The Voices of Private Credit: Jon Hodges, FIS

In this installment of “The Voices of Private Credit” series, we feature Jon Hodges, SVP – Head of Private Credit Solutions at FIS. Jon discusses the growing appetite among private credit firms to invest in technology and shares his insights on the best ways to incorporate AI into operations. Learn how Jon’s journey from startup founder to FIS has shaped his perspective on leveraging technology for operational efficiency.

Q. Please introduce yourself, your role at FIS, and your background.

A. My name is Jon Hodges. I’m a Senior Vice President within the Trade and Asset Services group at FIS, which is part of the Capital Markets division of FIS. I am responsible for a business called Virtus from FIS. We provide services and technology to asset managers, mainly in the structured credit space, predominantly invested in loans, both public and private.

I joined FIS in 2020 when Virtus was acquired by FIS in 2020. Prior to that, I had my own startup, which was acquired by Virtus. Our startup focused on order management and portfolio management specifically for credit managers. However, rather than targeting those who bought loans, we catered to those who purchased structured notes collateralized from pools of loans. This was mainly aimed at the hedge fund side, which had been my background before that.

Q. How would you explain “private credit” to a colleague or friend not familiar with this space?

A. I would say private credit is a loan between a borrower and a single lender or a small group of lenders. In basic terms, that loan is typically secured. It could be secured against collateral, which might be a company. In that case, you’re in the capital structure of that company if there were to be any kind of event. It could also be real estate, real assets, or any number of things.

Typically, private loans are quite bespoke. The terms are agreed upon between the borrower and the lender. This often means there can be quite a bit of variability in how a default might be determined from one loan to the next. The terms of these loans are private, hence the term “private credit.” Only the borrower, the lender, and any third parties given specific access to the credit agreement will know the terms of that loan, and they’re not usually traded very often.

Q. How has the demand for technology solutions to improve private capital firm operations changed in the past 5 years?

A. Private credit has always been a feature of capital markets, but it has certainly grown in popularity in recent years. This growth is largely because people see it as an area where they can achieve outsized returns. Traditionally, private credit operations have been heavily manual since the loans are bespoke. Excel has generally been the tool of choice, with different ways of modeling deals, making it hard for systems to cope due to the lack of a standard approach.

Our experience shows that firms are now more willing to invest in technology to have a more robust and secure platform. With the consolidation in the asset management industry, private credit asset managers are becoming part of larger asset managers with bigger technology footprints. This brings a greater burden around security, uptime, and other operational requirements. Stitching things together with Excel is no longer sufficient in this environment.

We are definitely seeing more investment in platforms. However, firms still seek flexibility within these platforms because there are many ways to structure private credit deals.

Q. In your experience, what operational or technology advice can you give emerging or established firms who want to grow their private credit portfolio?

A. It’s challenging for newer managers to always define exactly what they want deals to look like. However, driving consistency across deals can really pay off operationally. If you can standardize your reporting and ask your borrower companies to report in a standardized way, it allows you to pull data in quicker, review covenants more easily, and track investments much more efficiently. This approach provides greater scale, more opportunities for automation, and significantly reduces risk.

This consistency is driven by deal-making. If you have the scale, name, and market presence, you can probably enforce this standardization. However, if you’re a newer player, you might be driven more by the opportunities available to you, which might not always allow for this level of standardization.

On the technology side, managing information is key. At FIS, many of the firms we speak to are focused on data management and mastering data across companies. These companies might also have public debt or equity, so it’s crucial to consistently analyze data across all these potential asset classes. Being able to synthesize this information quickly and make fast decisions is extremely important, and this is where front office technology can be very beneficial.

Scaling operational teams quickly is also challenging. Finding people with the right subject matter expertise is difficult in this competitive and specialized market. This is where outsourcing to a provider like FIS, for example, can be advantageous. By outsourcing operational tasks, firms can focus on what they do best—the investment piece—while allowing a partner to drive operational scale.

Q. How do you envision the role of AI impacting the operations of private credit firms?

A. In this space, there’s a lot of opportunity to apply AI in various forms, given the manual nature of the work and the diverse document structures and terminology. However, there’s an assumption that if you give a document to a large language model (LLM) and ask it a question, it will always give you the right answer. Our experience shows that this isn’t the case most of the time, especially with legal documents. These documents often have dependency clauses, where, for example, the maturity date can change based on certain factors. What we have found effective is a combination of LLM, machine learning and human review or validation.

Q. Just to get to know a little trivia about you, what was the first car you ever owned?

A. It was a 1985 Vauxhall Nova. I bought it in 1997 when I was 17. I paid £1,350 for that car, which I had saved up from my weekend job. It had wind-down windows and a traditional carburetor. You could change the oil yourself. It was definitely an older car—no air conditioning, no radio. I had to buy a separate radio for it, if I recall. But, it never let me down. What can I say? It was a great car.