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Strip away the language of contracts, order books and event trading and Bernard Marantelli has a blunt description of what is happening inside US sports prediction markets. “Kalshi is a sportsbook that’s just not allowed to have an in-house risk team,” says the founder of White Swan Data, one of the specialist firms now making markets on prediction exchanges.

The difference is all about the risk function. A sportsbook employs traders to price bets and manage its exposure. An exchange provides an API through which firms compete to quote prices and supply liquidity.

“Here’s an API. Bernard and 88 other people can market-make all these request-for-quotes (RFQs),” Marantelli says. “Some people might come in and just do esports because they’re esports experts. Others do everything. Some focus on same-game parlays. But it’s a sportsbook.”

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They must also evaluate their current technical safeguards to ensure alignment with regulator expectations and certification standards.

Safeguarding has reappeared as a focal point for the regulator. In July of this year, ANJ imposed a €500,000 ($572,797) fine on an unnamed online betting operator, referred to as Company X, for not adequately identifying and supporting customers exhibiting signs of problematic gambling. 

The fine followed an investigation that found Company X had failed to correctly identify 29 high-risk players at an appropriate risk level. Six players were missed entirely and 23 were misclassified at a lower risk tier. 

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