Cross-vehicle exposure

Cross-vehicle exposure measures how many different BDCs, interval funds, and CEFs hold the same underlying credit at the same time. When a borrower has loans outstanding to ten different BDCs simultaneously, that's ten times the contagion surface if the borrower runs into trouble — each lender takes a hit, and because BDCs increasingly hold overlapping credits, a borrower default ripples across the asset class instead of being contained.

This view is hard to construct from filings alone for two reasons. First, the same borrower may appear under slightly different names across filings — "Petsmart, Inc.", "PetSmart, Inc.", "Petsmart Holdings" — so naive name matching misses overlaps. Real cross-vehicle analysis requires entity resolution: canonical-ID matching across LEI, CUSIP, ISIN, and fuzzy name comparison. Second, no single SEC dataset cross-references BDC Schedule of Investments with N-PORT fund holdings — analysts have to join them themselves.

Once cross-vehicle exposure is computed, the analytics become powerful. You can rank credits by how concentrated the exposure is (a credit held by 15 BDCs at 0.5% NAV each is materially different from one held by 3 BDCs at 2% NAV each). You can identify cases where one BDC marked a credit down 200bps while five peers held it flat — a likely mark dislocation. You can quantify a portfolio's "shared credit" percentage versus exclusively-held credits — a useful diversification metric that most BDC analytics products don't expose.

SpreadVista's entity resolution layer canonicalizes every issuer across 74 BDCs and 32+ credit-focused funds, makes the cross-vehicle view available on every credit, and is the differentiator behind the product's core promise: see the entire credit picture, not just one vehicle's slice.