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Evans, who chairs Stop Scams UK, an initiative she founded in 2019 to unite banks, technology companies and telecom providers to combat payment fraud, will assume the position on 30 September, commencing a five-year term.
The DCMS has said she brings extensive experience from her long-standing career in public protection and financial crime prevention.
Her previous leadership roles include chairing the Independent Parliamentary Standards Authority (IPSA), the Bar Standards Board and acting as a lay member of the General Medical Council.
About Don Premiote
During the second half of 2026, prediction markets have endured the wrath of a plethora of state governors, most notably Kathy Hochul of New York.
As the NFL season begins, a state in close proximity to the New England Patriots became the latest to attempt to curb the influence of the trading platforms. On 10 September, one day after the Pats’ season-opening loss to the Seattle Seahawks, Connecticut Governor Ned Lamont addressed the growth of the markets during a speech in downtown Hartford. On the same day, the Connecticut Department of Consumer Protection issued cease-and-desist orders to nine unregulated operators, including Polymarket, Robinhood and Underdog Predict.
“Prediction markets have branded themselves as legal and safe, but the reality is they are not adhering to Connecticut’s consumer protection standards,” Lamont wrote in a statement.
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His analogy is a poker table at which the weaker participants sustain the game. If those players disappear, the fourth-best professional at the table can suddenly become a loser because only the three strongest remain.
The US addressable market is vastly larger and customer recruitment remains strong. Marantelli says Kalshi increased its number of clients fivefold during the World Cup, while White Swan predicts that NFL prediction markets could generate between $5 billion and $7 billion of liability in a single week.
But he acknowledges the possibility that faster customer losses could eventually test the sustainability of the model.
