Private credit has grown from a niche corner of finance into one of its fastest-moving arenas. Capital moves quickly; the data describing it often does not. Loan terms, borrower details, collateral, settlements, and investor positions live in different systems, spreadsheets, and inboxes. That gap between how fast money moves and how slowly its data catches up is exactly where operational risk hides - and it is the gap Siepe was built to close.
Siepe, based in Dallas, describes itself simply: Data Driven. Performance Focused. Founded in 2012, the company makes cloud software and tech-enabled services for private credit, CLO (collateralized loan obligation), and alternative investment managers. Its platform is designed to take feeds from borrowers, lenders, and investors and present them in one centralized, real-time format that front, middle, and back-office teams can all work from.
"Our mission is to help credit managers better leverage their data to reduce operational risk and increase alpha."
Michael Pusateri · Founder & CEOAn operator's company
Siepe did not come from outside the industry looking in. Founder and CEO Michael Pusateri previously served as chief technology officer at Carlson Capital and as co-COO and CTO of Highland Capital Management. In other words, he ran the technology that credit managers depend on before he built a company to sell it. That lineage shapes the product: Siepe positions itself less as a vendor and more as an extension of a client's own team.
The name reflects the same insider sensibility. "Siepe" is the Italian word for "hedge" - a nod to the hedge funds and credit managers the company serves, pronounced see-EPP-ay.
What clients actually get
The pitch to a fund manager is concrete. Rather than hiring more analysts every time assets grow, a manager can lean on Siepe to automate the middle and back office - reconciliation, post-trade settlements, profit-and-loss, reporting, collateral administration, and compliance. The result the company describes is scale without a proportional increase in headcount or cost, with cleaner data as the foundation for better front-office decisions.