If you have been tracking private credit markets over the past two quarters, a clear pattern has emerged: gates activating, redemptions accelerating, and even marquee names appearing in unfavorable headlines.
Blackstone’s BCRED saw redemption requests reach 7.9% of NAV in Q1 2026. BlackRock’s HLEND activated its 5% gate for the first time1. Apollo followed a similar path2. Blue Owl halted quarterly redemptions for OBDC II after selling $600 million in loans to meet outflows.
These are not isolated incidents. Nor are they primarily driven by deteriorating loan performance. In many cases, the underlying assets remain fundamentally sound.
This distinction is critical. A liquidity event is not the same as a credit event. But if they are not managed effectively, one can quickly trigger the other. This is why structural vulnerabilities and risk management gaps are becoming increasingly visible.
The Default Picture Is Getting Harder to Interpret
Default rates are rising, but the signal is more nuanced than the headlines suggest.
Fitch reported a 9.2% default rate in 2025 across its monitored universe, up from 8.1% in 2024. Notably, defaults are concentrated among smaller issuers (sub-$25M EBITDA) and are dispersed across sectors rather than clustered.3
More importantly, traditional default metrics are understating risk. When distressed liability management exercises are included, the effective default rate is materially higher. The implication is clear: portfolio risk is underrepresented in reported NAVs, effectively widening the gap between stated valuations and economic reality.
For CIOs and risk managers, this disconnect is no longer theoretical. It is becoming a core portfolio concern.
Covenant Erosion Was Expected, But AI Disruption Was Not
As competition intensified, private credit managers systematically weakened covenants to win deals. In a low-rate, high-liquidity environment, this tradeoff appeared manageable.
That assumption is now being tested.
Specifically, a new, underpriced risk has emerged: AI-driven disruption, particularly in the software and technology sectors that dominate private credit exposure4. Private equity sponsors heavily consolidated mid-market software firms, attracted by recurring revenues and predictable cash flows. These businesses were considered “ideal credits.”
The rise of agentic AI, however, is challenging the value proposition of many of these companies.
This is not a uniform decline story. It is a dispersion story. In other words:
- Some firms are benefiting from AI tailwinds
- Others are seeing core revenue models erode rapidly
The real issue is concentration.
Private credit portfolios are significantly exposed to this segment at a time when outcomes are diverging sharply. Traditional underwriting frameworks built on assumptions of revenue stability, margin durability, and refinancing access were not designed to price technology obsolescence risk.
All these assumptions are now under pressure simultaneously.
The BDC Structure Has a Bank Run Problem
Business development companies were designed as a democratization vehicle, or a way to give retail and institutional investors access to middle-market private credit returns. The semi-liquid structure, which typically allows quarterly redemptions of up to 5%, seemed like a reasonable middle ground between the illiquidity of a closed-end fund and the daily liquidity of a public vehicle. What was less apparent during the build-up phase was how this structure behaves under stress.
When a fund’s stated NAV diverges from what investors believe is true, the logic becomes simple: exit before the gate closes. Once redemption requests breach the 5% threshold, the fund freezes. That freeze signals to the remaining investors that something is wrong, accelerating exit pressure across the category. In the fourth quarter of 2025, investors in private credit BDCs with over $1 billion in assets withdrew $2.9 billion. That is a 200% increase from the prior quarter.5
The underlying mechanism is valuation opacity. Because private loans carry no exchange-traded price, fund managers mark portfolios internally, typically at or near cost. That gap between internal marks and economic reality is tolerable when conditions are stable. But in an environment characterized by rising defaults, rising rates, and AI-disruption, it becomes the source of LP distrust.
What Disciplined Managers Are Doing Differently
None of these structural problems are unfixable. But addressing them mid-cycle is considerably harder than preparing for them in advance. The managers navigating this environment most effectively are, almost without exception, those who invested early.
These managers share specific characteristics. Real-time visibility into redemption pressure and liquidity buffers does not come from quarterly snapshots, but rather live dashboards with forward cash flow modeling across multiple stress scenarios. Independent valuation workflows with auditable trails reduce dependence on internal marks. Cross-portfolio analytics surface sector concentration risk, particularly software and AI-exposed lending.
Covenant monitoring has also become a differentiator. In a covenant-lite environment, managers with stronger early warning capabilities built infrastructure to track borrower financial performance continuously so they are not waiting for quarterly compliance certificates. Underwriting dispersion matters again in ways it simply did not when rates were suppressed and credit quality was rarely tested.
The LP trust problem requires something more than better data. Funds that proactively share valuation methodologies, stress scenario outputs, and concentration analyses retain capital through volatile cycles. Those relying on polished quarterly letters and stable NAV figures are finding that LP confidence, once it erodes, does not recover quietly.
The View From Where We Sit
What this cycle is making clear is that the gap between strong and weak outcomes is no longer purely a function of underwriting quality. It is increasingly a function of how quickly a platform sees risk accumulating and how confidently it acts before the decision window closes.
Firms navigating this issue from a position of control entered the cycle with four things in place:
- Dynamic scenario modeling that projects portfolio stress forward rather than reporting it backward
- AI-assisted credit surveillance that surfaces deterioration signals weeks ahead of traditional tool.
- Real-time liquidity visibility that makes redemption pressure manageable rather than reactive
- Audit-ready valuation infrastructure that gives LPs and auditors results they can actually interrogate
The industry is also constantly evolving. JPMorgan recently filed to launch a new private credit fund, this time with a 7.5% redemption sleeve, potentially on a monthly basis. Importantly, this fund is structured as an interval fund – a big difference from many of the world’s top private credit funds and one that invests in public securities, which could explain why they’re allowing for more liquidity than other funds.
IVP has worked with private credit managers across each of these dimensions: portfolio risk assessment, liquidity modeling, covenant monitoring, NAV transparency, and AI-driven credit deterioration signals. In these engagements, we are not just a software vendor, but rather a partner that understands how capital moves through these structures and where the blind spots tend to matter most. From our perspective, the conversation worth having right now is a direct one: where is your platform most exposed, and what will closing that gap actually require? That is where we start.
Learn more about IVP for Credit or contact sales@ivp.in to schedule a demo.
Frequently Asked Questions
Q – Is the current pressure on private credit driven by deteriorating loan performance or a liquidity problem?
A- The current issues are primarily a liquidity event, not necessarily a credit event, as the underlying assets often remain fundamentally sound. However, if liquidity events (like surging redemption requests) are not managed effectively, one can quickly trigger the other.
Q – How is AI disruption affecting private credit portfolios?
AI-driven disruption is a new, underpriced risk, particularly in the software and technology sectors where private credit exposure is concentrated. This is creating a “dispersion story,” where some firms benefit from AI tailwinds while others see their core revenue models rapidly erode. Traditional underwriting frameworks were not designed to price this “technology obsolescence risk”.
Q – What is the main structural vulnerability in BDCs that leads to redemption pressure?
The main vulnerability is the semi-liquid structure, typically allowing quarterly redemptions of up to 5%, combined with valuation opacity. When investors perceive a divergence between the stated Net Asset Value (NAV) and economic reality, they try to exit before the 5% redemption gate closes, which accelerates exit pressure across the category and creates a “bank run” problem.
References:
- Bloomberg Post, March 9, 2026 https://www.bloomberg.com/news/features/2026-03-08/blackrock-blackstone-confront-withdrawals-as-private-credit-redemptions-surge
- Reuters Post, March 24, 2026 https://www.reuters.com/markets/europe/apollos-private-credit-fund-limits-investor-withdrawals-after-redemption-2026-03-23/
- Reuters Post, March 7, 2026
https://www.reuters.com/business/us-private-credit-defaults-hit-record-92-2025-fitch-says-2026-03-06/ - Private credit’s software lending meets AI disruption
https://www.bis.org/publ/qtrpdf/r_qt2603v.htm#:~:text=Software%20companies’%20stocks%20collapsed%20by,signalling%20worries%20about%20underlying%20valuations. - SP Global Post, March 17, 2026 https://www.spglobal.com/ratings/en/regulatory/article/bdcs-exposure-to-software-stays-high-steady-s101675136
