of the first firms to use blockchain technology for payments.

“We decided to use blockchain to secure payment instructions because downside protection is very important to us,” says chief technology officer Schnidrig.

Schnidrig explains that while the vast majority of the firm’s counterparty banks have the industry’s SWIFT connection, a small number do not, because getting the infrastructure is a big investment.

“We are sending payment instructions to banks that can be worth hundreds of millions. So we felt we needed to increase security around payment instructions in these cases,” he says.

“We don’t store any information about the payment itself. What we store in the blockchain is the fingerprint of the document. We run a specific algorithm that spits out a 32-byte number. We then send the instruction via -email, the counterparty runs the same algorithm and they take the 32-byte number, check it against the number stored in the blockchain and complete the transaction. Any counterparty can validate the instruction in the public blockchain to see if the payment is authentic.”