The Voices of Private Credit: David Pollack, SWFL Consulting

Q: Please introduce yourself, your current role at SWFL Consulting, and your background.

A: My name is David Pollack, and I’m the managing partner of SWFL Consulting. I started my career at a hedge fund, spending about four years building custom solutions for portfolio accounting and tracking. I then moved to Framework Software, which specialized in private equity fund accounting. I then went on to Centerbridge, building custom solutions for waterfall calculations, private equity fund accounting, portfolio tracking, generating capital calls and distributions, and monitoring—all in one system.

Eventually, I launched SWFL Consulting. We focus on infrastructure work, specifically around Office 365 workflows, Power Automate, Azure Logic Apps, and Power BI.

With my background knowledge of how these systems work, including the components and allocation mechanisms, I can provide a higher level of service. You don’t need to explain concepts like allocation rules or waterfalls to me—I get it. I can read the LPA, understand it, and quickly start putting everything together by identifying the data sources and building the necessary workflows.

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

A: A major change from five years ago is that private credit firms are now far less hesitant to invest in technology solutions. In the past, only firms with deep pockets could afford to invest not only in these technologies but also in teams of consultants and developers to build these custom solutions.

Now, many more solutions are available almost off the shelf without such significant expenditure. These solutions are also far more targeted at specific needs. The explosion of cloud infrastructure has made it much easier to integrate different systems. For example, you can now plug a payment platform into an accounting system, and it will work with limited effort because of the APIs and integrations available today.

All the Office 365 solutions, AWS, and similar platforms greatly facilitate this connectivity. The tech infrastructure simply didn’t exist before, making it much harder to implement such solutions. Now, it’s cheaper and easier to implement these technologies.

Additionally, there are significant compliance and operational requirements now that didn’t exist before. Reporting and other regulatory demands necessitate these tools to operate effectively in the market. Without them, firms would be buried in paperwork and would need to expend a lot of resources on personnel just to generate these reports.

Q: What technological or operational advice can you give emerging private credit firms or fund managers to ensure they can profitably grow while minimizing risk?

A: When looking for a technology solution, you must understand what you need as an output.  Consider your reporting requirements as they relate to compliance, investor relations, servicing your portfolio, and risk management.

Start by identifying which platform or solution can address as many of these reporting needs as possible. Many solutions are available, but I haven’t seen one that could tackle everything. You may need more than one, but whatever you decide, find those solutions that fit you best for your firm’s needs.

Next, address the data sources that will feed this software. Strive to consolidate all the data into one place, such as a data warehouse. Start with your required reporting and operational needs, then work backward toward the solution that makes sense. It may seem like a lot to consider upfront, but if you do it early, this organizational effort will pay off in many ways as you grow.

Q: How do envision the role of AI to impact the operations of private credit firms?  

A: I think there are misconceptions around AI, such as the belief that you can teach it a bunch of things and then not have to touch it or be involved with it. AI has many strengths, particularly in pattern recognition. For instance, it’s very good at reading documentation and contracts, pulling out terms, and flagging certain terms.

For example, consider call notices and distribution notices. If I’m at CalPERS and receiving thousands of these notices, I might want to set up rules to quickly identify if management fees exceed a certain percentage of the distribution or if the total fund amount being called deviates from a certain percentage. AI can read the notice, flag any discrepancies immediately, and handle error capturing. This kind of application would be tremendously powerful.

At this point, AI will be a very powerful tool for tasks like reviewing large amounts of information quickly. It can empower a single person to handle much more than they could in the past. However, AI still requires human oversight to review its results and ensure they make sense. It’s not perfect on its own, but it can significantly enhance productivity.

Q: Final and most important question: What was your first car, and do you have any fun stories about it?

A: My very first car was a 1985 GMC Suburban. By the time I got it in 1998, it was dirty, rusted, dented, and made funny noises. I lived in a fairly well-off town, and while all my classmates had nice cars, everyone seemed to love my beaten-up SUV. On Friday nights, about 15 people crammed into my Suburban, cruising around. No one cared that it wasn’t a BMW; they thought it was awesome. That was my first car, and I loved it.