Key Takeaways

  • Software buyout debt holds an equity cushion averaging 13 to 14 turns of EBITDA, protecting direct lenders against severe enterprise value drops.
  • Private equity sponsors who bought software assets at 20x EBITDA with 6x to 7x debt carry nearly all the risk if multiples compress to 12x or 14x.
  • Ares Management avoided tech borrowers vulnerable to artificial intelligence displacement during initial investment committee screening.
  • Private credit capital structures remain insulated from tech headlines because lenders underwrote to cash flow coverage rather than equity expansion.

The Mathematical Buffer Protecting Direct Lenders

Market chatter around a tech sector meltdown has raised alarms that bad software buyouts will drag down private credit portfolios. Bain partner Hugh MacArthur pointed to industry conferences dominated by anxiety over a "SaaS apocalypse" and asked whether buyout distress is infecting private debt funds.

Kipp deVeer dismissed the panic by pointing directly to balance sheet math. “My simple answer is I think it's more of a problem for the owners of some of these assets than it is for the lenders to these assets,” deVeer said.

During the peak buyout frenzy, sponsors paid 20x EBITDA or higher for recurring-revenue software companies, but private credit funds rarely provided more than 6x or 7x debt. “For the most part, companies that got bought for, pick a number, twenty times EBITDA, that got leveraged six or seven times,” deVeer noted. “So the lenders have quite a lot of room for reduced valuations.”

A sponsor who overpaid faces painful write-downs if multiples compress, but the senior debt remains intact. “Is the company that got paid twenty times for, is that worth twelve times? Is it worth fourteen times? Is it worth sixteen times? I don't know,” deVeer explained. “But I think the question is more for the equity than it is for the debt.”

Underwriting for Tech Disruption

Beyond valuation compression, sponsors worry that artificial intelligence tools could replace seat-based enterprise software entirely. For private credit managers, this risk had to be filtered out before the loan closed.

deVeer explained that Ares addressed generative AI exposure directly at the investment committee stage rather than reacting after headlines began multiplying. “We weren't really leaning into companies that we thought would be materially disrupted by AI in the first place, so I think we're pretty well set up, and it's not something that's a significant concern for us these days,” deVeer said.

Direct lenders avoid underwriting businesses whose core products can be coded away by small teams using automated models. Instead, senior lenders favored mission-critical vertical software with high switching costs and embedded operational workflows. When enterprise value drops from 20x to 13x, the equity sponsor loses 35% of their capital, but the direct lender continues collecting interest payments on an asset that still generates enough cash flow to service its 6x debt stack.

Why It Matters

This gap between debt stability and equity pain signals that headline software distress will not translate into a systemic credit collapse. While private equity sponsors must face difficult LP conversations, lower returns, and delayed exits, large credit platforms with disciplined attachment points will absorb the cycle without impairment.