Private Credit, M&A, and AI Infrastructure Funding Dominate Credit Market Discussions

London – Discussions at the Morgan Stanley European Leveraged Finance Conference today revealed three key topics dominating concerns and opportunities for credit investors globally: the evolving private credit landscape, the resurgence of merger and acquisition activity, and the massive capital expenditure required to support artificial intelligence infrastructure.

Experts defined private credit as lending by non-bank institutions, increasingly to companies with credit ratings comparable to CCC to B in the public markets, but with stronger covenant protections. “The credits in the private credit market are weaker,” explained Vishy Tirupattur, Morgan Stanley’s Chief Fixed Income Strategist, “But on the other hand, the quality of covenants in these deals is significantly better compared to the public credit markets.” While concerns exist regarding the opaqueness of some private credit deals, analysts do not currently anticipate systemic risk, predicting default rates will remain slightly above long-term averages. For context, understanding private credit is becoming increasingly important as it expands beyond its traditional scope.

Regarding M&A activity, Andrew Sheets, Head of Corporate Credit Research at Morgan Stanley, noted that while activity is increasing after a post-COVID lull, current transactions are structured more conservatively than those preceding the 2008 financial crisis. “We’re still catching up,” Sheets stated, adding that equity contributions in current leveraged buyouts are substantially higher than in the past. This cautious approach, coupled with stricter regulations implemented after the 2008 crisis, suggests the market isn’t yet mirroring the conditions that preceded previous downturns. The potential impact of deregulation remains a key factor to watch.

The funding of AI infrastructure is estimated to require approximately $3 trillion in capital expenditure, with roughly half expected to be covered by the operating cash flows of hyperscalers. The remaining $1.5 trillion will likely be sourced through various credit channels, including a developing market for asset-based finance. “For AI to go from where it is today to substantially improving productivity…that CapEx needs to go through credit markets,” Tirupattur emphasized. This demand for capital is significantly different from previous tech booms, with much of the funding coming from highly-rated companies with strong balance sheets, as detailed in a recent Morgan Stanley report.

Analysts expect to see continued growth in AI-related capital expenditure and ongoing monitoring of credit market dynamics.