With the adoption of artificial intelligence and machine learning tools skyrocketing in the wake of ChatGPT’s launch late last year, its potential to revolutionise private credit has been thrust into the spotlight. Right across the asset class, from deal origination and due diligence through to investor reporting, accounting and risk management, the scope for managers to leverage the efficiencies of AI to work smarter could fundamentally change the status quo.
In California, the TerraCotta Group has long been at the forefront of applying data analytics and quantitative techniques to commercial real estate lending. Founder Tingting Zhang says narrow AI is already proving a powerful addition to real estate credit investment processes by using robots to think like humans.
“If we were to make an investment in a shopping centre, for example, as a human expert we would be very interested in the location of a property,” says Zhang. “The human expert would go for a look around, see how many people were in the shops, how affluent the area looks and how busy the car park is.
“Now, using various machine learning algorithms, we can get that data instantly from government sources, cell phone information, public sources and our own proprietary platform.”
Speed is the big advantage, she says: “The ‘robots’ are very quick to compute. For a human to look at 60 data points would take days, but the machine can do it instantly, it can detect patterns, and it doesn’t make mistakes or take a more optimistic or pessimistic outlook depending on its mood.”
Once the AI has identified an investment as being in a good location, human judgment takes over to move forward in how TerraCotta thinks about the credit.
Outside investment processes, many private funds are looking to integrate AI into their back-office and middle-office processes to speed things up, deliver enhanced insights and save on resources.
“When we talk about AI in fund servicing, we are not yet at the stage of using a friendly robot that produces your NAV while drafting the minutes of your next board meeting and advising on your ESG strategy,” says Agnes Mazurek, global head of private markets innovation at Apex Group.
“It is unlikely we will be there for many years because adoption of AI tools is very gradual. What we have now is a lot of tools that digitise information and we are seeing a lot of initiatives across private credit to create the building blocks to get there.”
Keith Miller, global head of private debt at Apex, says this is reflected in the growing number of conversations about opportunities for AI around the review of underlying assets. “That credit review process has always been incredibly manual but the big win for the asset class is the ability to review the underlying assets from a portfolio and risk monitoring perspective and conduct predictive modelling across assets to deliver scenario analysis.”
Accelex is one company harnessing AI to bring more transparency to the asset class, with technology that gives firms timely access to performance and transaction data from funds in a clean and easy-to-analyse format. Their tool automates the extraction and preparation of data, giving managers quick access to thousands of data points that would previously have taken huge effort to obtain, and allowing them to significantly enhance the accuracy of their reports.
Nicole Weder, co-founder and chief product officer at Accelex, says: “The additional complexity of private debt investments means reporting requires more granular data for investment monitoring and decisions. Debt teams need access to instruments rather than just asset-level information. In response, we have upgraded our data science capabilities to capture that detail.
“Investors want easier access to this data. They want to know what securities we are invested in, where we are in the capital structure, what the risk is, what kind of cashflows will be happening in the future. We also have an analytics suite, because if an investor is able to extract that data in real time, we can tell them what is happening in their portfolio, what the return drivers are, and then they can decide whether they want to make a commitment to the next vintage or the next fund from a particular GP.”
Right tool for the job
Other service providers and technology companies are developing their own tools to automate everything from the calculation of carried interest allocations to deal sourcing and ESG reporting.
Alter Domus has created its own version of ChatGPT and is already using bots across its business to help clients automate complex processes.
Davendra Patel, head of AI and automation at Alter Domus, says: “We have automation that can read emails, take out the attachments, automatically classify them, extract information and then summarise that in a report. We have been working hard on building this for the last four years and we are starting to see the fruits of that. It is a game changer, not only for us but also for our clients.”