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Kambi is now rolling out AI trading across other sports, including basketball, ice hockey and American football. Its longer-term ambition extends beyond automating established processes to using the technology to create products that could not previously be delivered at scale.
The aim is an on-demand sportsbook capable of offering the right bet to the right customer at the right time. Lamb believes Kambi’s network of more than 70 partners provides an important advantage in pursuing that goal. More than €17 billion in annual liquidity and billions of bets placed each year give its models a depth of information that can improve pricing, risk management and product development.
“The term AI is everywhere across the world of technology, and the betting and gaming industry is just one where its impact is being felt,” Lamb says. “Taking AI beyond being a buzzword, building and deploying the systems and automation necessary to maximise its potential and deliver the right results is the challenge each of these industries face.”
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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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“The big change is that technology can increasingly provide the infrastructure,” he says. “The creator provides the idea. And I think that will make the industry much more interesting.”
For Yggdrasil, Game in a Box and Studio in a Box are therefore intended to become more than tools for its own development operation. Curwen envisages them supporting a wider creator ecosystem, although he acknowledges that proving the model commercially must come first.
“We’re still early,” he says. “The priority is to prove the model properly; make sure the games perform and demonstrate that it works commercially. If we do that, I think the opportunity is significant.”
