Credit risk has traditionally been monitored through a familiar collection of fundamentals, ratings and market prices. But as private and public credit markets become more interconnected, investors are looking across a much wider range of data for signs that a borrower – or an entire sector – may be running into trouble.
That search for earlier warning signals was at the centre of a panel on “Private credit, public markets and emerging risk signals” at the recent A-Team/Eagle Alpha Alternative Data Conference in New York. The discussion explored where deterioration first becomes visible, the limits of transparency in both public and private markets, and whether alternative data can identify problems before conventional credit analysis catches up.A widening credit information network
The dividing line between public and private credit is becoming increasingly difficult to draw. Borrowers can have bonds, broadly syndicated loans and privately negotiated debt outstanding simultaneously, while lenders and asset managers may operate across several of those markets.
That creates potential channels through which stress in one market can provide information about another. Sector concentration can amplify the effect. Data centres were cited during the discussion as one example, with heavy capital expenditure requirements driving significant borrowing across the sector. Problems emerging among one group of borrowers could therefore carry implications for comparable credits elsewhere.
The growth of investment vehicles providing broader access to credit introduces another connection. BDCs, funds and other structures can give investors exposure to assets that remain considerably less liquid than the vehicles through which they are accessed.
Private credit nevertheless presents a particularly acute information problem. Lending arrangements are negotiated directly between borrowers and lenders, leaving outside investors with limited visibility into changing financial conditions, covenant performance or valuations. In stressed situations, that can mean a private debt position moves rapidly from close to par to a deeply impaired valuation with relatively little warning visible externally.
But public markets aren’t necessarily as transparent as they appear. A quoted bond price may bear little relationship to the price available to an institutional investor trying to sell a substantially larger position. Liquidity therefore becomes part of the information set: the observable price matters, but so does the ability to transact at or near it.
When the market moves before the numbers
Alternative data becomes particularly interesting when the sequence between corporate performance and market reaction begins to change. Traditionally, a deterioration in financial results might become visible through an earnings announcement, followed by adjustments in bond prices and liquidity. Increasingly, the panel heard, prices can begin moving before updated fundamentals appear. In more serious cases, liquidity may also start disappearing.
Alternative data offers one possible explanation. Investors monitoring business activity during a quarter may already be seeing evidence of deterioration before it reaches reported financial statements.
That extends a recurring theme: the value of higher-frequency alternative data may lie as much in monitoring risk and testing existing positions as in generating new investment ideas. Intraday signals can provide additional evidence about whether the assumptions supporting an existing position continue to hold.
Building a broader picture of deterioration
There is unlikely to be a single dataset capable of providing a definitive early warning signal.
The discussion covered familiar alternative sources such as credit and debit card transactions and foot-traffic data, but also a broader collection of observable indicators: CDS and other derivatives, ETF pricing and holdings, bilateral OTC transactions, rates and inflation expectations, executive departures, delayed product launches, changes in customer behaviour and regulatory developments.
The usefulness of those signals varies according to the borrower and exposure. Consumer transaction data might reveal changing retail activity, while movements in interest-rate expectations could provide more useful information about the pressure building on floating-rate borrowers.
The emphasis is therefore on combining signals rather than finding a single substitute for conventional analysis. Financial statements and fundamental credit data remain important, but market, liquidity and alternative datasets can provide additional perspectives on what is happening between reporting periods.
That increasingly reflects the wider direction of institutional data strategies, where traditional market data, alternative signals and derived datasets are becoming part of the same operational continuum rather than separate categories of information.
Recent A-Team Group research into fixed-income pricing found firms increasingly incorporating cross-asset signals including ETF prices, CDS indices and macro futures into bond valuations, while the growth of private credit is increasing demand for borrower financials, covenant data and independently verifiable valuations.
Proving that an early signal really is early
Access to more data doesn’t automatically improve credit risk monitoring. Investors still have to establish whether a signal genuinely anticipates deterioration or merely explains something already reflected in market prices.
That places considerable importance on point-in-time data. Researchers need to know precisely when information became available and what period it represented before testing whether it consistently preceded subsequent price movements. A handful of successful examples isn’t enough: useful signals need to demonstrate predictive value across a sufficiently large sample while keeping false positives under control.
The limitations were neatly illustrated when a panelist was asked whether a recent credit event came to mind where warning signs had clearly been visible in the data before the market reacted. The answer was simply: “No.”
Alternative data can help narrow the blind spots inherent in credit markets, particularly as monitoring expands beyond fundamentals to include prices, liquidity, derivatives, transactions and real-world indicators. The aim is to spot deterioration earlier, before it becomes evident through conventional credit analysis.
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