Technologies such as natural language processing (NLP), machine learning, and robotic process automation (RPA) applied in the private markets can increase investor confidence in those markets, which are becoming more appealing as investors hunt for opportunities in a volatile market.

In March, many firms, such as JP Morgan, declared the end of a decade-long bull market, and continued to watch through April as it morphed into a bear. A week before New York enacted its lockdown, the VIX volatility indicator stood at more than 75 and had surged 60 points since the S&P 500’s February 19 peak, the bank said in its Top Market Takeaways for March 13.

Three days later, as coronavirus fears hit a fever pitch on Wall Street, the indicator hit 82.69, surpassing the last record, 80.74, set on November 21, 2008.

Little more than a decade after the financial crisis, the public markets were in crisis again.

Most institutional investors have a small amount of exposure to private markets in their portfolios, but with the volatility in public markets, and a hunger for returns, many are looking to quickly increase those exposures. The growth of alternative investing is moderated by private markets’ inaccessibility and lack of transparency.

Comprising unlisted real estate, private equity and lending, venture capital firms and mortgages, the private markets are home to companies not legally required to provide financial information to the Securities and Exchange Commission (SEC) or list on exchanges. These firms do not need to post their financial statements publicly and, if pressed by investors or news media, can decline to release revenue or capitalization figures.

Still, investors are seeking to diversify their holdings and look for other sources of returns—the same trend fueling the mainstreaming of environmental, social, and governance (ESG) investing. Private market assets under management (AUM) increased 10% in 2019 to $6.5 trillion, up from $5.8 trillion in 2018, according to a report from McKinsey & Company.

While volatility is one driver, investors are also seeking out the private markets because there are simply fewer public companies available to invest in. The rise of private equity and the institutional demand for it have halved the number the publicly traded companies since the 1990s when the startup world exploded in Silicon Valley. Coupled with the expense of taking a company public, burdensome regulatory disclosure requirements, and the sheer amount of capital a private equity firm can inject into a business, there isn’t as much incentive to list on a public exchange as there once was.

However, whether or not the private markets can offer investors a way to offset the losses they’re taking in the public markets remains to be seen. On one hand, there is no herd mentality in the private markets, where thousands of people panicking at once can have disastrous effects. On the other hand, a smaller, less diversified group of people involved can lead to radical swings, says Brad Bailey, research director with Celent’s capital markets division.

“I think everything comes to roost,” Bailey says. “And let me tell you when a crisis hits, when people talk about liquidity, the immediate liquidity of a public market for all gives you [an] out. … Liquidity is everything. The ease with which you can buy and sell something has a tremendous value.”

An executive at a venture capital firm echoes Bailey. What ultimately brings institutional money to private and alternative investment is what investors’ mandates allow for. If the investments are part of a pension fund that isn’t expected to be out for 30 years or so, for example, liquidity isn’t an issue. If it’s a family member’s pension fund on the line, that’s a different story.

Finding a Signal

Lack of available data has made the private markets notoriously difficult to penetrate. Comparing traditional and alternative portfolios becomes almost impossible as many systems are closed off from one another. Growing interest in the market has led existing vendors to make additional investments in platforms for private market investors, and has spurred specialized startups. As more investors extend their exposure in private markets, they are also looking for ways to make their investments easier to handle.

The rise of private markets mirrors that of emerging technologies like NLP, machine learning, and RPA. Mike Minces, founding partner and president of Blue River Partners, an outsourced service provider for the alternative asset management industry, says technology began to change the game about five years ago.

“The general thought is that technology is finally changing how things work,” Minces says. “The space has been growing and since many of the players are small businesses with around 20 employees, it makes sense that they are trailing in terms of innovation. Not only that, but the technology is now more accessible with the acceptance of innovations like the cloud.”

Because private companies don’t send reports to regulators, there isn’t a standard way to inform investors about performance. Much of the investment data gathering is done through news sources, online sentiment, or even word-of-mouth.

Thomas Anker, applications manager at Danish labor-market pension fund Pensam, says the business, as well as the systems landscape, was fragmented and relied heavily on Microsoft Excel. The fund often found itself in situations where data was maintained in one system but not another, resulting in hours of manual reconciliations.

In 2019, Pensam, which services more than €4 billion ($4.3 billion) in alternative assets, deployed the SimCorp Dimension Alternative Investment Manager, after commissioning a study that found 80% of North American buy-side heads of operation wanted to see alternatives consolidated onto a single platform for front-to-back processing. By moving to SimCorp, Pensam was able to reduce its number of siloed systems and operational risk, as well as garner more control over its data through creating a centralized repository of investment data.

“The biggest gain for us, without a doubt, is that we have taken control over data to such an extent that we are now able to do daily look-throughs on all of our funds, which means that we can see the underlying exposure on our investments and maintain it on a daily basis instead of quarterly,” Anker says. “Being able to quickly gain an overview of the underlying investment data in our funds—either to a company, currency, or a certain business segment, without having to consolidate or reconcile data from other sheets or systems—allows us to do much more precise hedging at a faster pace than we could before. This, in return, creates cost savings of a magnitude I haven’t seen before on any other project I have done.”

Front-office investment teams, though, require more than efficient data gathering; they need reliable insights and analysis. Applying NLP helps organize and structure information from a spectrum of different sources, which allows for standardization in language and easier queries.  

Data giant FactSet trawls social media platforms such as Twitter and Instagram to see how private companies publicize themselves. It analyzes whether private companies are hiring or firing employees, and uses purchasing data to look at those firms’ real-estate—both of which can partly tell whether a business is in expansion or contraction mode. Further analysis will then be done to determine whether broader economic concerns are playing out, or if the cause is more personal; conversely, it will also tell if a company is gearing up to spend more, re-locate to somewhere bigger, or increase supply due to heightened demand.

For data providers and analysts covering private companies, instinct and inferring rules over confirmation, says Sara Dillon, FactSet’s senior director of content and private of markets.

“You’re looking at a lot of scraped data [and] web-crawled data; you’re looking at directional insight rather than numbers in the same way. So you might have fundamental information, but the fundamental information is not filed,” Dillon says. “You have indications of information via signal or other datasets, which will give you a directional idea of how a company is growing or not.”