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Rather than anticipating defaults, Permira sees the broad sell-off in software loans as a chance to buy fundamentally sound debt at a discount, expecting it to recover to par value without restructuring.
The market is indiscriminately punishing all software debt, creating bargains in quality companies with strong free cash flow. These firms will likely now prioritize paying down debt over M&A, mirroring the successful recovery playbook seen in the energy sector a decade ago.
The most significant risk in software-focused private credit isn't established companies but those underwritten on Annual Recurring Revenue (ARR) multiples instead of cash flow. These high-growth, non-cash-flowing businesses may never reach profitability if disrupted by AI, creating a major potential vulnerability.
Despite fears of AI disruption, private credit software loans have significant downside protection. With loan-to-value ratios around 30-40%, there is a substantial equity cushion. A company's value must erode by nearly 70% before the lender's principal is at risk, highlighting the structural safety of debt versus equity.
Historical analysis of distressed cycles in sectors like energy and retail shows that roughly one-third of the industry's debt defaulted over a two-year period. Applying this precedent to the software sector, which has approximately $300 billion in debt, suggests a potential default wave of around $100 billion if current pressures continue.
While public software stocks have dropped 20-30% on fears of AI disruption, credit markets, particularly private credit, remain confident. Lenders are protected by low leverage multiples (1-6x EBITDA) and a substantial equity cushion, making them less sensitive to equity valuation shifts.
An expert warns of a "mini bubble" where private credit funds lent heavily to PE firms buying unprofitable software companies based on high ARR multiples. With falling valuations, AI disruption, and a wall of debt maturing, a wave of defaults and restructurings is imminent.
Permira focuses on complex opportunities where deep operational and sector understanding is required. They believe this complexity is often confused with higher risk, allowing them to earn a significant premium.
With fewer traditional credit cycles, the most fertile ground for distressed investing lies in industry-specific downturns caused by technological or policy shifts. These "microcycles" offer opportunities to invest in good companies working through temporary, concentrated disruption.
As over-leveraged software companies fail, a new investment class will emerge. "Software special situations" funds will acquire these distressed assets from creditors, abandon growth-at-all-costs, and focus on restructuring for profitability and dividends, akin to a Constellation Software model.
Despite market fears about AI disrupting software companies, underlying private credit loans are structured defensively. They are often written at a 30% loan-to-value, meaning there is a 70% equity cushion before the lender's principal is at risk.