The Private Credit Boom Is Creating A New Risk: Bad Data
Private credit’s rapid growth is outpacing the infrastructure investors use to monitor it.
Nine in 10 firms surveyed by London Stock Exchange Group (LSEG) are already active in private credit or planning to expand into the asset class, underscoring how quickly private lending has moved into the mainstream. But as more money flows into privately negotiated loans, the market’s supporting infrastructure is under pressure.
Critical information can be scattered across different systems, formats and sources, making it harder to establish a consistent view of borrower performance, covenant compliance and valuations.
"The burden of proof sits heavily on the data architecture," LSEG said. The concern is becoming more apparent as investors demand greater visibility into increasingly complex portfolios.
Kanav Kalia, managing director at Oxane Partners, previously said that the market is reaching a point where "the industry needs a more consistent operating infrastructure." He pointed to isolated cases involving fraud, double pledging and other problems as evidence of gaps in how private-credit portfolios are monitored and reported.
Those concerns go beyond individual loans. Institutional investors increasingly want to understand their exposure at the borrower and loan level, including portfolio concentration and potential early warning signals.
Where Private Credit Data Gets Messy
Unlike public bonds, private loans can have customized structures and borrower-specific covenants, and financial information isn’t disclosed in the same standardized way.
LSEG’s research highlights how fragmented the process can be. Half of firms surveyed by A-Team Group rely on third-party data vendors to track covenants and performance metrics, while 28% maintain direct relationships with borrowers and issuers to collect financial statements and compliance certificates. Another 22% use proprietary internal systems to parse and monitor credit agreements, according to LSEG.
The different approaches are not necessarily problematic on their own. But they illustrate how private-credit data can become fragmented across investment platforms.
"When workflows depend on varied sourcing models, consistency and defensibility become harder to maintain," LSEG said.
That becomes particularly important when a borrower starts showing signs of stress. A missed covenant, weaker financial results, or a change in collateral value can alter a loan’s risk profile. If those developments are difficult to track across systems, investors could have a harder time identifying deterioration across a portfolio.
Valuations Present Another Challenge
Private-credit investments generally lack the continuously observable market prices available for public securities. Investors therefore rely more heavily on financial information, models and assumptions to determine what loans are worth.
LSEG noted that "a valuation is not simply a number," but reflects "inputs, assumptions, judgment and governance."
Kalia said investors are already pushing for greater valuation transparency, with some funds considering or moving toward daily valuation processes. That shift reflects a broader demand for more visibility into underlying assets rather than relying solely on fund-level performance.
AI Raises The Stakes
This challenge is intensifying as private-credit managers turn to AI to process loan documents and flag risks — but AI can’t compensate for incomplete or inconsistent underlying data. That makes granular data only more critical as the asset class grows.
The private-credit boom has largely been measured in dollars. The next test is whether investors have the information to know exactly what they own — and to catch risks before they become portfolio-wide problems.
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