Special report: Leveraging AI
AI is predicted to transform private credit, but there is still a long way to go. Jon Yarker explores the technology’s potential…
AI is almost unavoidable in 2025 with constant discussions around how this technology could radically change many elements of financial services. Private credit fund managers are already using and exploring AI, although adoption is in its early stages.
A common theme around AI is its ability to speed up tasks that people will have manually executed before. Some firms are now using the technology to complete previously arduous tasks, thus freeing up their employees’ time for other efforts.
For example, Man Group is actively integrating AI across its investment processes, particularly in private credit through Man US direct lending. There, AI is used in document processing and data extraction through proprietary automations to drive greater efficiency at these stages. As such Putri Pascualy, senior managing director and client portfolio manager for private credit at Man Group, says this has reduced the processing time per document from 15 minutes to just three.
“This significantly saves analyst time and reduces keying errors in daily workflows around credit ratings for private loan securities,” she explains. “Private credit is a very document-heavy business – every loan has lots of documents, and every time there’s a change in terms, there are more documents. With AI, we can do data scraping which reduces the time we need to analyse all these documents significantly.”
Tech provider Oxane Partners, which works with many private credit firms, explains that AI is a “partner in performance”, acting as a catalyst for better decision-making.
“We’re leveraging AI to automate manual and onerous tasks with a well-defined scope, within clear guardrails and human-in-the-loop checkpoints,” says Oxane’s managing director Kanav Kalia. This can include automating workflows around data validation checks, deliverable tracking, data extraction from financial documents, reporting, and other manually intensive processes.
“The key is having a well-defined scope, breaking complex tasks into smaller chunks that AI can reliably handle, and building in verification points,” he adds. “AI [oversees] the repetitive execution, while teams validate the outputs and remain in charge of decision-making.”
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Many private credit firms are at a point of adoption, reviewing already established processes and assessing where AI can be integrated to automate and enhance. Liquidity is coming at this from a different perspective as a private credit firm built on a proprietary AI platform. Co-founder and chief science officer Oron Maymon explains that the firm’s AI and machine learning (ML) systems screen markets and generate full investment reports after scoring and analysing these. Deals are then structured and stress-tested through hybrid ML engines, and monitored continuously through live data flows and intelligent alerts.
“We see AI transforming private credit from reactive analysis into proactive capital intelligence, where the entire lifecycle, from origination and structuring to monitoring and exit, is continuously optimised,” adds Maymon. “Our goal is to push AI beyond analytics to act as a full decision-support engine that autonomously assesses borrower health through real-time data feeds, simulates macroeconomic scenarios and recommends portfolio adjustments before risks even surface. We’re very close to achieving this.”
Tomorrow’s AI applications
Private credit firms are clearly sold on the merits of AI and, in an industry that is becoming increasingly competitive, more are looking to this technology as a way of edging out their peers.
At Man Group, the firm is exploring opportunities to automate more of its pipeline through the creation of workflow tools around automation and the centralisation of deal data.
“There are significant opportunities in the mid-market space where AI can help us unlock opportunities by allowing firms to work through many more deals,” adds Pascualy. “The smaller the deal, the greater the volume of trades required to put money to work, so there’s greater emphasis on processing trades efficiently.”
Meanwhile, John Channing, chief technology officer at Mount Street, a global loan services and technology provider, sees scope for further AI innovation through the use of model context protocol servers to help standardise large language models and help them connect with external tools, data sources and services.
“This will make up-to-date, business-specific data available in AI tools, rather than just the data in the training set,” says Channing. “We anticipate being able to ‘chat’ with our loan and collateral data and to be able to generate insights through querying, analysing and summarising data through a natural language interface.”
Liquidity is pursuing a similar approach, where Maymon says the ambition is to build an “autonomous private credit” where AI underpins every stage of the process, from sourcing opportunities to managing loans.
“Ultimately, it’s about enhancing human judgement, freeing investment teams to concentrate on the most strategic and high-impact decisions,” he adds.
The pursuit of autonomy
AI is playing an increasingly important role in supporting investment teams and questions about its ability to operate with autonomy are inevitable. Could this technology fully usurp the decision-making power of a human being?
Many in the industry are unconvinced about this and see the need for maintaining human input as crucial. Benjamin Lamping, chief executive at Reframe Capital, is not an expert in AI but sees several use cases for it to make investment teams’ lives easier and predicts that it could eventually augment high-value tasks. However, he is pragmatic about its limits.
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“Full autonomy is limited: final judgments on management quality, sponsor incentives, or niche risks at this time remain human-led,” says Lamping. “AI functions as an active collaborator, facilitating analysts’ productivity and insights rather than fully replacing human decision-making.”
Others share this view, anticipating AI and humans to become closely interlinked within investment but with humans remaining involved. Man Group’s Pascualy sees the “future” of private credit hinging on the convergence of human expertise and cutting-edge technologies like AI.
“Personal relationships and networks will always play a crucial role in deal origination,” she says. “Our part of the business is ‘AI-proof’ in that sense – human judgment and relationship-building remain irreplaceable.”
This sentiment is even shared by the providers of the technology itself. Henry Lindemann is co-founder and chief growth officer at Blueflame AI which provides AI solutions to alternatives sectors including private credit, and he admits there are limits to AI.
“AI is increasingly supporting higher-value investment activities in private credit, complementing rather than replacing human judgment,” says Lindemann. “While AI excels at identifying patterns and suggesting options, final decisions remain in human hands, preserving the judgment, experience, and relationship management that have been pillars of successful private credit investing.”
AI may not be set to replace humans completely, but it is starting to influence how private credit firms view talent. Intensifying competition in private credit is forcing firms to pay out more to attract the best talent, but AI could change how some of these roles are prioritised.
“The landscape is rapidly evolving, and AI will be an increasing component of private credit processes as it develops greater capabilities and ultimately robustness in its decision making,” says Simon Heath, chief operating officer and corporate finance partner at Heligan Group. “It will become a substitute for talent, and this is starting to be experienced at more junior grades with a lower volume of graduate roles across the industry. AI will reduce the requirement for middle management also.”
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As well as undermining some roles, AI will change how other functions are viewed. Liquidity’s Maymon sees this evolving to ironically champion two distinct skillsets: “First, those who can work effectively with AI, who think logically and precisely about what they’re asking for, will have an advantage over those who just know how to code.
“[And] second, people with strong interpersonal skills will thrive. As technology streamlines decision-making, human connection becomes even more valuable.”
AI will continue to dominate many conversations, especially in an industry like private credit where there is a growing pressure to compete and stand out from the pack. AI is already being actively integrated in many firms’ investment processes, but instead of replacing the ultimate human decision-making function this is highlighting the need to keep this out of AI’s reach.
