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BlackRock: Closing the technology gap

In the future, private markets firms can expect to benefit from risk management tools, unstructured data collection and advanced analytics, says BlackRock’s Sloane Collins

This article is sponsored by BlackRock.

How do you see the role of technology evolving over the next few years for measuring and managing risk in private markets, particularly in private equity?

Sloane Collins

We expect technology to play a growing role in measuring and managing risk in private markets. We think there is a significant gap between the tools and capabilities that investors in the public markets now take for granted and those that private market investors have access to today. Private market investors will require these tools in the future as the investor base broadens and their allocations increase.

Investors who are allocating dollars to these asset classes are going to want to understand risk and performance with their particular holdings in much more granularity and with more consistency. Firms that are managing funds on behalf of those investors will also require those tools to provide insights back to their investors and to help themselves make decisions in a scalable way.

Traditionally, public assets and private assets have been thought of as completely different animals, but there are some common dimensions. For example, both a publicly traded company and its private equity-backed counterpart within the same industry are operating in the same economy, and they are looking at similar factors that influence revenues and performance. Another example is bonds and private credit – the public versus the private sector – with their common credit risk factors.

As technology innovators, we are actively trying to fill in the gap, to provide the same types of tools to measure risk, project cashflows and perform scenario analysis on private markets exposures that align with the tools that exist for public markets. However, it is going to take time to develop these tools because you need a lot of granular data to start building these advanced risk analytics. There is a significant disparity between public markets and private markets data in terms of data availability, granularity and quality.

Can technology help democratise private markets by reducing the informational advantage that the largest investors now have over smaller investors?

We think technology is going to play a critical role in reducing that informational gap between large and small investors. If you look at very large and sophisticated investors, they have sizeable resources in developed analytics and research teams. They also have large budgets for purchasing data, and that powers a lot of insight into how they can make decisions in the private markets. Historically, there have been barriers to entry in the private markets, including regulatory barriers, and this type of information wasn’t easily available to small investors. Technology is really the only way that we see to equip a broader investor base with the same kind of analytical capacity and access to data that those large and sophisticated institutional investors have had.

We feel like we can play an important role in this with our Aladdin®, and eFront® platforms. Specifically, with the eFront® platform we have a data business that is increasing transparency for the private markets, and we have some of our most experienced professionals who have worked in the analytics space for years developing advanced analytics. We are building advanced analytics into technology solutions that we can deliver to institutional clients of all sizes.

Our hypothesis is that this trend of the broadening investor base in private markets is going to continue, particularly with smaller-sized professional investors in terms of the dollars they are allocating. We believe technology is going to be critical to enabling that.

What is natural language processing, and how is this technology helping private equity investors?

We think about natural language processing as technologies designed to make humans more productive by eliminating repetitive and tedious tasks. It involves computers extracting data points from unstructured sources, such as documents, webpages and emails. This technology extracts those data points at scale, following a set of rules.

Similarly, machine-learning technology helps discover patterns in those datasets, allowing you to be a little bit smarter around correlating certain data points or bringing certain fields and a data point together. We use the combination of these technologies to drive our data business and to extract data from hundreds of thousands of documents on behalf of our clients.

What potential applications do you see for technology-aided ESG reporting in private equity, both for GPs and LPs?

At BlackRock we are both an LP and a GP, and we are also a service provider to more than 100 LPs that collect data. We collect data from more than 10,000 funds for those LPs, so we are uniquely positioned to understand the challenges on both the LP and GP side.

There is a huge demand from LPs for quantifiable ESG data. There is also an evolving regulatory landscape globally for ESG disclosure requirements. The challenge we are dealing with is there are a lot of GPs that are not reporting ESG information to LPs, and when it is reported, it is very varied. In addition, because there are so many different ESG reporting frameworks in place globally, it becomes very cumbersome for LPs, even if they get the data, to comprehend what is in it. That is the pain point for LPs.

Meanwhile, on the GP side, managers are being asked for all of these custom requests from their LPs. That means there is also a tax on them to think about: “OK, so now I have to put this data in eight different formats,” for example. We think there is an opportunity for collaboration across all of these channels, and investor interest and technology will be a big part of that.

We also believe GPs will have to quickly establish ESG monitoring processes because, before they can report all this information, they need to collect it and understand what the exposures are for their portfolio companies or the companies they are lending to. GPs are also going to need technology and solutions to help, both with data sourcing and with interpreting and understanding that data.

Furthermore, right now, there is not a broad industry benchmark that allows either GPs or LPs to assess whether an ESG number is necessarily good or bad. So, we will also need technology to help deliver benchmarks.

Sloane Collins is head of product strategy for private markets technology solutions at BlackRock