Private credit fund managers embrace AI despite risk warnings
Just a year ago, artificial intelligence (AI) was being touted as the next big thing in private credit. Today, it has firmly established itself as part of the private market ecosystem, in a variety of ways. Many investment houses are already relying on AI to automate their back-office processes and free up junior analysts to do more specialised work.
However, a recent report by Moody’s found that AI has begun to be used in loan origination, causing the ratings agency to issue a warning to lenders.
“We generally expect that pools with assets underwritten by AI-based models will have relatively volatile losses, in part because of the short performance histories,” said the Moody’s report.
“In general, the shorter a lender’s history, the less predictable their loan performance is, especially as economic conditions change.”
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AI will also be limited by the amount of data that fund managers choose to share, and the quality of the historical data which relates to ongoing loans.
“What’s harder about AI and private credit, is that AI is only as good as the information that it’s being trained with,” said Cynthia Sachs, founding chief executive at data and technology firm Versana.
“And generally, most of the information to leverage for training is public data. But private credit is – as its name suggests – private. So you would have to be using private data to properly train the models.”
The use of private data has been a hot topic in the sector, but recently there have been more calls for data transparency in the pursuit of standardisation. AI is already being used to automate invoicing processes and analyse large swathes of data in the private credit world. However, any real standardisation effort would have to have the buy-in of multiple private credit firms, before any sector-wide analyses could be carried out.
It seems that the sector may get there sooner rather than later. Schroders Capital recently rolled out a new generative AI investment platform for its private markets business. It has been designed to speed up the analysis of large volumes of data within the private equity side of the business, but Schroders plans to eventually extend it to private credit as well.
And two AI specialists – Siepe and BlueFlame AI – have recently announced multi-million dollar funding rounds as they seek to bring more private credit clients onboard.
Sachs added that Versana is currently looking at AI and other distributed ledger technologies.
“We’re looking at future technologies and how they can help us build our future products,” she said. “So of course, our job is to make sure we’re at the cutting edge of technology.
“But it takes time to understand it, research it, and to know which ones are right for us.”
The demand for private credit AI solutions is clearly there, and fund managers and service providers are showing a willingness to work together to find the right solutions for the sector. But the risks remain. This is still a relatively new technology and private credit is a sector which has historically been rooted in relationship building and mutual trust.
While AI can be a useful means of speeding up labour-intensive back office processes, fund managers would do well to heed Moodys’ warnings and exercise caution by rolling it out judiciously and maintaining a human element in key processes.
