JPMorgan's Sanjay Jhamna: Software Shock is Over

JPMorgan's Sanjay Jhamna said inflows into private credit remain unquestionably strong despite recent negative headlines, signaling continued demand for the asset class. He also noted that recent AI model releases did not trigger a negative market reaction, suggesting the software-sector shock has passed. The comments point to supportive investor sentiment in private credit and a more stable backdrop for AI-linked software names.

Analysis

The key signal is not the headline itself but the absence of capitulation: when an asset class absorbs repeated criticism without disrupting inflow momentum, marginal buyers become more important than marginal skeptics. For private credit, that typically means financing spreads can stay tighter for longer than fundamentals alone justify, because allocators are still forced to deploy into a yield-starved backdrop. That is constructive for private lenders and the distribution franchises that intermediate the product, especially large banks with balance-sheet, origination, and structuring capabilities.

The second-order implication is that public credit may face a slower repricing of risk premia than equity investors expect. If private credit continues to soak up duration-sensitive capital, it can act as a pressure valve for lower-rated borrowers, delaying stress signals in high yield and leveraged loans. That creates a short-term stability regime but raises medium-term refinancing risk: once maturities roll and rates stay high, weaker issuers may discover the private market is less forgiving than the headline inflows suggest.

On the software side, the market’s failure to punish new AI model releases suggests the “AI disintermediation” trade is losing traction near term. The winners are likely to be platform and infrastructure names with pricing power and distribution lock-in, while pure-play application vendors that were vulnerable to model substitution may see valuation risk compress. The contrarian read is that calm reactions can be a sign of fatigue rather than vindication; if the sector stops reacting to incremental model improvements, alpha will shift from headline beta to idiosyncratic execution and monetization over the next 6-12 months.

JPMorgan should be a relative beneficiary if private credit flows remain robust, since origination, financing, and market-making activity should support fee income and spread capture. The main risk is a sudden reversal in credit sentiment from one or two idiosyncratic defaults, which could freeze new issuance and expose crowded exposure quickly. That tail risk matters most over the next 1-3 months, while the AI signal is more of a 6-12 month positioning clue than an immediate catalyst.

Key Decisions for Investors

• Long JPM vs. regional banks over the next 1-3 months: JPM has better access to private credit distribution and can monetize client demand; target 8-12% relative outperformance if inflows stay strong.
• Add selectively to senior direct-lending managers / diversified credit vehicles on pullbacks for a 6-12 month horizon: inflow durability should support NAV and fee growth, but size positions modestly because liquidity can gap quickly if defaults surface.
• Short a basket of software names most exposed to AI feature commoditization for 3-6 months, paired against large-cap platform/infrastructure winners: use a market-neutral structure because the sector signal is about dispersion, not direction.
• Avoid chasing tight-spread public credit for now; prefer a barbell of high-quality IG and cash over HY beta until a catalyst forces wider spreads. Risk/reward is unfavorable if private credit keeps suppressing stress signals, but asymmetric on the downside if sentiment flips.
• If using options, consider call spreads on JPM into the next earnings cycle to express fee-income upside with defined risk; implied volatility should be more efficient than outright stock exposure.