Evolving technology is helping to open up private credit to a wider pool of investors. Aysha Gilmore reports…
The use of technology and in particular artificial intelligence (AI) have become wrapped up in a new wave of hype in business, finance and investment. Since the rise, much of the discussion around AI specifically focuses on efficiency, but does it have more to offer the private credit space?
As general partners (GPs) in private credit try to unlock more capital from limited partners (LPs) and the wealth market, technology could play a vital role in expanding access to the asset class.
Reshaping portfolios
Yuriy Shterk, Clearwater Analytics’ global head of alternatives, says the key lies in AI helping LPs with total portfolio construction. For many LPs, private credit is only part of their portfolio and understanding how it fits in and what it contributes to overall performance is an area where technology and business innovation are making a difference.
“If I am able to track my portfolio as a whole and understand my performance, I have more money available as I no longer need to reserve cash to cover side effects. I can use this cash and deploy it into additional assets,” says Shterk.
If the technology is in place to enable this, he asks, can it expand the size of the market?
“The answer to that question is yes, it will. If you have an accurate representation of your portfolio as a whole, that will free up additional capital. This capital cannot be deployed in public markets because that space is limited, so where is it going to go? It is going to go into private.”
In the past, technology and innovation have already helped to open the asset class to LPs and, in turn, allowed the industry to grow. Areas that were traditionally not considered investable, such as mortgages, have become more accessible through improved data and systems.
Five years ago, mortgages were rarely viewed as a core LP allocation, but technology has enabled that asset type to become, in Shterk’s words, a “hot and sexy asset type in private credit portfolios”. Clearwater Analytics works with a range of LPs, the majority being insurance companies and pension funds, while endowments are increasingly exploring the private credit space.
“Nowadays, the vast majority of institutional investors either have mortgages as part of their portfolio or are seriously considering it,” he says. “The challenge was the amount of loans. There are no longer 20, now there are hundreds and thousands, and now with them in play, AI helps with that.”
Construction process
However, beyond freeing up capital through better portfolio construction, AI and technology tools are making it easier for investors to interrogate data across private credit managers and strategies which is likely to reshape the entire process.
The changes to LPs’ portfolio construction processes are where technology is likely to have “meaningful disruption”, according to Kevin Hogan, global head of private credit at Aztec Group.
As more private markets data becomes structured, these tools make it easier for LPs to compare opportunities and assess managers, an area that has traditionally relied on relationships and static reporting, explains Hogan.
Technology is sharpening comparisons around performance, risk, sector exposure and underwriting quality and overtime is likely to reshape portfolio construction processes as adoption increases, he adds.
Lowering barriers
Alongside this, private credit is opening up to a wider range of investors, including defined contribution pension funds in both the UK and US, with technology playing a role in lowering barriers to entry for these groups, Hogan says.
The role of technology is noticed through helping GPs develop semi-liquid products, which allow retail investors to enter that market while maintaining some flexibility, unlike traditional private credit investments such as direct lending which locks up capital for long periods.
“Technology is making private credit more accessible by digitising onboarding, Know Your Customer (KYC) and subscriptions, which supports semi-liquid and retail-friendly structures,” Hogan explains. “But it also demands stronger data infrastructure and real-time reporting. It’s not just widening access; it’s reshaping the operating model.”
These semi-liquid products require more frequent liquidity management, cashflow movements and tighter reporting cycles, which is overall driving a rapid build-out of data infrastructure. This includes real-time interfaces, automated reconciliation and faster, more transparent reporting for both investors and regulators.
“In short, technology is enabling broader access while reshaping private credit’s operating model to support a more diverse investor base,” Hogan adds.
Competitive edge
GPs’ technology adoption for data and information is also becoming a factor for LPs when deciding where to allocate capital, says Ivan Latanision, chief product officer at Allvue Systems.
“Competitive positioning for fundraising is a factor,” he explains. “When LPs are carrying out due diligence, they are looking at your technology infrastructure.
“If you have systems that are totally manual and it takes a month to pull everything [data] together, you will always be at a disadvantage.”
LPs increasingly want more information on performance and benchmarking, says Latanision. This was reflected in a recent GP survey conducted by Allvue, which found that firms with advanced data capabilities were twice as likely to report that their returns over the past year were well above average, compared to firms with only average data capabilities.
Latanision also raises the point that within public markets there is large amounts of data that is readily available, while “private markets are nothing like that and very opaque”. Technology has helped to lift some of the opacity in the market, which has long put off some investors from accessing the market.
“We know that LPs are hitting our GPs with all sorts of ad hoc reporting requests,” he says. “They want it more frequently, and this is an area where AI can really help. If you can get your data into a normalised, centralised repository and have the ability to apply business intelligence or standard reporting capabilities on top of it.”
Oshri Harari, chief operating officer and general counsel at the Liquidity, which is an AI-driven fintech private credit lender added that technology is speeding up investor due diligence, improving risk pricings, widening access to deal flow and allowing a broader range of qualified investors to participate in private credit.
“Combined, these advancements are creating a more transparent, data-driven and accessible marketplace, one that is progressively opening private credit to new participants without compromising rigour or governance,” he says.
Harari also points to recent advances in processing unstructured data. Natural language processing can now be used to analyse legal documents, call notes and financial models and convert them into usable intelligence.
“This creates a continuous monitoring environment where we can track covenant compliance and borrower behaviour in real time, rather than waiting for quarterly reports,” he says.
“The competitive advantage will go to those who use AI to price dynamically and execute quickly.”
It appears that technology has the potential to grow the global $3tn (£2.2tn) private credit industry even further, extending its reach to more investors’ portfolios.
Therefore, as GPs seek to unlock more capital from wealth and retail channels, the adoption of technology, and, in turn, AI, will become increasingly more critical.
