White Swan captures major share of parlay volume on prediction exchanges

White Swan takes forty percent of parlay volume on some prediction exchanges

Bernard Marantelli does not describe his firm as a financial technology company. He describes it as a sportsbook that someone else is legally required to operate.

That framing is more precise than it sounds. White Swan Data, the London-based outfit Marantelli founded, accounts for as much as forty percent of activity on some prediction exchanges, concentrated in the parlay market where institutional capital has the clearest edge. Marantelli says parlays offer better margins and fewer credible competitors than singles. The math behind a parlay requires a firm to model correlations between multiple outcomes and respond to individual requests in real time. That is not something a casual trader does twice a month. It is a skill set built over years in the sharper end of European sports betting, and the firms that have it are now moving it into a US market that was not designed to contain them.

Here is the structure underneath what customers see. A prediction exchange presents as peer-to-peer: you and I trade on whether the Eagles cover the spread. But the depth required for a mass-market product cannot come from occasional users. Someone has to quote continuously and commit real capital. On Kalshi and the secondary exchanges that have grown alongside it, that someone is White Swan, Susquehanna, Jump Trading, and a tier below them of perhaps a hundred smaller operations ranging from individual traders to teams of ten. Enda Kendrick, who runs service provider Veltium, says the largest UK and European sharp-betting groups have already moved in. The institutional layer is invisible to the retail customer, which is precisely the point.

Marantelli's description of Kalshi as a sportsbook without an in-house risk team is not a criticism. It is a technical observation about where the risk function sits. A traditional sportsbook employs traders to price its book and manage exposure internally. An exchange externalizes that function through an API and lets firms compete to supply it. The exchange takes a fee. The risk sits with whoever quoted the price. White Swan quoted the price.

I have seen this dynamic in other thin markets where institutional liquidity gets retail framing — the retail customer believes they are trading against the crowd, and is actually trading against a firm that has modeled the outcome more carefully than any crowd could. The customer experience is unchanged. The odds are not.

The legal argument playing out between New Jersey, Michigan, and the CFTC is about jurisdiction. The market structure argument is different and harder to resolve by statute. New Jersey Attorney General Jennifer Davenport filed a forty-seven page Supreme Court petition on Wednesday arguing that Kalshi's sports contracts are wagers subject to state law, not swaps under the Commodity Exchange Act. She is correct that the circuits are split and that the Supreme Court will eventually have to resolve it. She is not asking the right question about what happens to retail customers in the meantime.

The institutional market-making layer continues operating regardless of how the jurisdictional case lands. If states win and geofencing expands, the professional firms route capital elsewhere. If the CFTC's preemption holds, the same firms deepen their positions on a federally protected exchange. Neither outcome changes the asymmetry between a retail customer placing a same-game parlay and the firm on the other side that built its pricing model in the London sharp-betting ecosystem.