Mapping the next frontier in private markets: in conversation with Mark O’Hare

November 20, 2025 -When BlackRock confirmed its acquisition of Preqin in March 2025, the deal marked one of the clearest signs yet that private markets are entering a new data-driven era. Laurence Jarvis spoke to Mark O’Hare, vice chairman of BlackRock – and founder of Preqin – about the future for greater transparency in private markets.

You’ve dedicated much of your career to bringing transparency to private markets. How do you see the future for private markets data evolving?

Private markets have grown enormously, from roughly $400 billion in 2002 to over $18.6 trillion by 2024 in assets under management (AUM)* and if we look back at that timeframe, we can absolutely applaud ourselves. Over the course of the past two decades, the quality and availability of data in the private capital space has increased significantly and we’ve made significant inroads in helping institutional investors to make the best possible investment decisions.

When we look the other way, however, it’s clear we are not at the summit of mountain yet. Private markets data remains more opaque than that of public markets. Yet, with allocations to private markets on the rise, the stakes are that much higher. It’s one thing to have two per cent of your portfolio allocated to private markets, it’s quite another when we’re talking about 20 per cent or more. When you’re talking about those kinds of allocations, I believe it’s vital to have the best possible information that you can.

Our ‘North Star’ has always been the question: how can we improve the data? How can we improve the workflow tools? And how can we help our clients? In BlackRock we found a like-minded group. The acquisition has allowed us to, firstly, invest more in the raw data – expand the volume, the granularity and the quality of it. Secondly, it allows us to integrate the raw data into products that can be useful to clients, to give them insights and decision-making tools rather than raw datasets; and thirdly, we’re able to distribute those insights in more effective ways.

How far away are investors from being able to achieve true look–through and a whole of portfolio perspective?

It’s happening already. In the months since the acquisition completed, Preqin data has already been integrated into the Aladdin platform and benchmarks are available to Aladdin customers, so they are already able to get more of a whole of portfolio view. My belief is that, while we’re not at the point where private market data has reached the level of transparency that we see in public markets, AI could help unlock solutions.

Where do you see the role for AI in improving data acquisition and verification?

AI is one component of our broader technology strategy to deliver better insights and outcomes for clients, so we can deliver more accurate insights that help clients make informed decisions.

We’ve been using AI and machine learning for years, long before the arrival of consumer-facing tools like ChatGPT or Copilot. The challenge in private markets is twofold. First, you’re dealing with a mass of unstructured information – fund manager reports, LP letters, regulatory submissions – they’re all in provided different formats. The data acquisition team has to turn all that unstructured data into a structured format and traditionally, that has been a highly manual process. Then, not just building data, but looking to harness the power of AI, we have been creating customer-facing tools. An example is the forward-fundraising calendar, giving clients the ability to see what is coming up in real time across the fundraising landscape.

AI allows us to streamline and leverage that process. It’s not new, we’ve used it for years now, and it certainly doesn’t replace human intervention, but it does allow us to cover more data sources more accurately and effectively.

For example, in monitoring the performance of private equity funds, we might have multiple LPs invested in the same vehicle, each providing their own data and perspectives. AI helps us to integrate those perspectives to identify the most reliable number so we can get a better fix.

The second area where AI is becoming progressively more important is in identifying new data sources. Say you’re tracking the performance of a recent start up and there is limited information available, but there are LinkedIn reviews, there are Glassdoor reviews, recruitment analytics and so on. These are different data sources that may not give you an actual financial disclosure number, but it can give you contextual information on that company and how it’s performing. We’re doing more of that.

Of course, information that is confidential to investors is off limits so we can’t use everything but, in some cases, we can use aggregated and anonymised insights from those datasets to build benchmarks, such as valuation ranges for certain sectors. It’s that kind of optimal position of having and aggregating vast amounts of data such that you can respect the confidentiality and ownership of that data, but at the same time, give insights and value that may help everybody in the market. That is a huge opportunity.

How do you make sure AI improves data quality, rather than amplifying biases?

Clearly in areas like social media, AI can amplify bias and create echo chambers, but that’s not how we use it. Most of the information we collect is hard, factual information – it’s the number of employees, new contracts that are signed and so on. Where we do use alternative data, it’s a small part. We also find that having multiple independent sources allows us to identify outliers quickly. If for example ten data points align and one sits outside the range – it doesn’t automatically mean it’s wrong – but we will look at that and check and retest.

A more complex market also calls for smarter data. How are data collection models keeping up with growing investment complexity?

Absolutely, the industry is becoming more nuanced. One example is the growing popularity of continuation vehicles. Traditionally, investors would invest in buyout funds until the point of exit and then reinvest in different vehicles, and on one level that’s a great discipline. On the other hand, there are investors who think: these are great assets, they’re compounding, they’re growing ‘why would we sell?’ Those investors typically find continuation funds to be very attractive and while the concept is not brand new, the proportion of buyout exits to continuation vehicles is now nudging up to 20 per cent* so it’s becoming significant. As a result, we’ve been focusing on expanding our data collection in that area. AI can also help with more complex data pulls, like with family offices, where the information is scarce and unstructured and yet, they are increasing their allocations to private markets. Here, AI can help us make sense of diverse sources that lead to enhanced data coverage in this sector.

The growth in private credit is another example. How is Preqin looking at enhancing its coverage of data in that area?

Private credit has been a fast-growing asset class for some years now and BlackRock’s presence in that space is helping us gather more information on the sector.

These days, private credit funds are providing all sorts of different funding lines, be it direct lending, be it mezzanine, be it subordinate. Whether it’s taking the place of, or sitting alongside the banks, it’s taking a bigger share of the industry and increasingly providing a complete financing solution.

Finally, what will ‘good’ look like for private markets five years from now?

Despite all the progress that’s been made, private markets are indisputably still more manual and less easy to do business in, than public markets. By 2030, private markets could represent around 12% of the global investible universe — set to reach $32 trillion according to Preqin research.** That’s too large a segment to remain opaque.

I’m really excited about the work we are doing with BlackRock to get relevant information available in one place. It means institutional investors can access not only data, but also gain actionable insights, leverage those insights in investment decision-making, due diligence, selection and execution on one platform quickly and swiftly, and being able to do that at an attractive cost. To me, that’s what good looks like.


* According to Jeffries Global Secondary Market Review (published January 2025)

** According to Preqin’s Private Markets 2030 report (published October 2025)


This article was originally published on Fund Business. Click here to view the original version.