Researchers, including Ashby Monk, executive director of Stanford University’s Global Projects Center, are calling for private equity firms to share more and better data about the companies in which they invest, a sweeping change that would give investors a true picture of risks, fees, and performance. Monk, Sheridan Porter, co-founder of FEV Analytics, and Rajiv Sharma, research director of the Global Projects Center, also call for investors, or limited partners, in these private equity funds, to use new data science techniques to gather evidence and better understand their portfolios. In a recent paper, the co-authors argue that without these changes investors and others can’t determine conclusively whether private equity beats public equity or is the best strategy for their money.
The call for change is part of a larger philosophy the paper’s authors call organic finance, which makes the case for greater transparency and shows, for example, how asset managers can often create financial products whose risk-return characteristics don’t reflect the underlying investments.
“There is a pressing need to substantiate the economic case for private equity. In this article, we describe a new transparency framework, which we situate in our research agenda on ‘organic finance,’” wrote Monk and his co-authors. “The framework uses data science technology to operationalize private equity data and institute a scientific approach to performance measurement. We elucidate what scientific measurement should look like in private equity, incorporating examples of technologies in use today.”
Investors in private equity need data to calculate valuations, returns, risks, fees, performance attribution, and other measures of the sources of investment returns. Armed with that information, investors in private equity funds and others can follow those hard facts through the life of an investment and do accurate comparisons with other options. The authors also suggest limited partners in the funds use technology and data to better assess the value of investment opportunities and the track records of managers. According to the report, organic finance and the transparency it fosters is fundamental for the future of private equity because the asset class now represents a huge portion of institutional portfolios, sometimes rivaling the money invested in public stocks.
“PE has increasingly become a larger allocation in institutional portfolios around the world,” Porter told Institutional Investor. “We need to start modernizing and that modernization and transparency involves data.”
There are plenty of practices that need a facelift.
Investors in private equity face high costs and increased risks because of structural issues in the industry that hinder transparency. For example, investors generally don’t measure returns and fees based on information on the underlying portfolio companies. Instead, investors have data, such as cash flows, to calculate what’s called the internal rate of return, or the IRR, of the fund. That means, “the true investment risk within their PE portfolios is largely unknown,” according to the paper.
Measuring performance with internal rates of return also makes it difficult for investors to compare the returns of different private equity funds and to contrast the strategy with what they would have earned in the public markets. Monk and his co-authors argue that the measure is heavily influenced by returns earned early in a fund's life. As an example, the report cites private equity funds from the 1970s and 1980s, whose returns earned since inception are exceptional because of this property. “This is not only misleading as an indicator of their contemporary performance, but it forms a performance moat around the top private equity firms against which emerging managers and strategies struggle to appear competitive,” wrote the authors.
Other structural barriers to transparency include risk misalignment, which includes compensation structures that do not align the risk between the general partner of the fund and the investor; and the net-of-fees performance reporting model, “which adds to the ambiguity of private equity’s economic equation” and makes it difficult for investors to “follow the money,” the paper said. When performance is reported after fees, investors are blind to any information on carry, broker-dealer fees, management, and other fees charged to the fund.
“The real crux of the issue is that the LP just does not really get access to the information that is required to appraise the manager that they’ve invested into and how they’ve actually generated the returns that they’ve supposedly generated,” Sharma told II.
But, investors are beginning to demand a more transparent investment system.
In the paper, the authors propose the use of technology to modernize both investment data and performance measurement.
“Once we understand that the data must come from that underlying-holdings level rather than where it typically comes from, which is cash flows at the fund level, we’re talking about a much broader data set,” Porter said. She added that in many cases, the data is being reported, but not in an automated way.
In the proposed framework, the data provided to LPs from GPs must represent the underlying holdings of their investments and the flow of that data should be automated and flow through a secure network where information can’t be removed. With a more complete data set and automation, all of the parties involved will develop more data science tools to derive meaning and intelligence from the information. As a result, the quality of the dataset will increase and so too will LPs’ evidence-based decisions. Data science techniques have already proven useful to determine more timely valuations, now calculated on a quarterly basis, and to estimate values of companies when they go public or are sold.
“The framework we’re promoting here is really in the hands of the LP,” Porter said. “It’s really pushing toward a more public-equities style metric, so really looking at the importance of the valuation. In fact, the absence of a continually observable price [of private companies] is a structural issue, and that’s also in the realm of technology.”
In short, the framework comes down to collecting the data, using the data to help young companies develop tools to help LPs make investment decisions, and then putting the data to work to construct more effective portfolios, which includes measuring risk, Porter said.
“There is really a need for greater efficiencies in the way our asset owners allocate and manage their capital,” Porter said. “This has urgency and many benefits, not just in terms of returns but also in how capital gets allocated in our economy. Are we funding the things we want to fund?”