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A total of 22 participants were purposely recruited to provide detailed insights.
Participants broadly accepted the principle that gambling information should be transparent and accessible, but many reported difficulty interpreting or using it effectively in practice.
Technical data such as odds and rules were often obscured by delivery timing that came too late to influence decisions.
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Atucha warns there is a tipping point where higher taxes can undermine channelisation, citing the UK and Germany as important case studies.
“I sometimes wish regulators would look at other cases,” he adds. “I mean, what happened in Germany, what’s happening in the UK.”
This risk is particularly apparent when many offshore operators are established brands rather than unknown entities.
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“In simple terms, what we have undertaken is a shift from machine-assisted human trading to human-assisted machine trading,” Lamb explains.
The shift means that rather than spending their time pricing and managing established markets, traders can now apply their expertise where human judgement has the greatest value, including developing and testing new products. AI removes many of the practical limits on what can be offered and priced, and manages the resulting scale and complexity. The result is greater efficiency for Kambi and a better service for its partners and their customers.
“To this point, sportsbook product creation has largely been guided by a trading department’s ability to profitably price and risk-manage certain bet offers,” Lamb says. “AI trading lifts those limitations, while also enabling that existing human expertise to be leveraged more effectively.”